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Documentation Index

Fetch the complete documentation index at: https://ai.tharung.in/llms.txt

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AI Engineering Roadmap

Master:
  • Python
  • Machine Learning
  • Deep Learning
  • LLM Engineering
  • RAG
  • AI Agents
  • MLOps
  • System Design

Start Learning

Follow the complete step-by-step AI Engineering roadmap.

Core Learning Phases

Phase 0 — Orientation

Understand AI Engineering, market demand, and roadmap planning.

Phase 1 — Python

Learn Python, async programming, NumPy, Pandas, and OOP.

Phase 2 — Mathematics

Linear algebra, calculus, probability, optimization.

Phase 3 — Machine Learning

Regression, trees, clustering, evaluation metrics.

Phase 4 — Deep Learning

Neural networks, PyTorch, CNNs, transformers.

Phase 5 — NLP & Transformers

Attention, embeddings, GPT, BERT, tokenization.

Phase 6 — LLM Engineering

Prompt engineering, APIs, streaming, routing.

Phase 7 — Multi LLM Systems

Build intelligent routing and orchestration systems.

Phase 8 — RAG

Vector databases, embeddings, retrieval systems.

Phase 9 — AI Agents

Autonomous AI agents with tools and memory.

Phase 10 — Fine-tuning

LoRA, QLoRA, RLHF, DPO pipelines.

Phase 11 — Generative AI

Diffusion models, multimodal AI, voice AI.

Phase 12 — MLOps & LLMOps

Deployment, observability, Kubernetes, monitoring.

Phase 13 — AI System Design

Design scalable AI systems and architectures.

Phase 14 — SQL + pgvector

Build vector search systems using Postgres.

Phase 15 — Quantization

Optimize models for fast inference.

Phase 16 — Reinforcement Learning

PPO, RLHF, reward models, DPO.

Phase 17 — AI Safety

Ethics, governance, privacy, AI security.

Multi-LLM Platform

Build production-grade AI orchestration systems with routing and fallback.

Enterprise RAG

Multi-tenant RAG with reranking, HyDE, and vector databases.

AI Agent Platform

Autonomous research and coding agents with tool usage.

Production AI Infrastructure

Kubernetes + monitoring + observability for AI systems.

Learning Stack

Languages

Python, SQL, TypeScript

Frameworks

PyTorch, FastAPI, LangChain

Infrastructure

Docker, Kubernetes, Redis

Databases

Postgres, Pinecone, Qdrant

AI APIs

OpenAI, Claude, Gemini

Deployment

Vercel, AWS, GCP

Final Capstone

Production AI Platform

Combine Multi-LLM routing, RAG, Agents, Fine-tuning, Monitoring, and Kubernetes deployment into a single enterprise-grade platform.