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Complete O'Reilly Learning Path 2024

· 10min · Pragmatic AI Labs
Table of Contents

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:

Do you want to learn AWS Advanced AI Engineering?

Production LLM architecture patterns using Rust, AWS, and Bedrock.

Check out our course!
  • Start with Foundations if you're new to programming or cloud computing
  • Choose a Specialization Track:
    • Cloud (AWS, Azure, or GCP)
    • AI/ML Development
    • Data Engineering
    • DevOps
    • System Administration
    • Programming Languages
  • 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)
  • 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

Cloud Platforms - Azure

Cloud Platforms - AWS

Modern Programming Languages

MLOps and AI Engineering

Cloud Security and Certification

Advanced Programming Topics

AI Ethics and Responsible Development

System Administration and Linux

Cloud Native Development and DevOps

Data Engineering and Analytics

Security and Best Practices

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:

  • Start with foundational courses in your area of interest
  • Complete hands-on projects as you learn
  • Join the course discussions and communities
  • Take notes and create your own examples
  • Practice regularly with the provided exercise files

Happy learning! 🚀

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Based on this article's content, here are some courses that might interest you:

  1. AWS Advanced AI Engineering (1 week)
    Production LLM architecture patterns using Rust, AWS, and Bedrock.

  2. Cloud Computing Foundations (5 weeks)
    Learn the fundamentals of cloud computing across major platforms including AWS, Azure, and Google Cloud. Master essential DevOps practices and gain hands-on experience building and deploying cloud applications.

  3. AWS Certified Cloud Practitioner Preparation (7 weeks)
    Master AWS cloud fundamentals and prepare for the AWS Certified Cloud Practitioner certification exam. Learn through hands-on labs and real-world demonstrations while building practical cloud computing skills.

  4. MLOps Platforms: Amazon SageMaker and Azure ML (5 weeks)
    Learn to implement end-to-end MLOps workflows using Amazon SageMaker and Azure ML services. Master the essential skills needed to build, deploy, and manage machine learning models in production environments across multiple cloud platforms.

  5. 52 Weeks of AWS: Complete Cloud Certification Journey (21 weeks)
    Complete AWS certification preparation covering Cloud Practitioner to Machine Learning specializations in 52 weeks

Learn more at Pragmatic AI Labs