Abstract: Introduction to LLM vulnerabilities This introductory course on vulnerabilities for Large Language Models (LLMs) and language models in general. It provides a deep dive into the practical applications of large language models (LLMs) using Azure's AI services. Upon completion, learners will be able to: Explain the concept of model replication or model shadowing as a potential attack vector in large language models, and describe methods to mitigate it through techniques like rate limiting and buffering. Analyze the potential benefits and limitations of using pre-trained LLMs Develop strategies for mitigating risks and ethical considerations when deploying LLM-powered applications. Describe the high-level process of creating a large language model, including data collection, cleaning, and training. Explain the role of security in large language models and recognize potential security vulnerabilities and attack vectors. Identify insecure plugin designs in large language model software development kits (SDKs) that could lead to remote execution and implement strategies to secure plugins. You will learn how to secure your large language model (LLM) applications by addressing potential vulnerabilities. You will explore strategies to mitigate risks from insecure plugin design, including proper input validation and sanitization. Additionally, you will discover techniques to protect against sensitive information disclosure, such as using a redaction service to remove personally identifiable data from prompts and model responses. Finally, you will learn how to actively monitor your application dependencies for security updates and vulnerabilities, ensuring your system remains secure over time. Week 1: Foundations of Language Models This week you will get a brief overview of LLMs and how do they work Learning Objectives Analyze common types of generative applications and their architectures, including multi-model applications, and understand their challenges and benefits. Explain the functioning of a multi-model application, including the role of the framework and specialized machine learning models. Identify the advantages of smaller, specialized models in terms of resource usage, interaction speed, and deployment agility. Compare and contrast different generative AI application types, such as API-based, embedded models, and multi-model applications, and understand their use cases and challenges. Recognize the importance of large language models in various real-world applications, including text-based chatting, customer service, content creation, and daily tasks. Evaluate the benefits and drawbacks of large language models, considering aspects like accuracy, privacy, and potential misuse. Understand the basics of tokenization, indexing, and probability machines in the context of large language models. Describe the high-level process of creating a large language model, including data collection, cleaning, and training. Explain the role of security in large language models and recognize potential security vulnerabilities and attack vectors. Week 2: Language Model Vulnerabilities This week focuses on model-based vulnerabilities that you can explore with prompts. Learning Objectives Explain the concept of model replication or model shadowing as a potential attack vector in large language models, and describe methods to mitigate it through techniques like rate limiting and buffering. Identify and demonstrate insecure output handling in large language models, and understand the potential security threats and attack vectors associated with it. Understand prompt injection and its implications for large language models, including how certain applications define the initial behavior of these models and how to exploit implicit system prompts. Recognize model theft vulnerabilities and understand how handling and access to system components can impact model security, particularly in the context of dynamically loaded models from external sources. Week 3: System vulnerabilities This week you will learn how to deal with environments and system-based vulnerabilities as they relate to LLMs. Learning Objectives Identify insecure plugin designs in large language model software development kits (SDKs) that could lead to remote execution and implement strategies to secure plugins. Explain the potential risks of sensitive information disclosure in large language models and implement measures to redact personal identifiable information using HTTP APIs and regular expressions. Monitor and update dependencies in large language model applications to prevent potential security vulnerabilities and automate the process using tools like GitHub's Dependabot. Evaluate application vulnerabilities based on the programming language and framework, and implement measures to prevent potential security threats. Week 4: Other types of vulnerabilities Learning Objectives Identify potential security threats and vulnerabilities associated with large and small language models. Implement strategies to prevent security situations and guard against making environments more secure. Recognize the concept of excessive agency in large language models and its potential impacts on functionality. Explain the denial of service threat for large language models and describe methods to guard against API misuse.% About your instructor Alfredo Deza has over a decade of experience as a Software Engineer doing DevOps, automation, and scalable system architecture. Before getting into technology he participated in the 2004 Olympic Games and was the first-ever World Champion in High Jump representing Peru. He currently works in Developer Relations at Microsoft and is an Adjunct Professor at Duke University teaching Machine Learning, Cloud Computing, Data Engineering, Python, and Rust. With Alfredo's guidance, you will gain the knowledge and skills to understand and work with vulnerabilities within language models. Resources Introduction to Generative AI Responsible Generative AI and Local LLMS Practical MLOps book.

Abstract: Rust For DevOps Learn how to use and apply DevOps principles using Rust This is an early release of the course. In this course, you will learn the basics of DevOps using the Rust programming language. DevOps helps you build, test, and deploy code faster while creating a robust foundation for your projects and teams. First, we will talk about what DevOps is. You will learn things like automation, monitoring, and working together as a team. Then, we will see how to use DevOps ideas in Rust code. You will learn about version control, testing, containers, and deploying Rust programs. Although this course explains the foundations of DevOps and using Rust which is ideal for beginners, experienced Rust developers will find solid advice in how to apply DevOps best practices to existing applications. Learning Objectives The core principles and practices of DevOps How to apply DevOps concepts to build, package, and deploy applications with Rust The basics of containerization and how to leverage containers for DevOps with Rust Course Content This course is divided into 4 weeks with 3 lessons that contain about 6 videos each. Each video is about 5 minutes long and contains a hands-on demonstration of the concepts covered in the lesson. The course is designed to be taken in order, but you can jump to any lesson you want to learn more about. Week 1: Introduction to DevOps Principles Introduction to DevOps Principles DevOps Considerations for Applications Basics of Containerization Week 2: Implementing monitoring and logging strategies Introduction to monitoring and logging strategies Tools and Services for monitoring and logging Logging with Rust About your instructor Alfredo Deza has over a decade of experience as a Software Engineer doing DevOps, automation, and scalable system architecture. Before getting into technology he participated in the 2004 Olympic Games and was the first-ever World Champion in High Jump representing Peru. He currently works in Developer Relations at Microsoft and is an Adjunct Professor at Duke University teaching Machine Learning, Cloud Computing, Data Engineering, Python, and Rust. With Alfredo's guidance, you will gain the knowledge and skills to build robust applications and infrastructure with the Rust programming language and for Rust applications. Resources Rust Bootcamp Deploy Rust on Azure Functions DevOps command-line tools in Python and Rust Switching to Rust from Python First Steps with Rust Learning Path.

Abstract: Azure Databricks with Pandas and Open Datasets. Find out how to get a working cluster with Databricks using Azure and then use the full Pandas API operating in the cluster with Open Datasets and a Python Jupyter Notebook. This video will walk you through creating a workspace in Azure to create the Databricks service, then create the cluster that comes with the Pyspark Pandas API, and finally import the open datasets into the cluster. Although straightforward to create a Databricks cluster with Azure, it is a bit more involved to run a Python Jupyter Notebook that has Azure ML Open Datasets installed and availabe in the cluster along with the ability to use the full Pandas API you are used to working with and taking advantage of the clustering capabilities from Databricks.

Abstract: Python Command Line Tools Course This is a full Python CLI course that will take you from the most basic approaches to command line tools in Python to the more advanced featuers that use frameworks like argparse and Click. Everything on this course is available in the course Repository on GitHub, so that you can follow the examples closely and use that as a foundation with all examples and sample files. Building a CLI is the foundation for automation in your daily work By the end of the course you should feel confident in creating a tool, and the following: Create simple CLI tools without any frameworks Learn about arguments, flags, help menus and how to create them automatically Use the argparse framework to build more complex tools Build a CLI with the Click framework Use special features of Click like colored output and argument types Modularizing and project scaffolding in Python Packaging and packaging files in Python How to create tests and run them automatically Continuous Integration and Continuous Deployment with Github Actions for Python Packaging a CLI tool with an executable Distributing a CLI tool on PyPI (the Python Package Index) How to automatically test your project on a PR (GitHub pull request) How to automate publishing your tool to PyPI on a release We'll cover 3 different ways to create tools, from the very basic (with sys.argv) to using a framework that comes with Python ( argparse), and finally the more involved, by using an external library like Click. This flexibility is essential because it will let you decide when to use a simple single file with no dependencies to a fully featured framework like Click. Then you will learn about the project layout, modularizing and organizing your code in directories and files while keeping everything useful for a CLI. You will test your code using Pytest and then package your code using Python packaging files and tools. You will continue by automating everything, including the testing and linting using GitHub Actions, and finally publishing your project to the Python Package Index so that it can be installed by anyone in the world. Course Resources Course Repository on GitHub Build Python applications from scratch.

Abstract: What is the if __name__ condition in Python for? If you've seen __main__ at the end of a Python script and wondered why that is there it is to avoid side effects when importing and allowing you to run the file as a script on the terminal. If you want more details, watch this short video where we work with a Python script to find out those side effects and how the Python script can change once the if condition with __name__ is done at the end. Next Steps Now that you know about the conditional at the end, you might want to explore writing Python scripts that use this trick. There are several examples you can follow in these GitHub repositories with argparse, the Click framework and using sys.argv: argparse GitHub repo examples sys.argv GitHub repo examples Build Python applications from scratch.

