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Il y a 4 modules dans ce cours
Throughout this course, you'll explore virtualization, containerization, and Kubernetes, mastering the very tools that power data engineering in the industry. Each week presents a new set of tools and platforms that are indispensable in data engineering. From mastering Docker and Kubernetes to exploring advanced topics such as AI-driven coding with GitHub Copilot, efficient container image management with Azure and Amazon Elastic Container Registries, and Site Reliability Engineering (SRE) practices, you'll go beyond the basics and acquire the expertise needed to thrive in the dynamic and data-driven landscape of advanced data engineering. Whether you're a current student looking to expand your skills or a working professional aiming to take your expertise to the next level, this course is tailored to equip you with the advanced knowledge and hands-on experience necessary for success.
In this module, you will learn about the fundamentals of virtualization, exploring its various aspects such as hardware utilization and scaling applications. You will start by understanding what virtualization is and delve into the concept of virtual machines. Through the introduction of Virtual Box and a hands-on demo, you will gain a practical understanding of how virtual machines work and their benefits. Additionally, you will explore container concepts, focusing on Docker as a key containerization tool. Through an introduction to Docker and its architecture, you will learn how to scale applications using containers, providing a comprehensive overview of virtualization and its practical applications. To apply your newfound knowledge, you will be assessed through a series of hands-on exercises involving the creation and management of virtual machines and containers, demonstrating your ability to effectively utilize virtualization technologies.
Inclus
8 vidéos9 lectures8 devoirs1 sujet de discussion
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8 vidéos•Total 26 minutes
Virtualization•3 minutes
Scaling Applications•2 minutes
Hardware Utilization•1 minute
Introduction to Virtual Machines•2 minutes
Virtual Box Demo•10 minutes
Container Concepts•2 minutes
Introduction to Docker •5 minutes
Docker Architecture •1 minute
9 lectures•Total 90 minutes
Welcome to Kubernetes for Data Engineering with Python!•10 minutes
Meet your Instructors: Noah Gift and Kennedy Behrman•10 minutes
Tools and Platforms•10 minutes
Report a problem with the course•10 minutes
What is Virtualization?•10 minutes
What is a Virtual Machine?•10 minutes
Introduction to Containers•10 minutes
Docker: The Container Platform•10 minutes
Spin up a local Docker container•10 minutes
8 devoirs•Total 240 minutes
Virtualization•30 minutes
Virtualization•30 minutes
Scaling Applications•30 minutes
Introduction to Virtual Machines•30 minutes
Virtual Box•30 minutes
Containers•30 minutes
Introduction to Docker•30 minutes
Docker Architecture•30 minutes
1 sujet de discussion•Total 10 minutes
Meet and Greet (optional)•10 minutes
Using Docker
Module 2•6 heures à terminer
Détails du module
In this module, you will learn how to effectively work with the Docker client, create volumes, and run databases in containers, gaining hands-on experience in managing containerized applications. You will also explore how to use the Docker command line for tasks such as building images and working with Dockerfiles, enabling you to package your software efficiently. You'll get a chance to study real-life Dockerfile examples and consult the Dockerfile reference for best practices. Furthermore, you will dive into orchestration with Docker Compose, learning how to manage multi-container applications using Compose. As an extension to this, you will be introduced to Airflow, a workflow management platform, and learn how to integrate it with Docker Compose for a seamless automation experience.
Inclus
9 vidéos6 lectures8 devoirs
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9 vidéos•Total 40 minutes
Docker Client•5 minutes
Creating a Volume•5 minutes
Running a Database in a Container•6 minutes
Building an Image•5 minutes
Dockerfiles•2 minutes
Dockerfile Examples•5 minutes
Orchestration with Docker Compose•3 minutes
Introduction to Airflow•4 minutes
Airflow Demonstration using Compose•5 minutes
6 lectures•Total 60 minutes
Use the Docker Command Line•10 minutes
Creating a Docker Image (Step-by-Step)•10 minutes
Getting Started with Docker Compose•10 minutes
Getting Started with Apache Airflow•10 minutes
Docker vs. Kubernetes: A Primer•10 minutes
Use Docker to Spin Up Airflow•10 minutes
8 devoirs•Total 240 minutes
Docker•30 minutes
Docker Client•30 minutes
Volumes•30 minutes
Running a Database in a Container•30 minutes
Building an Image•30 minutes
Dockerfiles•30 minutes
Compose•30 minutes
Airflow•30 minutes
Kubernetes: Container Orchestration in Action
Module 3•6 heures à terminer
Détails du module
In this module, you will embark on a comprehensive journey into Kubernetes, the cornerstone of modern container orchestration. You'll begin by grasping Kubernetes key concepts, cluster architecture, and service deployments. The advantages of cloud development environments, exemplified by GitHub Codespaces, will become more clear as you explore GitHub's ecosystem and harness AI-driven coding with GitHub Copilot and OpenAI Codewhisper. The module culminates in hands-on experience as you deploy Kubernetes using Minikube within GitHub Codespaces. Gain a solid foundation in Kubernetes essentials and the power of cloud-based development, setting the stage for successful containerized application management and collaborative coding in the modern era.
