AI Learning Roadmap

Your structured path from beginner to AI expert

Learning Path Overview

Follow this progressive path to build your AI expertise systematically:

1

Foundation Phase

Build core understanding of AI concepts and mathematics

AI History Classical ML Deep Learning LLMs Intro
2

Tools & Frameworks

Master modern AI development tools and platforms

Hugging Face LangChain Vector DBs Prompting
3

Application Development

Build real-world AI applications and systems

RAG Systems Code Assistants Multi-Agent Chatbots
4

Production & Scale

Deploy and manage AI systems at enterprise scale

ML Lifecycle MLOps GPU Infra Deployment
5

Specialization & Leadership

Choose your specialty and lead AI initiatives

Industry AI Governance Strategy Leadership

Accelerated Track

3 Months
  • 20+ hours per week commitment
  • Focus on practical implementation
  • Skip advanced theory initially
  • Build 2-3 projects
  • Best for: Career switchers
Recommended

Standard Track

6 Months
  • 10-15 hours per week
  • Balanced theory and practice
  • Complete all core modules
  • Build 5+ projects
  • Best for: Most learners

Deep Dive Track

12 Months
  • 5-10 hours per week
  • Comprehensive understanding
  • Research paper reading
  • Open source contributions
  • Best for: Academic pursuit

Career Path Options

Choose a specialization based on your interests and career goals:

🤖

ML Engineer

Build and deploy machine learning models at scale

Focus: Modules 1, 2, 4, 7
💬

GenAI Developer

Create AI-powered applications using LLMs

Focus: Modules 2, 3, 6, 7
📊

Data Scientist

Extract insights and build predictive models

Focus: Modules 1, 3, 5, 7
🏗️

AI Infrastructure

Design and manage AI systems infrastructure

Focus: Modules 4, 5, 6, 7
👔

AI Product Manager

Lead AI product development and strategy

Focus: Modules 3, 6, 8
🔬

AI Researcher

Push the boundaries of AI capabilities

Focus: All modules + research papers

Skills Development Tree

Master these skills progressively as you advance through the roadmap:

Foundation Skills

Python Programming Linear Algebra Statistics Calculus Data Structures Algorithms

Core AI/ML Skills

Supervised Learning Neural Networks Deep Learning Unsupervised Learning Reinforcement Learning Feature Engineering

GenAI & LLM Skills

Prompt Engineering RAG Systems Fine-tuning Vector Databases Embeddings Agent Design

Production Skills

Model Deployment API Development Docker/Kubernetes CI/CD Monitoring A/B Testing

Soft Skills

Problem Solving Communication Project Management Team Collaboration Technical Writing Presentation

Module Dependencies

Some modules build on others. Here's the recommended prerequisite structure:

Ready to Start Your Journey?

Begin with the foundations and progress at your own pace

Get Started → View Modules →