Abstract: What does the Yield keyword do in Python? This video covers the basics so you can understand what yield is, what is a generator, and why is it different than any other iterable in Python A yield keyword makes a function a lazy iterable. Producing values one at a time. The function becomes a generator, so when called, the code will not execute. A generator is a function that uses the yield keyword. This function is an iterable that produces values one at a time, or does a lazy production of values. I'll use a Jupyter Notebook that you can use to follow along with practical examples that will show you what are some of the key differences and when or why you would use the yield keyword. In this video you will learn: What is an iterable and how is it different from using yield? What does yield do to a function? What is a Python generator Potential uses for a Python generator like infinite results Useful Resources GitHub repository with examples Build Python applications from scratch Try Azure for Free Introduction to Azure Databricks.

Abstract: One of the important aspects of MLOps, also known as Machine Learning Operations or Operationalizing Machine learning, is to package ML models. How exactly do you package ML models? In this video I show you exactly what that means, and go through the process of packaging an ONNX model taken from the ONNX Model Zoo. I end up with a docker container that can be shared, exposing an API that is ready to consume and perform live predictions for sentiment analysis. Topics include: * What are the concepts behind packaging Machine Learning Models * Create a sentiment analysis API tool with Flask * Define dependencies and a Dockerfile for packaging * Create a container with an ONNX model that can be deployed anywhere with an HTTP API A few resources that are helpful if you are trying to get started with SBOMs, generating them and using them to capture vulnerabilities: * The RoBERTa ONNX Model * Schema labeling concetps for Docker containers * The Practical MLOps code respository full of examples

Abstract: Learn to use AWS App Runner to do an MLOps workflow that deploys a Flask Microservice that running sklearn. This tutorial walks you through how to deploy code from the O'Reilly book Practical MLOps using the AWS App Runner Service. Topics include: * MLOps * AWS App Runner * Container as a Service * Python * Flask * Microservice * Sklearn * Machine Learning Engineering

Abstract: Packaging in Python has always been polarizing. From complicated beginnings where you couldn't uninstall libraries, to virtualenv that allows you to work in a self-contained environment that can be thrown away. In this video, I'll present an introduction to Conda, and to a chanel-specific variation of it that is maintained by the community called miniforge. If you are looking for a way to get scientific packages for the new Apple M1 silicon, this video will also help you out get everything sorted, including installing versions of Python that are pre-packaged and ready for data science tasks. Topics include: * Install Conda by using the community version called miniforge. * Use conda to install a specific version of Python, without system installs * Find more about the differences between virtualenv, pip, and conda * Install data science libraries in the new Apple M1 silicon Useful links: * Conda documentation * Conda Forge community documentation * Conda miniforge project

Abstract: Learn to ruthlessly scrape data using APIs you discover as well as cut and paste. Topics include: * Business Analytics * Data Science * Google Colab * Jupyter * Scraping * Cut and Paste * Google Sheets * Cleaning Data * Using Pandas with found data * Using the Twitter and Pandas API

Abstract: Learn to use optimization strategies and greedy algorithms in one hour.

Abstract: Use FastAPI to expose an HTTP API for fast live predictions using an ONNX Machine Learning Model. FastAPI is a Python web framework that provides easy development of documented HTTP APIs by offering self-documented endpoints with Swagger - a tool to describe, document, and use RESTful web services. Learn how to quickly put together an API which validates requests, and self-documents its endpoints using OpenAPI via Swagger. Quickly produce a robust interface for others to consume your Machine Learning model by following core best-practices of MLOps. Parts of this video cover the basics of packaging Machine Learning models, as covered in the Practical MLOps book. Topics include: * Create a Python project to serve live predictions using FastAPI * Use a Dockerfile to package the model and the API using Docker containerization * With minimal Python code, expose an ONNX model to perform sentiment analysis over an HTTP endpoint * Dynamically interact with the API using the self-documented endpoint in the container. Useful links: * Demo Github Repository with sample code * Practical MLOps book * FastAPI Intro tutorial * RoBERTa ONNX Model for sentiment analysis

Abstract: Learn about six key elements of MLOPs based on the best-selling book Practical MLOps Topics include: * Source Code Management * Continuous Integration and Continuous Delivery * Development Environment * Deploy Environment * Microservices including Flask and FastAPI * Business Logic

Abstract: Learn to master key components of Python functions. Topics include: * Input, Output and Unit of Work * Decorators, Yield Statements, Generators, Closures and Nested Functions * Using Github Codespaces and Github Actions * Building Command-line tools * Microservices including Flask and FastAPI * Using AWS Cloud9 along side AWS App Runner

Abstract: Learn to get started on the right setup on your first day as a data scientist or business analytics professional. Topics include: * Business Analytics * Data Science * Google Colab * Jupyter * Github Actions and Github Codespaces * Continuous Integration and Delivery * EDA * GCP * AWS * Azure

Abstract: Learn to use optimization techninques along with AWS Step Functions

Abstract: A walkthrough of Chapter 7 of the O'Reilly book Practical MLOps. Learn about real-world computer vision including a recap of Tesla AI day 2021. Topics include: * Getting models into production * Tesla FSD * Tesla Computer Vision * Tesla AI Day * DataOps * ML Platforms * Sagemaker * Continuous Integration and Continuous Deployment * MLOps cookbook * ML Engineering * Data Engineering * AWS App runner * GCP * Azure * Containers * Kaizen

Abstract: Learn to build Computer Vision MVPs quickly using AutoML. Topics include: * Getting models into production * Apple Create ML * Google Vertex AI * Image Classification * CoreML * Tensorflow * Rapid Prototyping * GCP * Azure * Containers * Kaizen

Abstract: Learn the foundations of MLOPs Topics include: * Linux and Bash * AWS Cloud9 and AWS Cloud Shell and other Cloud Topics * The intuition behind MLOps techniques: optimization, gradient descent and data science.

Abstract: Topics include: * Solar * Tesla * Nest * Smart Home * Time of Use * Net metering * Battery Backup * EV (electric vehicle) * Artificial Intelligence * Level 1 Charging * Level 2 Charging * Level 3 Charging

Abstract: Use AWS Step Functions to solve problems

Abstract: It is essential to have a strategy defined when figuring out your career. Starting out is difficult. Regardless what your background is, you need to have a clear idea how to get to your dream job. Even if you are not in technology and want a data-science position, you have to have a clear path towards data-science. In this video I'll cover some of the stories that allowed me to gain perspective in my career in tech, along with some advice that can help you out. Topics include: * Find some techniques to define your career and next steps * Design a custom strategy to help answer career questions * Accurately determine what might be a good job or position Useful links: * Start a career in Tech * Learn Python from scratch

Abstract: Learn the foundations of Agile Project Management in this quick video snippit featuring global technical project management expert Jerry Castro. Topics include: * Agile * Balancing chaos vs order * How to get started with Agile

Abstract: A walkthrough of Chapter 5 of the O'Reilly book Practical MLOps. Topics include: * Getting models into production * Feature Store vs Data Warehouse * AutoML * MLOps * DataOps * ML Platforms * Sagemaker * Continuous Integration and Continuous Deployment * MLOps cookbook * ML Engineering * Data Engineering * Spark * GCP * Azure * Containers * Kaizen

Abstract: Apply DevOps principles to Jenkins by automating tasks using the Jenkins API with Python. Create a powerful command-line tool with the Click framework to harness the API and trigger remote jobs with a simple invocation. Using code (and Python in this case) to automate frequent tasks is an import DevOps principle that you should apply whenever possible. Some of the concepts in this video are covered in the Python For DevOps book. Learn how to identify core concepts when trying to automate something like Jenkins, like identifying the API access, authorization, and the possibility of finding a helper library to make things easier. your Machine Learning model by following core best-practices of MLOps. Topics include: * Setup a main Jenkins instance with Docker, using the official Jenkins LTS image. * Create a user with an API token, so that it is authorized to operate Jenkins. * Use a Jupyter notebook to try out the API using Python and figure out concepts that can be applied later * Create a command-line tool using the Click framework to quickly trigger Jenkins jobs. Useful links: * Jenkins LTS Docker image documentation * Official Jenkins LTS Docker image * Python-Jenkins library documentation * Python-Jenkins Library * Python for DevOps Book

Abstract: A walkthrough of Chapter 1 of the O'Reilly book Practical MLOps. Topics include: * DevOps * MLOps * DataOps * ML Platforms * Sagemaker * Continuous Integration and Continuous Deployment * MLOps cookbook * ML Engineering * Data Engineering * Spark * GCP * Azure * Containers * Kaizen

Abstract: Learn to use AWS Elastic Beanstalk to deploy a Flask application. This tutorial covers Continuous Delivery of a Python Flask application using AWS Code Build. Elastic Beanstalk is a PAAS (Platform as a Service) that has powerful tools and integrations. This video course covers building out an development environment in Cloud9, a Makefile system and then finally, a full fledged CI/CD pipeline using Pylint and AWS Code Build of a Flask API. Follow along with the Github Resource: https://github.com/nogibjj/Flask-Elastic-Beanstalk.