Inclus
14 vidéos7 lectures8 devoirs
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14 vidéos•Total 52 minutes
Kubernetes Key Concepts•2 minutes
Kubernetes Clusters•1 minute
Kubernetes Nodes•1 minute
Kubernetes Service Deployments•1 minute
Cloud Developer Workspace Advantage•4 minutes
Key Concepts in the GitHub Ecosystem•4 minutes
Using GitHub Templates•2 minutes
Using GitHub Codespaces•6 minutes
Using OpenAI Codewhisper•1 minute
Fine-Tuning a Model with Hugging Face•3 minutes
Using GitHub Copilot•8 minutes
GitHub Actions•4 minutes
Running Minikube in GitHub Codespaces•7 minutes
Deploying a Service with Minikube•7 minutes
7 lectures•Total 70 minutes
What is Kubernetes?•10 minutes
Virtualization, Containerization, and Elasticity•10 minutes
Fine-Tune a Pretrained Model•10 minutes
Getting Started with GitHub Copilot•10 minutes
Hello Minikube•10 minutes
Minikube + Kubernetes: A Recap•10 minutes
Deploying FastAPI to AWS with ECR and App Runner•10 minutes
8 devoirs•Total 240 minutes
Kubernetes, GitHub, and Minikube•30 minutes
Kubernetes Key Concepts•30 minutes
Kubernetes Clusters•30 minutes
Kubernetes Nodes•30 minutes
Kubernetes Service Deployments•30 minutes
Key Concepts in the GitHub Ecosystem•30 minutes
Running Minikube in GitHub Codespaces•30 minutes
Deploying a Service with Minikube•30 minutes
Building Kubernetes Solutions
Module 4•9 heures à terminer
Détails du module
This module immerses you in the hands-on world of Kubernetes solutions. You'll start by mastering containerization, constructing FastAPI microservices, and deploying containerized applications using Azure Container Registry and Amazon Elastic Container Registry. Next, explore options for cloud-based container orchestration, featuring Google Cloud Run and AWS Copilot, and expand your coding horizons in AWS Cloud9. Finally, address critical production issues as you delve into load testing, monitoring systems, the SRE mindset for MLOps, and the art of operationalizing microservices. This module offers a comprehensive toolkit to navigate Kubernetes in real-world scenarios, combining theory and practice to prepare you for Kubernetes success.
Inclus
13 vidéos8 lectures14 devoirs
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13 vidéos•Total 67 minutes
Build a Tiny Bash Container using GitHub Codespaces•9 minutes
Build FastAPI Microservice in Cloud9 in Python•6 minutes
Deploy a FastAPI PyTorch Containerized Application to AWS App Runner•8 minutes
Options for Container Orchestration•2 minutes
GCP Cloud Run•5 minutes
Build Microservice in Cloud9 in C#•7 minutes
AWS Copilot - Command Line Interface for Containerized Applications•9 minutes
Load-Testing with Locust•3 minutes
Monitoring Systems•1 minute
SRE Mindset for MLOps•5 minutes
Operationalize Microservices•2 minutes
CI for Microservices•7 minutes
What is Continuous Delivery?•3 minutes
8 lectures•Total 80 minutes
Using Container Registries with Kubernetes: Azure Container Registry and Amazon Elastic Container Registry (ECR)•10 minutes
Kubernetes and Google Cloud•10 minutes
Deploying Containerized Applications and Kubernetes in the Cloud with AWS•10 minutes
Getting Started with Site Reliability Engineering (SRE)•10 minutes
Continuous Delivery of FastAPI App to AWS App Runner•10 minutes
Final Project Explained•10 minutes
Next Steps•10 minutes
Share your learning experience•10 minutes
14 devoirs•Total 420 minutes
Kubernetes Data Engineering Solutions•30 minutes
Build a Tiny Bash Container using GitHub Codespaces•30 minutes
Build FastAPI Microservice in Cloud9 in Python•30 minutes
Deploying a FastAPI PyTorch Containerized Application to AWS App Runner•30 minutes
Options for Container Orchestration•30 minutes
GCP Cloud Run•30 minutes
Build Microservice in Cloud9 in C#•30 minutes
AWS Copilot•30 minutes
Load-Testing with Locust•30 minutes
Monitoring Systems•30 minutes
SRE Mindset for MLOps•30 minutes
Operationalize Microservices•30 minutes
CI for Microservices•30 minutes
Continuous Delivery•30 minutes
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Avis des étudiants
3.8
50 avis
5 stars
52 %
4 stars
12 %
3 stars
12 %
2 stars
10 %
1 star
14 %
Affichage de 3 sur 50
M
ML
4·
Révisé le 18 févr. 2024
It was great but the last module of week 4 felt isolated from the rest of the course.
V
VV
5·
Révisé le 19 mars 2025
For the first time I really understood what "virtualization" is and how things sort of expand for larger and larger units. Really solid stuff on CI/CD stuff also.
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