Learning Hub — AI Engineer Journey
Goal: AI Engineer · Duration: 6 months · 24 weeks · 168 days · Daily time: 1–2 hours
Synced from my Notion workspace. This is the real plan I follow — nothing polished away.
The Golden Rule
A topic is only complete when:
- ✅ Project built and run (output confirmed)
- ✅ Quiz passed (at least 2/3 correct)
- ✅ Communication exercise done (recorded or written)
Never mark complete because someone said to.
Track Activation Timeline
| Track | Starts | Status |
|---|---|---|
| 🤖 AI Engineering | Week 1 | 🟢 Active |
| 💬 Communication | Week 1 | 🟢 Active |
| 📚 CS Fundamentals | Week 1 | 🟢 Active (light) |
| 🏗️ System Design | Week 5 | ⚪ Not started |
| 🔢 DSA | Week 9 | ⚪ Not started |
| 🎯 Career Prep | Week 13 | ⚪ Not started |
Start Here
- DSA Patterns — The Complete Guide — every core pattern with visuals, templates, and when to use it
- Progress & Trackers — my live status across all tracks
- Blog — long-form technical writing
Hope AI — ML & DS Course (38 modules, 6 phases)
The full AI-engineer track I'm working through. Notes live in my Notion and sync here on demand.
| Phase | Weeks | Focus |
|---|---|---|
| 🌱 Phase 1 | 0–3 | Foundations & Python |
| 🤖 Phase 2 | 4–8 | Core Machine Learning & Data Science |
| 🌐 Phase 3 | 9–10 | Web Dev & Databases |
| 🧠 Phase 4 | 11–15 | Deep Learning & GenAI Basics |
| 🚀 Phase 5 | 16–20 | RAG · Agents · LangChain · LangGraph · MCP |
| ☁️ Phase 6 | 21–23 | Cloud Deployment (GCP · AWS) |
Every module below has its own page with the complete notes — TL;DRs, mental models, code cheatsheets, interview Q&A, and checklists. Use the sidebar (or the full curriculum list underneath) to move around exactly like in my Notion. All 38 modules are published.
📚 Full Curriculum — every module
🌱 Phase 1 — Foundations (Weeks 0–3)
- 🌱 Week 0 — Ground Work
- 🗺️ Week 1 — Travel Path (AI Foundations)
- 🐍 Week 2 — Python for AI & Data Science
- 📈 Week 3 — Machine Learning: Regression
🤖 Phase 2 — Core ML & Data Science (Weeks 4–8)
- 🎯 Week 4.1 — ML: Classification
- 🔵 Week 4.2 — ML: Clustering
- 📝 Week 4.2 — ML Practice & Interview Prep
- 📊 Week 5 — Univariate Analysis
- 🔗 Week 6 — Bivariate Analysis
- 📊 Week 7 — Data Visualization
- ⚙️ Week 8.1 — Feature Engineering & Selection
- 📉 Week 8.2 — Dimensionality Reduction
🌐 Phase 3 — Web Dev & Databases (Weeks 9–10)
- 🌐 Week 9.2 — Web Dev for AI: Streamlit
- 🏗️ Week 9.3 — Web Dev for AI: FastAPI & Flask
- 🎬 Week 10 — Recommendation Systems
- 🗄️ Week 10.1 — MySQL for Data Science & AI
🧠 Phase 4 — Deep Learning & GenAI (Weeks 11–15)
- 🧠 Week 11 — Deep Learning: ANN & CNN
- 📈 Week 12 — Time Series Analysis
- 💬 Week 13 — Natural Language Processing
- 🧠 Week 13.1 — Advanced NLP (Transformers & BERT)
- 💬 Week 14 — ChatGPT API & Advanced Techniques
- ⚡ Week 15 — Real-Time AI Apps
🚀 Phase 5 — Agentic AI (Weeks 16–20)
- 🔍 Week 16 — RAG, Embeddings & Vector Databases
- 🤖 Week 17 — AI Agents
- ⛓️ Week 18 — LangChain
- 🕸️ Week 19 — LangGraph
- 🤖 Week 19.1 — Agentic AI Application
- 🔌 Week 20 — MCP Server
☁️ Phase 6 — Cloud Deployment (Weeks 21–23)
🎯 Career Resources
- 🗣️ Communication Skills for AI Engineers
- 📄 Resume & Interview Preparation
- 💻 Technical Interview Preparation
- ❓ AI/ML Question Bank
- 📚 Technical Concepts — Master Reference
- 🎯 Get Goal — AI Engineer Job Strategy
- 📱 LinkedIn Content Strategy
🚀 AI Engineer Journey — Plan & Trackers
- 📜 Session Constitution — 13 Rules
- 🗓️ 6-Month Roadmap Overview
- 📅 Month 1 — Foundation (Wk 1–4)
- 📅 Month 2 — Real Applications (Wk 5–8)
- 📅 Month 3 — Agentic AI + DSA (Wk 9–12)
- 📅 Month 4 — Advanced AI + Portfolio (Wk 13–16)
- 📅 Month 5 — Full Interview Prep (Wk 17–20)
- 📅 Month 6 — Land the Job (Wk 21–24)
- 💬 Communication Track — Full Curriculum
- 🏗️ System Design Bank
- 📦 Projects Portfolio
- 🎯 Target Companies — Prep Guide
- 🔧 Tools & Resources
- 🇮🇳 Tamil Communication Skills
- ⚡ AI Generalist Master Roadmap 2026
📚 Vanakkam DSA Course (24 sections)
- 📚 Vanakkam DSA Learning Hub
- S1 — Introduction
- S2 — Warm Up
- S3 — Time/Space Complexity
- S4 — Arrays (Easy/Medium)
- S5 — Recursion
- S6 — Searching & Sorting
- S7 — Linked List
- S8 — Strings
- S9 — Stacks & Queues
- S10 — Binary Search
- S11 — Two Pointers & Sliding Window
- S12 — Binary Tree
- S13 — Binary Search Tree
- S14 — Heap / Priority Queue
- S15 — Hashing
- S16 — Backtracking
- S17 — Greedy Algorithm
- S18 — Dynamic Programming
- S19 — Graphs
- S20 — Tries
- S21 — Searching & Sorting (Advanced)
- S22 — DP & Arrays (Advanced)
- S23 — Strings (Advanced)
- S24 — Bonus