Abstract: Get started with Github and Github Actions in this introductory video to GitOps concepts, by building a container, setting some Github Actions to prevent problems, and finally, push to DockerHub in a fully automated way. These concepts are critical to get automation best-practices in place with Github. Particularly useful when collaborating with others and trying to run automated checks on Dockerfiles and git repos. Topics include: * Create a new Github repository * Enable Github Actions checks and steps for a new repository. * Find a Github Action to lint and check a Dockerfile to prevent issues before merging on pull requests. * Add Github Secrets and reuse them in a Github Action * Validate that a container builds correctly, and automatically push to dockerhub

Abstract: AWS Machine Learning Certification In ONE HOUR!

Abstract: Learn some counter-intuitive ways to think about programming as a beginner. It is ok to feel stupid, it means you are on the right path! Topics include: * Failure is good * The goal of programming is to reduce complexity * Automation is a requirement * Continuously Improve your code * Embrace Automation and Monitoring

Abstract: Learn to build Machine Learning solutions without writing any code with CreateML from Apple. Topics include: * Computer Vision * Image Classification * OS X * Apple * Core ML

Abstract: Learn to use Google AutoML Vision to train models with out writing code. Topics include: * Google AutoML Vision with Corel.AI * Core ML * Tensorflow Lite * Edge Inference * MLOps for Edge Computer Vision

Abstract: Learn to think like a Venture Capitalist about your career and design for failure. Topics include: * Cost of Living * Open Source Software * Investments * Designing your 1-3 year experiences * Being proactive vs reactive

Abstract: Learn to pass ANY AWS Certification Exam on the first try. Topics include: * AWS Certifications * AWS Certified Cloud Practitioner * AWS Exam Guide * AWS White Papers * AWS Sample Questions * AWS Cloud Shell * AWS Unofficial Questions * AWS Academy

Abstract: What is an SBOM (Software Bill Of Materials) and why should you care? An SBOM is a critical cybersecurity component to keep track and catalog what is installed (and at what versions) in production environments. With recent cybersecurity threats, SBOMs play an important role to implement a remediation strategy when threats and vulnerabilities are reported. Without an SBOM, it is borderline impossible to detect what exactly is released into production, and what may be vulnerable today. Topics include: * Understand the concepts behind an SBOM * Create an SBOM and use different output formats like CycloneDX to import into other systems * Use an SBOM to detect CVE and other vulnerabilities associated with installed software * Capture information about pre-installed system dependencies and nested dependencies * Use CycloneDX and other machine-readable formats like JSON to import outputs into other systems A few resources that are helpful if you are trying to get started with SBOMs, generating them and using them to capture vulnerabilities: * A simple, user-friendly SBOM generator: Syft * A fast vulnerability matcher that uses SBOMs as input: Grype * The CycloneDX format

Abstract: Learn to use Google AutoML to build a computer vision prediction model via their Qwiklabs website. Later, compare Apple's CreateML with the same data set and build an AutoML prediction model that deploy to the edge. Topics include: * Google AutoML * Apple CreateML * Apple CoreML * Computer Vision * Cloud Computing * Single label image classification * Using AutoML as a prototyping Tool * Edge Computer Vision Models

Abstract: Learn the essentials of Bash for Cloud Computing Topics include: * AWS Cloud Shell and Github Code Spaces Shell programming * Editing Bashrc * Using Vim * Using shell navigation including: cd, ls, pwd, history * editing the Bash prompt and creating simple Bash Scripts, as well as Python Virtual Environments with Bash

Abstract: Learn to use MLOPs methodology to build applied computer vision solutions. Topics include: * Apple CreateML * AutoML * Image Classification * Kaizen * Computer Vision

Abstract: Learn to tell stories with Data and then present those conclusions to Business Executives. Learn to use Colab/Jupyter Notebooks to build Data Science notebooks that tell a story. Topics include: * Effects of Intermittent Fasting, Sugar, Wealth and Real Estate Values on society * Visualizing data through Plotly graphs with 3D Interactive Visualizations of KMeans clustering * Using sklearn, pandas, plotly, matplotlib, KMeans clustering, ELI5, shap and other libraries * The role of the Matthew Effect on society. The Github Project is here: https://github.com/noahgift/data-story-telling

Abstract: Learn to use no-code and low-code solutions to perform Natural Processing. In this video you walk through building a text based analysis using Python and Cloud Tools. You learn how to perform document similarity, visualize word clouds and use Amazon AI Tools. The techniques covered include: * Google Colab * Spacy * AWS Quicksite * AWS Comprehend * AWS Rekognition * NLTK * WordCloud * Pandas * Plotly * Github Finally, the course analyzes Hemingway books using popular off the shelf Python libraries. Follow along with the Github Resource: https://github.com/noahgift/exploratory-data-analysis

Abstract: Learn to use the AWS (Amazon Web Services) platfrom to perform Computer Vision with the Python Language. This video course takes you from zero and introduces you to using the AWS Rekognition Console, AWS Cloud Shell and AWS Cloud9 environment to build computer vision solutions. Topics include: * Using AWS Rekognition to do Celebrity Recognition, Text Detection, PPE Detection and Image Labeling * Setting up AWS Cloud Shell to use the AWS SDK * Doing S3 copies with the AWS command-line SDK * Setting up AWS Cloud9 for development * Configuring bashrc file for use with Python * Using IPython with the AWS Boto3 SDK * Using Python Click to create command-line tools with colorized output * Using Github Actions to test and lint a computer vision project

Abstract: How are you generating revenue in your business or career. This lesson talks about consulting, salary and MRR including investing. Topics include: * Consulting * Salary * Investments * Autonomy vs Dependency * MRR (Monthly Recurring Revenue)

Abstract: Learn all about distributed tracing in this 1 hour course. If you want to go beyond logging and monitoring, and trying to tell a story by connecting the dots, then distributed tracing is the way to go. Topics include: * Opentracing and the foundations of distributed tracing libraries like Jaeger * Micro-service strategies and other microservice implementations that make distributed-tracing a perfect use case * Implement distributed tracing instrumentation in a Github project using docker compose with multiple Docker containers * Leverage the knowledge to use hosted services like Datadog for querying and debugging traces

Abstract: Learn to debug Python code quickly! Topics include: * Continuous Integration * Python Debugger: PDB * Debugging with print statements * Debugging with IPython * Using pylint and pytest to debug code

Abstract: Learn to AWS Sagemaker Autopilot from zero and deploy a model to production.

Abstract: Get started with Google Cloud Platform (GCP) and Cloud Functions in this one-hour video. Everything you need to know to get up and running quickly using serverless technology from GCP. Topics include: * An introduction to serverless technologies * Create a cloud function, install dependencies, and use different runtimes like Python 3.8 * Debug issues when a cloud function deployment fails * Use Google's Machine Learning offering to do live translations to any language * Enable authentication for your cloud function

Abstract: Learn how to use AWS in one Hour

Abstract: Learn to do GPU programming in Python in Five Minutes

Abstract: Get started with Docker and building powerful containers in this one-hour video. From the basics of containers, and its differences with virtual machines, to interactive commands and containerization of applications. Everything you need to know to get up and running quickly to use containers and grasp docker concepts. Topics include: * An introduction to containers and their differences with Virtual Machines * Start, stop, and manage containers. * Map container ports to local ports, mount volumes, and other startup flags for container images. * Get access to running containers to interactively debug a service like Nnginx. * Build a Python application with a Dockerfile, and deploy it running the latest Python version.

Abstract: Learn to do Data Science with Python, Pandas and Colab Notebook in one hour! This video lesson takes you through a Covid-19 Dataset from the NyTimes and shows you how to explore it. The libraries involved include: Pandas, Colab, Plotly, sklearn, numpy and matplotlib. A suggested structure for Data Science projects is included: Ingest, EDA, Modeling and Conclusion. Finally, the course wraps up with how to integrate Cloud based business analytics including the following tools. AWS Cloud9, IPython, AWS Rekognition, AWS Translate and AWS Comprehend. These solutions are explored with both boto3 and the AWS Console. Follow along with the Github Resource: https://github.com/paiml/minimal-python/blob/master/Chapter7_data_science.ipynb

Abstract: Get started with security vulnerability scanning and integrating that with Github, Github Actions and automated security checks in pull requests. Learn how to scan reported vulnerabilities in projects and Docker containers, so that you can publish images to Docker hub or merge pull requests while knowing that changes in dependencies are secure. Topics include: * Install and run locally a security vulnerability scanner * Catalog a project with an SBOM (Software Bill Of Materials) so that the scanner can do vulnerability matching. * Setup a Github Action to automatically scan vulnerabilities in a project and optionally fail a build to prevent a merge. * Scan a Docker container image that is built locally against the latest vulnerabilities, based on any CVE reported publicly

Abstract: Distribute the load of Jenkins builds with a remote Docker instance or Kubernetes server in this 1-hour long tutorial Topics include: * Configure a remote Docker instance to interact with the master Jenkins server * Modify an existing job to use Docker to do builds using labels * Setup a remote kubernetes instance to connect to Jenkins with JNLP * Use the right container image to connect back to Jenkins as a remote container node

