AI-Assisted Development Learning Plan by Qwen
Based on your goal to build AI agents, data science/ML, and automation, here is your personalized study plan.
1. Recommended Language: Python
Why: Python is the industry standard for data science, machine learning, and AI agent development. It has the richest ecosystem of libraries (PyTorch, TensorFlow, LangChain, Pandas) and is excellent for scripting automation tasks.
Topic 1: Coding Basics
Variables, data types, if statements, loops, functions, OOP
| Resource | Type | Free? | Time | Description | Key Topics |
|---|---|---|---|---|---|
| Python.org Official Tutorial | Text-based Course | ✅ Free | ~10–15 hrs | The official Python tutorial — thorough and always up to date | Syntax, data types, loops, functions |
| Automate the Boring Stuff with Python | Textbook | ✅ Free | ~20–30 hrs | Hands-on book focused on practical Python from day one | Functions, OOP, file I/O, automation basics |
| CS50P (Harvard) | Video Course | ✅ Free | ~20–30 hrs | Harvard’s Python intro — excellent structure and problem sets | Full Python fundamentals, OOP |
| Python Crash Course (Matthes) | Textbook | 💲 Paid | ~25–35 hrs | Best-selling beginner book with projects including data viz | Variables, loops, OOP, mini-projects |
| Python Principles | Interactive Course | 💲 Paid | ~15–20 hrs | Bite-sized interactive exercises, great for building habits | Core syntax, logic, functions |
Topic 2: Software Architecture
Project structure, tech stacks, APIs, data flow, databases, testing, deployment
| Resource | Type | Free? | Time | Description | Key Topics |
|---|---|---|---|---|---|
| Full Stack Python | Reference | ✅ Free | ~10–15 hrs | Comprehensive guide to Python’s role across the full stack | Frameworks, databases, deployment |
| Real Python – Structuring Projects | Text-based Course | ✅ Free | ~5–8 hrs | Practical articles on packaging, project layout, and testing | Project structure, modules, virtual envs |
| Architecture Patterns with Python (O’Reilly) | Textbook | 💲 Paid | ~25–35 hrs | Deep dive into clean architecture and design patterns in Python | DDD, repositories, service layers |
| FastAPI Official Docs + Tutorial | Text-based Course | ✅ Free | ~10–15 hrs | Build production-grade APIs with Python’s fastest modern framework | REST APIs, async, data validation |
| pytest Documentation + Real Python Testing Guide | Reference | ✅ Free | ~8–12 hrs | Industry-standard testing in Python | Unit tests, fixtures, mocking |
Topic 3: Version Control & GitHub
Git fundamentals, branching, pull requests, collaboration workflows
| Resource | Type | Free? | Time | Description | Key Topics |
|---|---|---|---|---|---|
| Pro Git Book (git-scm.com) | Textbook | ✅ Free | ~10–15 hrs | The definitive Git reference, written by Git’s core contributors | Commits, branching, merging, remotes |
| GitHub Skills | Interactive Course | ✅ Free | ~5–8 hrs | Official GitHub learning paths with hands-on repo exercises | PRs, issues, Actions, collaboration |
| Learn Git Branching | Interactive Course | ✅ Free | ~4–6 hrs | Visual, gamified Git branching practice | Branching, rebasing, cherry-pick |
| The Git & GitHub Bootcamp (Udemy – Colt Steele) | Video Course | 💲 Paid | ~17 hrs | Most popular Git video course with real-world workflows | Full Git workflow, GitHub collaboration |
Topic 4: Privacy & Security
Authentication, hosting options, database security, deployment security
| Resource | Type | Free? | Time | Description | Key Topics |
|---|---|---|---|---|---|
| OWASP Top 10 | Reference | ✅ Free | ~5–8 hrs | Most critical web security risks — essential reading | Injection, broken auth, sensitive data exposure |
| FastAPI Security Docs | Reference | ✅ Free | ~6–10 hrs | Authentication, OAuth2, JWT, and security patterns in FastAPI | OAuth2, JWT, API security |
| Python Security Best Practices (Real Python) | Text-based Course | ✅ Free | ~4–6 hrs | Practical security guidance for Python developers | Secrets, input validation, dependency scanning |
| Google Cloud Security Fundamentals | Video Course | ✅ Free | ~8–12 hrs | Google’s intro to cloud security concepts | IAM, network security, encryption |
Topic 5: Microservices & Containerization [OPTIONAL]
Docker, container security, CI/CD, production deployment
| Resource | Type | Free? | Time | Description | Key Topics |
|---|---|---|---|---|---|
| Docker for the Absolute Beginner (KodeKloud) | Video Course | ✅ Free | ~10–15 hrs | Very beginner-friendly Docker intro with labs | Images, containers, Dockerfile |
| Docker Deep Dive (Nigel Poulton) | Textbook | 💲 Paid | ~15–20 hrs | Comprehensive, clear guide to Docker internals | Architecture, networking, storage |
| Kubernetes Basics (Kubernetes.io) | Interactive Course | ✅ Free | ~8–12 hrs | Official Kubernetes tutorial with interactive labs | Pods, deployments, services |
| CI/CD with GitHub Actions (GitHub Docs) | Reference | ✅ Free | ~5–8 hrs | Automate testing, building, and deploying with Actions | Workflows, jobs, runners |
Suggested Learning Timeline
Total Estimated Time: ~180–300 hours
| Weekly Hours | Total Duration |
|---|---|
| 5 hrs/week | ~9–12 months |
| 10 hrs/week | ~4–6 months |
| 20 hrs/week | ~2–3 months |
Recommended Weekly Study Structure (10 hrs/week)
3 hrs — structured course/book
3 hrs — coding exercises
2 hrs — building a project
1 hr — reading docs/blogs
1 hr — reviewing/refactoring code
Early Project Ideas for AI Agents
- AI Research Assistant – Summarizes articles, finds papers
- Web Automation Agent – Automates repetitive browser tasks
- Data Analysis AI – Cleans, visualizes, and interprets datasets
- Multi-Agent Workflow – Coordinates multiple AI agents for complex tasks
- LLM-Powered API Service – Serves AI capabilities via REST API
Key Takeaway
Start building immediately — even with basic Python knowledge. The fastest way to learn AI development is to build AI projects.