This roadmap reflects my personal journey in learning Artificial Intelligence and Machine Learning — built from practical experience, online certifications, and self-guided exploration.
Whether you're a beginner or a working professional curious about AI, this structured plan will guide you from foundational knowledge to hands-on projects that actually demonstrate your skills.
💡 Why I Created This:
- To stay focused and goal-oriented in my AI/ML learning
- To help others (especially non-tech professionals) learn AI in simple, actionable steps
- To show potential employers my initiative and ability to self-learn, apply, and share
Feel free to explore the stages, check out the tools, and even repurpose this roadmap for your own growth!
| Phase | Status | Timeline | Notes / Goals |
|---|---|---|---|
| 🌱 Foundations | ✅ Completed | Weeks 1–4 | Completed Generative AI Foundation Certificate from UpGrad. Learned prompt engineering, AI tools (ChatGPT, Canva AI, Notion AI) |
| 🔍 ML Fundamentals | 🚧 In Progress | Weeks 5–12 | Starting Python basics, exploring machine learning concepts and libraries |
| 🧠 Deep Learning | 🔲 Not Started | Weeks 13–20 | Plan to learn neural networks, CNNs, transformers |
| 🚀 Specialization | 🔲 Not Started | Weeks 21+ | Focus on NLP, GenAI apps, resume analyzer, chatbot projects |
✅Beginner (No technical background)
✅ Completed Generative AI Foundation Certificate
✅ Hands-on with AI tools like ChatGPT, Notion AI, Canva AI
⏳ Currently learning Python & ML basics
[ ] Hands-On Machine Learning – Aurélien Géron
👉 Priority for ML + practical TensorFlow projects
[ ] Deep Learning – Ian Goodfellow
📌 Advanced theory – read selectively as needed
[ ] Pattern Recognition and Machine Learning – C. Bishop
📌 Math-heavy reference, optional for now
[ ] Generative AI Foundation (UpGrad)
✅ Completed – Prompt engineering, ChatGPT, Canva AI
[ ] Machine Learning – Andrew Ng (Coursera)
🎯 Start here next – builds math + ML intuition
[ ] Deep Learning Specialization – deeplearning.ai
🚀 Move here after ML basics
[ ] Fast.ai – Practical Deep Learning
Great for building real apps quickly
[ ] 3Blue1Brown
✅ Used for Linear Algebra visuals
⭐️ Highly recommended for ML stats & concepts
[ ] Tech With Tim
Covers projects, Python, and tutorials
Weekly reading goal: 2 articles
[ ] Distill.pub
Optional – Deep, visual explanations
[ ] Papers With Code
Use for project ideas + current SOTA models