Abstract: Get started with MLOps and Github Actions to package a container with an ONNX model that does live inferencing with a Flask application. By using Azure ML, learn how to download the large ONNX model into the Github Action workflow, package it as a container and then push it to a container registry. For reference use the https://github.com/alfredodeza/flask-roberta repository Topics include: * Create a container that does live inferencing with Flask and the ONNX runtime * Package the model and verify it works locally * Setup a Github Action to authenticate to Azure ML and download a previously registered model * Build the new container as a Github Action, authenticate to Docker Hub or Github Packages * Push the new container to the Github registry or any other registry like Docker Hub

Abstract: Zero to One: Data Science to MLOps in One Hour. Learn to frame a problem, then convert it into a data science project and present it to stakeholders. Later, move that prediction system to producting using MLOps Topics include: * Big Tech Misinformation and what can be done about it using Data Science. * Doing MLOps with sklearn and Flask by creating Microservices * Using sklearn, pandas, plotly, matplotlib, KMeans clustering, ELI5, shap and other libraries * Putting code into production using the Python MLOps Cookbook found here: https://github.com/noahgift/data-story-telling

Abstract: "In this Adobe Photoshop Lightroom 4 training course, creative and technical expert Andy Anderson takes you through the features and functions of this comprehensive software for both the professional and amateur photographer. Designed for the beginner, you do not require any prior experience working with Adobe Lightroom to take advantage of this tutorial. You will begin by touring the Lightroom interface, and become familiar with the tools and features that are available to you. You will them move on to cover features such as basic and advanced catalog organization, tethering, manipulating your images, geo-coding images, working with modules such as Develop and the Book Module, and so much more. You will learn to create slide shows, print and publish your images, and even export them to use with other Adobe Suite products. By the conclusion of this video based training course on Adobe Photoshop Lightroom 4, you will have a clear understanding of the features and functions at your fingertips, and how to utilize them within the software. Working files are included to let you work alongside the author as he proceed through this software video tutorial."--Resource description page.

Abstract: Get started with Vim in this one-hour video. Everything you need to know to get up and running quickly. Topics include: * Opening, saving, and quiting files * Basic movements and operations, like copying and deleting * Updating the .vimrc configuration file for customization * Installing plugins and further customization

Abstract: AWS Solutions Architect Certification In ONE HOUR!

Abstract: Get started building powerful Command-line Tools with Python. From a single file with no dependencies to packaging and publishing your tool on the Python Package Index. Everything you need to know to get up and running quickly to create Python command-line tools. Topics include: * An introduction to Python scripts and Python packaging * Declare dependencies and package your script for installing and sharing. * Use argparse or upgrade to a more powerful framework like Click * Add flags, options and arguments to fine-tune and control your command-line tool

Abstract: Get started with Machine Learning and Auto ML using Azure ML Studio easily building powerful models and deploy them in a scalable environment. Everything you need to know to get up and running quickly in Machine Learning using Azure, from datasets to containerized deployments and data validation. Topics include: * An introduction to Azure ML Studio and AutoML * Import datasets and version them within Azure - even from remote locations like Github * Create compute clusters for training and live inferencing * Select models for deployment into Kubernetes or Docker Container instances * Practice MLOps, operationalizing a deployed model with logs and metrics via Application Insights * Consume a live endpoint with a deployed model over an HTTP API * Use the generated Swagger files to grasp the HTTP endpoints

Abstract: Python Devops in TWO HOURS!

Abstract: Get started with Jenkins, Jenkins Pipelines, and Github integration in this introductory video to the most widely used CI/CD platform in the world: Jenkins. Learn how to setup an example repository from Github into Jenkins using the same techniques you would need to scale a massive CI CD production environment. Topics include: * Install and configure Jenkins including plugins like Blue Ocean that enables pipelines * Create a Personal Access Token (PAT) in Github to connect a repository to Jenkins * Setup a trigger to run automated tests for the Github repository using a Jenkinsfile * Add a remote node or slave to the Jenkins master instance via SSH to quickly scale up operations * Validate that the project builds and deploys correctly

Abstract: In this video you walk through the foundational concepts of Machine Learning.

Abstract: Learn to use containers to build Microservices on the AWS platform. In this video you walk through building a Flask Microservice using the following AWS tools: * AWS Cloud9 * AWS ECR (Elastic Container Registery) * AWS ECS (AWS Container Service) * AWS Fargate (Container as a Service) Finally, the course builds and deploys a Fargate container that was provisioned to ECR. Follow along with the Github Resource: https://github.com/noahgift/eks-fargate-tutorial

Abstract: Zero to One: AWS Lambda with SAM and Python in One Hour. Learn to use AWS Cloud9 to develop serverless applications with Python and SAM (Serverless Application Model) Topics include: * Building a Lambda inside of Cloud9 * Deploying a containerized service to Amazon ECR and AWS Lambda * Invoking API Gateway based AWS Lambda services using sam invoke and AWS Cloud9

Abstract: Enhance testing Python projects by adding Tox, a testing management tool that can easily create test matrices. In this video course, learn how to use different functional test strategies and expand basic unit testing by combining different software versions. Topics include: * Use Pytest for fast verification of unit tests * Detect missing dependencies that can get packaged and released even when tests are passing * Build a test matrix by adding factors and combinatorial versions by leveraging Tox to avoid boilerplate configuration * Use different Python versions to test the same code

Abstract: Python exceptions are exceptional at helping your program take decisions. It is natural to feel the urge to catch them all and ignore them. But powerful programs can be created by learning how to leverage them in order to make robust scripts and take your coding skills to the next level. In this video, I cover several techniques that will help you improve your exception handling. Topics include: * Create a script that uses exception poorly, and then improve it * Slowly clean up broad catching exceptions to improve the script * Learn how to produce better errors from exceptions * Leverage other tools like logging to produce meaningful errors and tracebacks while keeping messages clean Follow along the repository to continue using more examples: https://github.com/alfredodeza/exceptions/

Abstract: Sometimes scraping is the only way to extract meaningful data when there are no options like an accessible API. Parsing raw HTML can be intimidating and full of failures if you aren't used to existing tooling that can help you parse faster and more efficiently. In this video, learn all the basics including some advanced techniques to parse HTML and extract data with the Scrapy library in Python. k Topics include: * Install, configure, and create a new project with Scrapy, a powerful scraping library written in Python * See what is required to start parsing a website, including looking at raw HTML, tags, and CSS. * Identify data to create a dataset or datasets to perform data science analysis later * Capture parsed data and save it in different formats locally * Ultra fast scraping techniques by using the filesystem directly A few resources that are helpful if you are trying to do scraping, some of them covered in the course: * Scrapy Library * Scrapy Getting started tutorial

Abstract: The Go programming language is becoming more popular these days with cloud-native applications and the Kubernetes ecosystem. If you are coming from Python, you will find yourself surprised to see similar patterns, while at the same time see some things that are missing or plain impossible with Go. In this course, I will introduce you to some of the basics of Golang from a Python perspective, so that you can reduce the friction trying to learn it. Topics include: * Packages, imports and variable definitions * From lists to arrays and slices * From Python dictionaries to Go maps * Looping on data structures, retrieving and adding values or items * Error handling, and the surprising fact that there aren't any tracebacks or exceptions in Go A few resources that are helpful if you are trying to learn Go, some of them covered in the course: * Visual Studio Code for Go * The Go playground * An (interactive) tour of Go

Abstract: Dive into performance tuning by learning how data is structured and accessed in SQL Server. Learn from this video how to use execution plans, IO metrics, and query timing to identify problematic queries and trace latency directly to missing or incorrect indexes. Also learn about cardinality and how it affects execution plans and overall query performance. Understanding how indexes and statistics work provides a solid foundation for writing better queries and architecting more effective database objects. The knowledge from this video helps you to dive further into procedural TSQL and identify why a stored procedure or ad-hoc query can perform unexpectedly badly. This video examines such cases through a discussion of the causes of poor performance in TSQL procedures along with solutions such as parameter sniffing. In addition, the video demonstrates how local variables perform differently from parameters and how plan reuse can benefit performance. When plan reuse harms performance, the correct solutions will be presented, allowing you to permanently solve a performance challenge without the use of hacks or temporary fixes. What You Will Learn Create effective table indexes with confidence Identify queries where poor indexing is the cause of latency Display and use statistical metrics to troubleshoot performance challenges Optimize and speed up queries that make poor use of indexes Find and resolve parameter sniffing problems in procedural TSQL Identify when ad-hoc TSQL or local variables can negatively affect performance Understand when plan reuse can inadvertently harm performance Who This Video Is For Database administrators, developers, and architects who need to write fast and efficient database queries. For database administrators who are asked to troubleshoot slow queries to make them faster. For anyone working against SQL Server who relies upon highly performant queries to perform important tasks.

