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Complete O'Reilly Learning Path 2024

2024-11-25

Complete O'Reilly Learning Path 2024 - Extended Edition

This learning path contains over 200 courses organized by topic and difficulty. Here's how to navigate it effectively:

  1. Start with Foundations if you're new to programming or cloud computing
  2. Choose a Specialization Track:
    • Cloud (AWS, Azure, or GCP)
    • AI/ML Development
    • Data Engineering
    • DevOps
    • System Administration
    • Programming Languages
  3. Time Commitment:
    • Quick Start courses (1-2 hours each)
    • Standard courses (4-6 hours)
    • Deep dive courses (10+ hours)
    • Series courses (20+ hours spread across multiple modules)
  4. Recommended Progression:
    • Complete foundation courses in your area
    • Take certification prep courses if desired
    • Build practical skills with hands-on courses
    • Explore advanced topics and specializations

🎯 Start with courses marked "Fundamentals" or "Beginners" in your chosen track. Most courses are self-contained, but prerequisites are noted where relevant.

Complete Learning Path 2024

Foundations

  1. Introduction to Generative AI
  2. Python for Beginners
  3. Linux for Beginners
  4. Python Functions and Classes
  5. Python Testing for Beginners
  6. Intro to Pandas
  7. Learn Python in One Hour
  8. Python Bootcamp
  9. Data Science on Your First Day with Python
  10. Business Analytics and Data Science on Day 1

Cloud Platforms - Azure

  1. Microsoft Azure Fundamentals (AZ-900) Certification
  2. Microsoft Azure AI Fundamentals (AI-900) Certification
  3. Azure LLMOps
  4. Azure PostgreSQL
  5. Azure AutoML
  6. Microsoft Azure Data Scientist Associate (DP-100)-2023
  7. Introduction to Azure Functions
  8. Azure Remote Compute for VSCode
  9. Azure in GitHub Actions
  10. Azure Databricks, Pandas and OpenDatasets
  11. Learn Azure ML AutoML in One Hour
  12. AZ-900 Azure Fundamentals Quick Reference Guide

Cloud Platforms - AWS

  1. 52 Weeks of AWS-The Complete Series
  2. AWS Certified Security - Specialty Exam Prep: SCS-C02
  3. AWS Solutions Architect Professional (SAP-C02) 2023
  4. AWS Certified Cloud Practitioner
  5. AWS Certified Machine Learning - Specialty (MLS-C01)-2023
  6. AWS Storage Solutions 2022: EBS, S3, EFS, Glacier
  7. AWS Step Functions for Optimization
  8. AWS Lambda and Step Functions
  9. AWS CDK with Python
  10. AWS CloudShell
  11. Live Coding Amazon Bedrock
  12. GenAI and LLMs on AWS
  13. AWS Python Computer Vision
  14. Using AWS SageMaker

Modern Programming Languages

  1. Rust Fundamentals
  2. Python Bootcamp
  3. 52 Weeks of Swift
  4. Go for Python Developers
  5. Rust Data Engineering
  6. 52 Weeks of Rust
  7. Live Coding in Rust
  8. Rust for Pythonistas
  9. Assimilate Go
  10. Assimilate Haskell
  11. Using Rust with Python
  12. Switching to Rust from Python

MLOps and AI Engineering

  1. Hugging Face for MLOps
  2. Applied Hugging Face
  3. Enterprise MLOps Interviews
  4. MLOps Masterclass: Theory to DevOps to Cloud-native to AutoML
  5. MLOps Platforms From Zero: Databricks, MLFlow/MLRun/SKLearn
  6. Introduction to MLFlow for MLOps
  7. MLOps 248 Course: Building AI with Bedrock Agent
  8. Doing MLOps with Databricks and MLFlow
  9. MLOps Workflow with GitHub Actions
  10. MLOps Foundations

Cloud Security and Certification

  1. AWS Certified Security - Specialty
  2. AWS Certified Advanced Networking - Specialty
  3. AWS Certified Data Analytics (DAS-C01)
  4. Learn to pass ANY AWS Certification Exam
  5. AWS Solutions Architect Certification In ONE HOUR
  6. AWS Machine Learning Certification In ONE HOUR
  7. GitHub Enterprise Certified
  8. Professional Data Engineer Certification Course
  9. Google Professional Cloud Architect Certification Course 2023
  10. Google Professional Machine Learning Engineer Course 2023
  11. Databricks Certified Data Engineer Associate

Advanced Programming Topics

  1. Python Functions Master Class 2023
  2. Rust GUI Development for Linux
  3. Using Rust with Python
  4. Python Standard Library Essentials With Jupyter
  5. Python Command Line Tools Course
  6. Build a useful Python decorator
  7. The yield keyword in Python
  8. Python Dictionaries Course
  9. Advanced Testing with Pytest
  10. Effective Python Exceptions
  11. Python and Pandas
  12. Speed up Python dramatically with CUDA GPU

AI Ethics and Responsible Development

  1. Radical Ideas in AI Ethics
  2. Agile for AI
  3. Introduction to LLM vulnerabilities
  4. Enterprise MLOps Interviews
  5. Responsible Generative AI and Local LLMs
  6. Small Language Models and LlamaFile
  7. LLM Server
  8. LLMOps Applications

System Administration and Linux

  1. Kubuntu Linux Desktop
  2. Year of The Linux Desktop
  3. Bash Essentials for Cloud Computing
  4. Learn Vim in One Hour
  5. Create a Vim Plugin
  6. Linux and Bash Going Pro
  7. Assimilate Bash
  8. VSCode Development Environments

Cloud Native Development and DevOps

  1. Serverless Rust on AWS
  2. Build Real-World AWS Microservices with Python and FastAPI
  3. AWS Fargate for Flask Microservice
  4. Python Microservice with FastAPI and AWS App Runner
  5. Fast, documented Machine Learning APIs with FastAPI
  6. DevOps Theory to Practice
  7. Master Docker
  8. Python DevOps Master Class 2022
  9. GitHub Actions and GitOps
  10. Jenkins CI/CD and GitHub

Data Engineering and Analytics

  1. MySQL for Data Engineering
  2. Data Platforms: Spark to Snowflake
  3. Apache Airflow Fundamentals
  4. Scripting with Python and SQL for Data Engineering
  5. Data Story Telling
  6. SQL for CSV Datasets
  7. Achieving Scalability with Vector Graph and Key Value Databases
  8. Kubernetes for Data

Security and Best Practices

  1. GitHub Foundations: Privacy, Security, and Administration
  2. Introduction to Software Bill of Materials
  3. Secure Projects with Vulnerability Scanning in GitHub
  4. Get Started with Distributed Tracing
  5. GitHub Codespaces Course
  6. GitHub Fundamentals
  7. Applied GitHub Platform
  8. Introduction to GitHub Models

This comprehensive learning path now includes all 200+ courses organized into relevant categories, making it easier to find the right courses for your learning journey. Each section progresses from fundamentals to advanced topics, allowing you to build your skills systematically.

Remember to:

Happy learning! 🚀