DevOps Launchpad - Tutorial Overview

Welcome to the DevOps Launchpad course! This program is designed to provide you with the essential skills needed to build, deploy, and manage AI applications using modern technologies like Kubernetes, Docker, CI/CD pipelines, and GPU infrastructure.

Pre-Training

Use following Google courses and its full Playlist videos

• Computer Fundamentals - Google Course
• OS Concepts and Practical - Windows and Linux
• Network Infrastructure - Google Course
• Git & GitHub - Google Course
• Python for Automation - Google Course

Course Highlights:

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Course Curriculum:

Introduction to Tech & AI Career

• Overview of technology and the AI tech stack
• Mistakes to avoid in the tech job hunt
• Introduction to DevOps and how AI is changing the landscape

Software Development

• Agile SDLC, Developer PC setup with Git and Visual Studio
• Software Development with Python
• Impact of AI on software development and the software lifecycle
• Repositories
  • Git tutorial
  • Python Tutorial
  • PHP Tutorial
  • Social Media Scheduler tldr-today
  • Yelp Review Scraper
  • NLP Sentiment Analysis

Linux and Networking

• Deconstructing a computer, networking fundamentals, subnetting, DNS, and DHCP
• Introduction to Linux, Redhat Linux, commands, and file systems
• Networking fundamentals including IPv6, VPN, and cloud networking basics
• Repositories
  • Shell Scripting
  • Ansible Tutorial

Cloud Computing

• Deep dive into AWS, Azure, and GCP
• Introduction to cloud services, EC2, S3, Lambda, and Google AI tools
• Setting up a virtual private cloud and Terraform for Infrastructure as Code (IaC)
• Repositories
  • Quick Labs to Launch Cloud Instance

DevOps & Automation

• Introduction to Docker and Kubernetes for containerized applications
• CI/CD pipeline development with Jenkins and GitHub Actions
• Terraform projects, Ansible for automation, and setting up deployment pipelines
• Repositories
  • Terraform
  • Pulumi
  • Ansible
  • Docker
  • Kubernetes

Data Engineering & Platforms

• Introduction to PySpark and Databricks
• Introduction to SnowflakeDB
• Basic Data Analytics and Data Science
• Repositories
  • Snowflake
  • Databricks
  • Elasticsearch
  • Data Science
  • PostgreSQL

Advanced AI Platform Engineering

• Site Reliability Engineering (SRE) for AI workloads
• Ensuring scalability, high availability, and fault tolerance for AI inference
• Observability and model-aware monitoring for AI platforms

Projects

• Deploying AI Applications: Full cycle deployment of web apps, databases, and voting apps with Kubernetes and AWS ECS
• LLMOps Projects: Deploying a DB-Agent on cloud, optimizing LLaMA inference on Nvidia H100

Special Topics:

• AI Platform Engineering Careers: How to adapt to AI and evolve your DevOps career with skills in LLMOps and AI agents
• Observability and Logging for AI Cloud: Infrastructure monitoring, traditional vs AI GPU cloud environments

Interview Preparation

• k8s Interview
• Interview challenge

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Subscription Plans:

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