Abstract: In this video course, you will learn the basic principles of neural networks that are used to build models. You'll start by seeing machine learning, neurons, activations, activation functions, weights, and how everything works under the hood. Next, you'll cover the basics of the learning loop including how backpropagation and gradient descent work. Further, you will learn about convolutions, how they are inspired by the animal visual cortex, and how we use them in neural networks. One of the focuses of the course is image classification and detecting common objects in images. This has many uses in your day-to-day projects. We will be using the PyTorch open-source neural network library here. The course will also cover current state-of-the-art neural network models and show how to use them even on smaller hardware. The video concludes by showing some common tricks with hyperparameter settings and regularization techniques, and how to use neural networks in production environments. What You Will Learn Discover the basics of neural networks and how they function Work with convolutional neural networks Use CNNs in your day-to-day work for image classification and other tasks Who This Video Is For Data scientists and machine learning and deep learning engineers.

Abstract: Sneak Peek The Sneak Peek program provides early access to Pearson video products and is exclusively available to Safari subscribers. Content for titles in this program is made available throughout the development cycle, so products may not be complete, edited, or finalized, including video post-production editing. 16+ Hours of Video Instruction Parallel Functional Programming in Java LiveLessons describes by example how to apply Java functional programming features and frameworks to alleviate the complexity of developing software that can run efficiently and scalably on multi-core and distributed-core processors. In this course, learn how to develop programs using powerful object-oriented and functional programming language features and frameworks supported by Java. This course first provides an introduction to Java's foundational functional programming features, including lambda expressions, method references, and functional interfaces. These core features provide the foundation for the next topic in this course: the Java's Streams framework, which supports functional-style sequential and parallel operations on streams of elements, such as map-reduce transformations on Java collections. This course also shows by example how to develop efficient reactive programs that run scalably on multi-core processors using powerful object-oriented and functional programming language features and parallelism frameworks supported by Java. This portion of the course describes how Java leverages its functional programming features to create the completable futures framework. This framework defines a powerful reactive programming model that allows programmers to run multiple asynchronous operations concurrently in one or more pools of threads and process their results asynchronously with respect to other operations in a program. Skill Level Intermediate Learn How To Develop efficient parallel and reactive programs using powerful modern Java object-oriented and functional programming language features and frameworks Recognize the inherent and accidental complexities involved with developing parallel and reactive software for modern Java clients and servers Understand how common software patterns and modern Java parallel and reactive programming mechanisms can and cannot help to alleviate this complexity Know where to find additional sources of information on how to successfully develop robust parallel and reactive programs in modern Java Who Should Take This C...

Abstract: 27+ Hours of Video Instruction CCNP and CCIE Data Center Core DCCOR 350-601 Complete Video Course focuses on implementing and configuring Cisco Identity Services Engine for preparation for the DCCOR 350-601 certification, and providing the necessary skills for real-world deployment scenarios. Overview CCNP and CCIE Data Center Core DCCOR 350-601 Complete Video Course focuses on a blend of the real-world experience and best practices mixed with the requirements for the CCNP and CCIE Data Center Core DCCOR 350-601 exam. The goal of the course is to not only cover the objectives for the CCNP and CCIE Data Center Core exam, but also provide a solid learning resource for mastering key concepts regarding planning and delivering a Cisco Data Center solution. CCNP and CCIE Data Center Core DCCOR 350-601 Complete Video Course is a unique and a complete video course that provides solid understanding of Core Data Center technologies as well as CCNP Data Center Core exam. This complete video course guides the viewer from an Introduction to the Data Center technologies such as Layer2 and Layer3 features, Overlay technologies such as OTV and VXLAN, Application Data Center Infrastructure, Compute with network and Storage management, Hyperflex, Security and Programmability and Automation. The key topics covered in this course will enable the viewers to understand and implement the key data center technologies covering network, Software Defined Data Center using Cisco ACI, Storage and Compute and finally automating the services in Data Center environment. The topics covered in the CCNP Data Center Core Technologies are the foundational topics for designing and implementing a Next Generation Data Center using Cisco hardware and Software. Cisco Nexus OS (NX-OS) is a next generation modular software, primarily targeting Data Center networking, with the motivation to provide the key features of virtualization, high availability and upgradeability on Nexus line of products. The NX-OS software is used across all Nexus data center products which can run in standalone as well as ACI mode and as SAN-OS. This complete video course is for candidates who can install, configure, and manage Cisco Nexus switches, Cisco MDS switches; implement and deploy automation of Cisco Application Centric Infrastructure (ACI), implement compute using Cisco Unified Computing System (UCS). This complete video course not only helps building the foundation for the CCNP Data Center exam bu...

Abstract: This step-by-step video will show you how to leverage the power of the Creative Cloud Libraries panel and how it can streamline your work as a freelancer or as a member of a larger team. You will look at Adobe desktop apps that have the panel or access to the panel. During this discussion you'll briefly see what each can or cannot import and export with the CC Libraries panel. This video focuses on importing assets with Bridge and the Creative Cloud Console; collaborating and sharing your CC libraries; and touches on Animate, Dreamweaver, After Effects, Premiere Pro, XD, Dimension, and Fresco. While the Creative Cloud Libraries panel and console have been available in several versions of Adobe, their look and arrangement have changed over time. Adobe beginners or those who have not used the panel will discover how useful it is and save time when working between several Adobe programs to complete complex layout projects. What You Will Learn Use Bridge and Creative Cloud Console to import assets such as animations, 3D items, videos, and templates How to collaborate with a team through the CC libraries Access graphics from Adobe Stock How to integrate your work with other Adobe software for web projects, such as Animate, Dreamweaver, and Premiere Pro Who This Video Is For Students, graphic designers, and corporate administrators who need to create documents for events. This video is a beginner to intermediate level, and will be most helpful to viewers with some basic experience in Photoshop, Illustrator, and InDesign.

Abstract: Learn the architecture and implementation of Microsoft's latest SQL Server capability - Big Data Clusters. Combine SQL Server for data, PolyBase for data virtualization, Data Pools for scale-out data processing, and Spark with HDFS for scalable non-relational data processing and analysis. You'll begin this video with a quick overview of the big data space, along with an easy-to-understand introduction to containers, Kubernetes, Spark, and HDFS. You'll put those pieces together by planning and deploying your own cluster. Then it's on to operationalizing the cluster through problem-solving with Transact-SQL, PolyBase, data processing at scale, and working with Spark and HDFS. What You Will Learn Understand big data technologies such as Spark and HDFS Deploy a Big Data Cluster on a Kubernetes environment in Azure Implement PolyBase queries to bring in data from external sources Run Transact-SQL statements and process relational data at scale Execute Spark jobs and machine learning from within SQL Server 2019 Implement basic security protocols to protect your data from theft Who This Video Is For Database professionals who are curious about SQL Server 2019's flagship feature. For those who want to get started in querying and analyzing massive amounts of data using Spark and HDFS clusters while taking advantage of their SQL Server investment.

Abstract: Get to grips with Java design patterns and write robust and extensible software About This Video Understand interfaces, composition, inheritance, and polymorphism Get up and running with the concepts behind design patterns Learn the different design patterns with the help of real-world examples, code, and slides In Detail If you are an intermediate to advanced Java developer or a developer in any other OOP language and are looking to learn Java design patterns, then this course is for you. It is also tailored for anyone who has working knowledge of Java or OOP knowledge and is looking to delve into the core software development principles - design patterns. This course will help you understand Java design patterns effectively so you can apply what you've learned to your projects. Design patterns are the common denominator you need to learn in order to build effective software and systems that work efficiently. In this course, you will explore the different design patterns, right from the Observer Design Pattern and the Singleton Design Pattern through to the Adapter Design Pattern and Façade Design Pattern. As you progress, you'll understand how to apply these patterns to real-world projects. In addition to this, you'll get to grips with solving different software architecture problems using the patterns. By the end of this book, you will be well-versed with Java design patterns and be able to write efficient and extensible software.

Abstract: 9 Hours of Video Instruction The Exam AZ-104 Microsoft Azure Administrator (Video) offers full coverage of the MS AZ-104 exam so you can learn everything you need to know to pass the exam. Coverage includes cloud concepts, core Azure Services, Azure pricing and support, and the fundamentals of cloud security, privacy, compliance, and trust, with the goal of passing the AZ-104 Exam. Description The Exam AZ-104 Microsoft Azure Administrator (Video) offers 9 full hours of video training on all core concepts in the AZ-104 exam so you can fully understand cloud concepts, core Azure Services, Azure pricing and support, and the fundamentals of cloud security, privacy, compliance, and trust. It will prepare Azure Administrators to implement, monitor, and maintain Microsoft Azure solutions, including major services related to compute, storage, network, and security. With 9 hours of hands-on demonstrations, it will provide the knowledge necessary to pass the exam and become Microsoft Certified: Microsoft Azure Administrator. With years of IT experience, numerous publications under his belt, and a wealth of expertise teaching in the field, Michael Shannon is uniquely qualified to prepare students for the Microsoft Azure Administrator AZ-104 exam. Topics include: Module 1: Manage Azure subscriptions and resources Module 2: Implement and manage storage Module 3: Deploy and manage virtual machines (VMs) Module 4: Configure and manage virtual networks Module 5: Manage identities About the Instructor Michael J. Shannon began his IT career when he transitioned from recording studio engineer to network technician for a major telecommunications company in the early 1990s. He soon began to focus on security and was one of the first 10 people to attain the HIPAA Certified Security Specialist. Throughout his 30 years in IT, he has worked as an employee, contractor, and consultant for several companies including Platinum Technologies, Fujitsu, IBM, State Farm, MindSharp, and Pearson, among others. Mr. Shannon has authored several books, training manuals, published articles, and CBT modules over the years as well. He is the senior technical instructor for Skillsoft Corporation, specializing in all things cloud and security. Skill Level Intermediate/Advanced Learn How To Manage Azure subscriptions and resources Implement and manage storage Deploy and manage virtual machines (VMs) Configure and manage virtual networks Manage identities Who Should Take...

Abstract: Use machine learning today without a machine learning background About This Video Quickly get up and running using state-of-the-art machine learning algorithms in your .Net applications Implement machine learning algorithms using real-world data sets, without first learning math Leverage state-of-the-art (TensorFlow, ONNX) models, pre-trained by the tech giants, in your own .Net code In Detail ML.NET enables developers utilize their .NET skills to easily integrate machine learning into virtually any .NET application. This course will teach you how to implement machine learning and build models using Microsoft's new Machine Learning library, ML.NET. You will learn how to leverage the library effectively to build and integrate machine learning into your .NET applications. By taking this course, you will learn how to implement various machine learning tasks and algorithms using the ML.NET library, and use the Model Builder and CLI to build custom models using AutoML. You will load and prepare data to train and evaluate a model; make predictions with a trained model; and, crucially, retrain it. You will cover image classification, sentiment analysis, recommendation engines, and more! You'll also work through techniques to improve model performance and accuracy, and extend ML.NET by leveraging pre-trained TensorFlow models using transfer learning in your ML.NET application and some advanced techniques. By the end of the course, even if you previously lacked existing machine learning knowledge, you will be confident enough to perform machine learning tasks and build custom ML models using the ML.NET library.

Abstract: Learn how to apply the cloud, no-code/low code and data science to build cloud based business analytics solutions. This is the missing semester of an MBA that gives you just what you need to build technical solutions in the analytics space.

Abstract: 9+ Hours of Video Instruction Certified Kubernetes Application Developer (CKAD) Complete Video Course provides more than 9 hours of video instruction for IT professionals preparing to take the CKAD exam, which requires an in-depth knowledge of how to develop, create, manage, store, and troubleshoot Kubernetes applications. Certified Kubernetes Application Developer (CKAD) Complete Video Course provides more than 9 hours of video instruction for IT professionals,Äìincluding IT Administrators, DevOps Engineers, Software Developers, IT Architects, and Hybrid Cloud Administrators,Äìpreparing to take the CKAD exam, which requires an in-depth knowledge of how to develop, create, manage, store, and troubleshoot Kubernetes applications. The course includes labs, demonstrations, and lightboard explanations by best-selling author and presenter Sander van Vugt. This course first provides a full introduction to containers and Kubernetes; it then moves through the process of creating, managing, and storing applications. The title provides labs for working with the API using curl, as well as using NameSpace and managing pods. You will also learn how to manage deployments, services, ingress, and setting up storage; and you will get a full walkthrough of key troubleshooting scenarios. The course ends with a sample exam so you can practice before taking the real test. Topics include: Module 1: Getting Started Module 2: Kubernetes Essentials Module 3: Building and Exposing Scalable Applications Module 4: Sample Exams About the Instructor Sander van Vugt has been teaching Linux classes since 1995 and has written more than 60 books about different Linux-related topics, including the best-selling RHCSA-RHCE 7 Cert Guide . Sander is also the author of more than 25 video courses, including Kubernetes Fundamentals . He teaches courses for customers around the world, and is also a regular speaker on major conferences related to open source software. Sander is also the founder of the Living Open Source Foundation, a non-profit organization that teaches open source to talent in different African countries. Skill Level Beginner/Intermediate Learn How To Best prepare to pass the Certified Kubernetes Application Developer (CKAD) Exam Run applications in containers Develop, create, manage, store, and troubleshoot Kubernetes applications Manage API options Manage pods Manage deployment and networking Manage ingress and storage Manage ConfigMaps and Secrets Troubleshoot Kuber...

Abstract: 4.5+ Hours of Video Instruction Description The Cloud Technology and Certifications Jump Start video course covers critical information about cloud technologies, including the "Big Four" public cloud vendors, and their offerings. This course also covers such practical guidance as how to plan a migration to the cloud and the tools available for migration. Overview The goal of Cloud Technology and Certifications Jump Start Livelessons clarifies why cloud technologies are revolutionizing and dominating the IT industry and provides the basics you need to start your cloud career. By providing many real-world examples to illustrate the sea changes taking place, and walking through the various options available, this course explains the benefits of cloud computing. This video series also provides very practical information about each of the Big Four public cloud vendors. This provides the learner with an understanding of the offerings of each of these major players in the industry and also permits a student to see the trends that are occurring in the space as they compare the offerings from the dominant players. The course starts with the evolution of cloud computing, the types of deployments, and the steps to deploy technologies today. The course also covers such important topics as cloud security, cloud migrations, and the architectural design changes that make your solutions much more "cloud-ready". Lastly, the course provides an overview of the various certifications offered by the Big Four cloud vendors. Topics include: The Evolution of Cloud Computing The Big Four Public Cloud Vendors Adopting Cloud Technologies Cloud Migrations Cloud Certifications About the Instructor Anthony Sequeira, CCIE No. 15626, is a seasoned trainer and author regarding various levels and tracks of Cisco, Microsoft, and AWS certifications. Anthony formally began his career in the information technology industry in 1994 with IBM in Tampa, Florida. He quickly formed his own computer consultancy, Computer Solutions, and then discovered his true passion,Äîteaching and writing about information technologies. Anthony joined Mastering Computers in 1996 and lectured to massive audiences around the world about the latest in computer technologies. Mastering Computers became the revolutionary online training company KnowledgeNet, and Anthony trained there for many years. Anthony is currently pursuing his second CCIE in the area of Cisco Data Center! Anthony is currently a freela...

Abstract: Welcome to Skylines Academy, where you will get a detailed introduction into Azure DevOps! This course is for you in you want to: • Get the best overview of Azure DevOps from one of the IT industry's leading technologists • Develop a skillset in Azure DevOps, which is becoming more and more sought after as organizations continue to automate processes for faster results • Take the AZ-400 certification and are looking for a place to start Course Description: This course is based on a major section of the AZ-400 Certification from Microsoft: Designing and Implementing Microsoft DevOps Solutions, and includes important fundamental and in-depth lectures and demonstrations on how to start with Azure DevOps. As a foundation to learning all-things Azure DevOps, Author and Instructor Shannon Kuehn will lead you through this course and teach you the following: 1. The importance of source control and how to effectively manage and implement it: o Source Control 101 o Git o Source Control Systems o Authentication to Git Repos o Git Repo Organization 2. An overview of Azure DevOps to get you up-to-speed with the service: o Setting up Azure DevOps with Demo Generator o Azure Repos o In-depth demos on Git Credential Manager, Version Control with Azure Repos, Importing/Cloning/Forking/Branching, and Pull Requests o Azure Pipelines o Jenkins and Azure Pipelines Integration 3. Analyze and Integrate Multi-Stage Files, including: o Deploying Multi-Container Application to Azure Kubernetes Service (AKS) 4. Understanding Parallel Jobs, Build Agents, and Private Agents 5. Implementing Security for Software Configuration: o Secrets and Certificates o Demonstration on Azure Key Vault and Azure Pipelines 6. Mobile DevOps & Visual Studio App Center o Mobile Target Devices and Distribution Groups o Public/Private Distribution Groups o Target UI Test Device Sets o Tester Devices for Deployment Using the Skylines Academy approach, lectures will educate you on the fundamental terms and principles of Azure DevOps, and demos will enable you with a hands-on experience using scenarios to empower you in the real world. The Skylines Academy AZ-400 Course Series This AZ-400 Azure DevOps Development Processes & Source Control is part of a series of courses which will cover the entirety of the AZ-400 Skills Measured document by Microsoft. This course is also an excellent stand-alone knowledge option for those looking to amplify their skills in Source Control without studying for the...

Abstract: This three-part series of half-day online events gives attendees an overarching perspective of software development from which to make decisions that strengthen and grow companies and industries, a deep knowledge of key open source technologies to make it happen, and a community in which both they and their companies can thrive. In Part 1, Live Coding-Go, Rust, and Python, we wanted to get deeper into actual coding, and one way to do that was to outlaw slides. That's right, these sessions all incorporate live-coding. These four sessions from Ellen Körbes, John Walicki, Nathan Stocks, and Reuven Lerner will walk you through coding best practices and new ways of getting the most out of languages like Python, Go, and Rust. This event is sponsored by IBM, and features spotlights on Kode With Klossy and the Eclipse Foundation. About the presenters: Rachel Roumeliotis is vice president of content strategy at O'Reilly, where she leads an editorial team that covers a wide variety of programming topics ranging from full stack to open source in the enterprise to emerging programming languages. She's been a programming chair for the O'Reilly OSCON, Fluent, Strata, Software Architecture, and Security Conferences. She's currently the programming chair for the OSCON and Strata Data & AI Superstream Series on O'Reilly online learning. She's been working in technical publishing for 10 years, acquiring content in many areas including mobile programming, UX, computer security, and AI. Kelsey Hightower has worn every hat possible throughout his career in tech and enjoys leadership roles focused on making things happen and shipping software. Kelsey is a strong open source advocate focused on building simple tools that make people smile. When he isn't slinging Go code, you can catch him giving technical workshops covering everything from programming to system administration. Ellen Körbes ran DevRel at both Tilt and Garden-two of the very few companies 100% focused on the development experience side of Kubernetes. They got their start building Kubernetes CLI tooling under SIG-CLI. They've since spoken about Go and Kubernetes at many world-famous events. Tara Tran is the manager of recruitment and instruction, and Mehreen Butt is an instructor at Kode With Klossy. John Walicki is the CTO for edge/IoT advocacy in the Developer Ecosystem Group within the IBM Cognitive Applications Group, where he helps developers create custom IoT and embedded Linux solutions for thei...

Abstract: This is a one hour introduction to Python with code samples you can execute at home at the same time. Code can be executed here: https://github.com/noahgift/functional_intro_to_python/blob/master/Public_Master_SafariOnline_Day1_Part1.ipynb Subscribe to YouTube channel: https://lnkd.in/gUpprB2 You can find more content by Noah Gift at https://noahgift.com. #pragmaticai #python #tutorial

Abstract: Get started with MLOPS. Topics include Flask Machine Learning on AWS, what MLOPS is, Azure DevOps Pipelines for MLOps and dealing with edge cases in exporting models.

Abstract: Many people wrongly believe that to program properly in Python, it is necessary to master all of its many moving parts. But the single most important part of modern Python programming - the part you should learn first - is the function. What can you do with a function? Build command-line tools, web applications, GPU programming, serverless, distributed computing, and machine learning. In the cloud and machine learning era, the function rules. In this course, you'll begin your Python journey through learning about this critically important subset of the Python language. You'll master the use of functions much more quickly by not getting bogged down with all the rest.

Abstract: 8+ Hours of Video Instruction It can be difficult for developers familiar with Java and other languages to make the transition to modern JavaScript. If you simply want to be productive with JavaScript as it exists today, then you don't want to relive history with books or courses that teach older JavaScript versions, or that assume familiarity with those older versions and focus on recently introduced features. This course assumes that you are a competent programmer who understands branches and loops, functions, data structures, and the basics of object-oriented programming. You will get up to speed with modern JavaScript in the shortest possible time. Description Modern JavaScript for the Impatient LiveLessons focuses on how to be productive with JavaScript as it exists today. After reviewing the fundamentals of values, variables, and control flow, the video thoroughly covers functions, objects, and classes. The standard library and the most commonly used tools are also covered, as well as key topics related to asynchronous programming, internationalization, and modules. Related Content This training pairs with Cay Horstmann's book Modern JavaScript for the Impatient (9780136502142) About the Instructor Cay S. Horstmann is a professor of computer science at San Jose State University and a Java Champion. He is also the author of Core Java, Volume II,ÄîFundamentals, Eleventh Edition (2019); Core Java, Volume I,ÄîFundamentals, Eleventh Edition (2018); Core Java SE 9 for the Impatient, Second Edition (2018); Java SE 8 for the Really Impatient (2014); and Scala for the Impatie nt (2012). He has written more than a dozen other books for professional programmers and computer science students. What You Will Learn After starting with the basics-JavaScript values, variables, and types, and a quick overview of expressions and the various type of flow control statements-Horstmann shows viewers how to implement functions that consume and produce other functions and how to use closures to implement a form of classes before moving on to more advanced topics including: Object-oriented programming with modern JavaScript (classes and inheritance and how these are implemented with prototypes) The standard library (numbers and dates, strings and regular expressions, as well as arrays and collections.) Metaprogramming, iterators, and generators (a powerful mechanism to bridge between linear and event-driven control flow) How to use proxies to inter...

Abstract: ​This step-by-step video will show you how to leverage the power of the Creative Cloud Libraries panel in Illustrator and InDesign. With this information, you'll be able to streamline your work as a freelance or as a member of a larger team. We'll break down the features and tools of the Creative Cloud Libraries panel. While the Creative Cloud Libraries panel and console have been available in several versions of Adobe, their look and arrangement have changed over time. Adobe beginners or those who have not used the panel will discover how useful it is and save time when working between Adobe Illustrator and InDesign to complete complex layout projects. What You Will Learn Understand what the CC Libraries panel is and how it's used Export and import assets such as 3D items, character styles, patterns, and videos Discover what can and cannot be imported via the CC Libraries panel Who This Video Is For Students, graphic designers, and corporate administrators who need to create documents for events. This video is for intermediate level users with some experience in basic layout in Photoshop, Illustrator, and InDesign.

Abstract: Build powerful, reactive, great-looking UI web experiences with this front-end compiler and its framework. About This Video Build modern, real-life, responsive web applications with Svelte by taking advantage of its small footprint (thanks to its compilation step) Develop complex web applications with Sapper, the framework based on Svelte that provides useful and powerful features thus, making developing Svelte apps even easier Learn a web technology (whose popularity is on the rise thanks to its great developer experience and powerful features) to improve your Svelte skills In Detail This course will take you through three core projects to help you build effective, reactive, and attractive apps with Svelte, demonstrating its intrinsic benefits, including less code and impressive reactivity/state management along the way. Our first project, a vCard generator app, will demonstrate the modularity and reactivity web applications you can develop with Svelte. We will build reusable and dynamic components that we will later enhance with more advanced features. Sections on animation and transitions are included to make applications look as good as they perform! Our second project will be a fully functional Kanban board application, similar to Trello. This application will also have effective state management, by making use of stores and other key Svelte features. Our final application will be based on the previous Kanban board application but making use of Sapper, the official Svelte framework. However, we will build this application with Sapper, the official Svelte framework. We will learn how to create web apps with Sapper and master its most useful features, such as routing and prefetching. We will also provide an introduction to testing Sapper applications with Cypress, and we finish the course by deploying our application in two different ways: as a static page, and as an SEO-optimized server-side rendered (SSR) application.

Abstract: Sneak Peek The Sneak Peek program provides early access to Pearson video products and is exclusively available to Safari subscribers. Content for titles in this program is made available throughout the development cycle, so products may not be complete, edited, or finalized, including video post-production editing. C++20 Fundamentals LiveLessons with Paul Deitel is a code-oriented presentation of C++, one of the world,Äôs most versatile and powerful programming languages. C++ remains hugely popular for the development of systems software, embedded systems, operating systems, real-time systems, communications systems and other high performance computer applications. C++20 Fundamentals LiveLessons is comprehensive and covers all major versions of C++, including: C++11, C++17, and C++20. The code repository for this LiveLesson is kept at https://github.com/pdeitel/CPlusPlus20FundamentalsLiveLessons and will be kept up to date as lessons are added and as changes are made.

Abstract: Learn to build solutions using Python for DevOps. Topics include serverless, microservices, GCP, AWS, Azure, Continuous Integration and Continuous Delivery.

Abstract: Learn advanced testing techniques in Python, PyTest, AWS and more. Topics include: * Debugging Python * Using pdb * Using pylint * Using Github Actions for Matrix testing multiple versions of Python and Operating Systems * Using AWS specific features for testing including AWS Cloud9 AWS Code Guru and AWS Code Build * Testing Python Click Command Line Tools with PyTest

Abstract: Join #onemillion2021, where one million students learn Cloud, Data, and Python skills globally by 2021. This course takes a user on a journey to understand and then master the AWS Cloud. This material exists in many forms at top universities around the world. This material has adjusted to the unique properties of the O'Reilly platform. Many techniques will also prepare a student interested in Python, Data Science, Data Engineering, or Machine Learning to use the AWS cloud in those domains. Some of the hands-on demos include: How to build websites using: AWS S3, AWS Lambda, and AWS EC2 Instances How to use AWS Spot Instances and run machine learning workloads How to write simple Python functions and deploy them using AWS Lambda How to create AWS S3 buckets and synchronize data to them How to use AWS Cloud9 to develop software and interact with the AWS Cloud How to create a user account in AWS IAM How to manage billing and set up alerts to protect you from unexpected charges

Abstract: In much the same way that the open source paradigm of software development has become a standard model for building applications using code that's generated and evolved by developers from around the globe, InnerSource development is rapidly becoming the preferred methodology for building software products intended for use only within an organization. InnerSource applies the same principles that have made open source so successful, like code reuse and unleashing the combined talent and expertise of many developers to help build higher-quality solutions faster and more flexibly. Within the InnerSource framework, the Contributor role is one of the most central roles-to put it succinctly, without Contributors, there wouldn't be anything to receive or discuss. In this video course, you learn that there's far more to being a Contributor than simply dumping code in a branch or issue. You'll explore what it takes to become a Contributor in an InnerSource community, including adopting the mindset, habits, technical approaches, and other details of this role. You'll learn about the mechanics of being a Contributor-the nuts and bolts of developing solutions in this unique environment. You'll also examine the Contributor ethos, including the guest-in-home analogy, the indispensable set of principles to which a Contributor needs to adhere to successfully interact in an InnerSource development environment and contribute to the host teams work, foster good relationships, and be a happy InnerSource Contributor. What you'll learn-and how you can apply it What an InnerSource Contributor is and why the role is important How to become an InnerSource Contributor and adopt the mindsets and habits that lead to becoming one Understand the Contributor ethos and mindset of an InnerSource Contributor The mechanics and technical aspects of contribution to ensure success The benefits of being a Contributor: what's in it for me (the guest), the receiving team (the host), and our company? This video is for you because... You're a possible future Contributor to an InnerSource project and want to know what to expect You're a host team member looking to open your environment to outside contributors via InnerSourcing and you want to know what the expectations and benefits are of the Contributor role You're a product owner looking to support your TC or a (line) manager and want to know how the InnerSource approach is meant to work Prerequisites: We recommend that you first watch t...

Abstract: As the digital economy changes the rules of the game for enterprises, the role of software and IT architects is also transforming. Rather than focus on technical decisions alone, architects and senior technologists need to combine organizational and technical knowledge to effect change in their company's structure and processes. To accomplish that, they need to connect the IT engine room to the penthouse, where the business strategy is defined. In this guide, author Gregor Hohpe shares real-world advice and hard-learned lessons from actual IT transformations. His anecdotes help architects, senior developers, and other IT professionals prepare for a more complex but rewarding role in the enterprise. This book is ideal for: Software architects and senior developers looking to shape the company's technology direction or assist in an organizational transformation Enterprise architects and senior technologists searching for practical advice on how to navigate technical and organizational topics CTOs and senior technical architects who are devising an IT strategy that impacts the way the organization works IT managers who want to learn what's worked and what hasn't in large-scale transformation

Abstract: Protect yourself against data theft through unauthorized access to the physical database files and their copies that may be found in backup sets and transaction logs. Thwart unauthorized access to those files by making use of SQL Server's Transparent Data Encryption (TDE) feature to provide at-rest encryption of an entire database such that only authorized instances of SQL Server can read the data, log, and backup files. This video explains how the TDE feature works and shows how to implement at-rest encryption using best practices. It also covers independent backup encryption for an additional layer of protection. The video begins with an introduction to TDE and the pros and cons of its implementation. It talks about the use case for applying this type of encryption. The video then walks you through implementing TDE on a new database or existing database. Next, it will cover how to manage the movement of these encrypted databases. Finally, you'll cover independent backup encryption. What You Will Learn Recognize use cases for Transparent Data Encryption Encrypt your entire database, including log and backup files Preserve encryption keys and restore from encrypted backups Manage encryption through dynamic management objects Encrypt database backups independently of TDE Move a TDE encrypted database, including log files Who This Video Is For Database administrators who need to encrypt a database at rest to meet IT audit requirements, or for reasons of data privacy and confidentiality. For system architects who want to understand their options for securing their organization's confidential data.

Abstract: The future will not be like the past. We're at an inflection point where the decisions our societies make now can have an enormous impact on the course of the next few decades. Those of us in business have difficult choices to make. And those choices have to be made with wildly uncertain futures in mind. We can no longer base our strategies on the old baselines of predictable consumer demand, globalization, office life and business travel, and access to talent, credit, or venture funding. In this edition of Meet the Expert, Tim O'Reilly discusses what skills will be needed to plan for the new world and how scenario planning will help you develop a robust strategy that will hold up well against a range of possible outcomes. Learn how to better prepare for a post-COVID future as you explore the technologies that will be most important in the 21st century. Recorded on June 15, 2020. See the original event page for resources for further learning or watch recordings of past events . O'Reilly Meet the Expert explores emerging business and technology topics and ideas through a series of one-hour interactive events. You'll engage in a live conversation with experts, sharing your questions and ideas while hearing their unique perspectives, insights, fears, and predictions.

Abstract: Master Cisco's ACI and become an expert NOW! About This Video This course will help you get from zero to hero and master the policy-driven Data Center approach that ACI offers ACI involves a big learning curve and you'll learn to change your traditional network design mentality, which will be crucial to mastering ACI We will work with ACI APIC version 3.x. which provides the current SDN feature set you need to perform all data center functions and requirements In Detail Automation, objects, and policies are replacing traditional networks as we know them. North-to-South or East-to-West traffic flows-do you know the difference between the two? Don't worry if you don't: this course will remedy that! Traditional campus networks are static, and won't change much because they can't scale up. Data centers are not meant to be static. Today's Data Center architecture requirements are: scalability, geo-redundancy, security, multi-tenancy, and speed! Data center traffic flow should be highly available and predictable. As the demand for talented ACI engineers and architects is rapidly increasing, knowing the foundational aspects of SDN-based architectures and being able to implement and support them are crucial for your career development. This fast-paced course uses a whiteboard-based approach with hand written explanations. We start with an introduction to fabric data center designs, Spine and Leaf architectures, and ACI. We then start to implement them and deploy a fabric from the ground up. Then we build a multi-tenant environment. After completing this video training course, you will have gained a solid understanding of how to administer an Application Centric Infrastructure.

Abstract: This hands-on course teaches you to build reactive, scalable, and dynamic cross-platform apps using Ionic 4 and 5 About This Video Build performant, persistent, reactive, and scalable cross-platform apps using the Ionic 4 and 5 framework Develop apps that use a single codebase and work on mobile platforms Android, iOS, and also the web using native APIs and in-device storage Follow industry best practices and use MobX with Ionic (via device storage) to build a scalable architecture In Detail While Ionic is an easy and straightforward framework to learn, building Ionic apps can sometimes be hard. Designing its architecture and making sure that your application is high-performing, dynamic, and scalable are always tricky. In this course, you will develop a feature-rich Notes app in a step-by-step process using the Ionic framework. You will be using web components, persistent storage, and APIs to ensure your app is high-performing. You'll use the MobX reactive state management tool to make your apps scalable. You'll then use a SQLite database to persist data onto your device. With the Ionic Native Camera API, you'll add, save pictures to your notes then edit and save them, set reminders in your notes, and have your device notify you of events using Ionic Native local notifications. You will deploy your app across iOS and Android devices and also on the web. By the end of the course, you will have taken your Ionic 4 and 5 skills to the next level and will be equipped to build cross-platform hybrid mobile apps.

Abstract: This video introduces Cosmos DB and highlights the benefits that using Cosmos DB can bring to your applications and clients. Watching this video helps to increase your toolbox of knowledge around Azure and build your skills on this important cloud platform. Examples in the video are built in C#, the language from which Cosmos DB is most commonly used. A running example throughout the video demonstrates the basics of entering data, querying and updating data, deleting data, and working with the Cosmos DB change feed. What You Will Learn Understand Cosmos DB and when it should be used Become familiar with the different APIs that are available Create a new service in Azure in support of a Cosmos DB database Develop applications locally using C# and the Table API Create a database and add data to it Query, update, and delete data as needed React to events and streaming data with the change feed Who This Video Is For Developers with knowledge of C#, but who have not used Cosmos DB before and who would like to know more about it and the scenarios in which Cosmos DB is useful. For developers who have come from a relational database background and want to understand how Cosmos DB can be used differently from the relational databases to which they are accustomed.

Abstract: In late 2017, Slack's largest customers were plagued with relentless performance-related outages, due in part to the fact that public channels, private channels, and DMs were stored in completely distinct ways. Instead of shipping scrappy, short-term fixes, the company opted to address the root problem and completely refactor problematic functionality by consolidating any redundant database schemas. In this Spotlight on Data , Maude Lemaire explains how Slack succeeded by mapping out a precise plan that was careful to scope the effort to only its necessary components. Join in to learn real-world, successful techniques for modernizing your infrastructure from the ground up-live and in production. Recorded on November 18, 2019. See the original event page for resources for further learning or watch recordings of other past events . O'Reilly Spotlight explores emerging business and technology topics and ideas through a series of one-hour interactive events. In live conversations, participants share their questions and ideas while hearing the experts' unique perspectives, insights, fears, and predictions for the future. In every edition of Spotlight on Data , you'll learn about, discuss, and debate the tools, techniques, questions, and quandaries in the world of data. You'll discover how successful companies leverage data effectively and how you can follow their lead to transform your organization and prepare for the Next Economy.