📘 AI Guides & Learning Paths
Structured learning paths to master AI from beginner to expert. Follow curated roadmaps designed for different goals and skill levels.
🌱 Complete Beginner Path
No coding background? Start here with a comprehensive introduction to AI concepts and tools.
Week 1-2: What is AI? → Understanding Machine Learning → Real-world AI Applications
Week 3-4: Python Basics → Data Structures → Essential Libraries (NumPy, Pandas)
Week 5-6: Your First ML Project → Supervised Learning → Model Evaluation
Week 7-8: Deep Learning Intro → Neural Networks → Image Classification
Start Beginner Path →
💻 Developer Path
Have coding skills? Level up fast with practical ML and AI development.
Month 1: ML Fundamentals → Scikit-learn → Feature Engineering → Model Selection
Month 2: Deep Learning → TensorFlow/PyTorch → CNNs → RNNs
Month 3: NLP & Transformers → LLMs → Fine-tuning → Embeddings
Month 4: MLOps → Docker → Kubernetes → CI/CD → Production Deployment
Start Developer Path →
🏢 Business Professional Path
Apply AI to your industry without becoming a data scientist.
Phase 1: AI Business Fundamentals → Use Cases → ROI Analysis
Phase 2: Industry Applications (Finance, Healthcare, Retail, Manufacturing)
Phase 3: No-Code AI Tools → Vendor Selection → Implementation Strategy
Phase 4: AI Strategy → Team Building → Change Management
Explore Industry Applications →
🧠 LLM & Generative AI Path
Master large language models and generative AI applications.
Foundation: Transformers Architecture → Attention Mechanisms → Tokenization
Practical: OpenAI API → Prompt Engineering → RAG Systems → Vector Databases
Advanced: Fine-tuning → LoRA → RLHF → Custom Model Training
Production: LLM Deployment → Cost Optimization → Monitoring
Start LLM Path →
🤖 Agentic AI Path
Build autonomous AI systems that can plan, reason, and take action.
Basics: Agent Fundamentals → ReAct → Tool Use → Memory Systems
Intermediate: Multi-Agent Systems → Coordination → Planning Algorithms
Advanced: Enterprise Agents → Process Automation → Self-Improvement
Production: Agent Deployment → Safety → Monitoring → Evaluation
Start Agentic AI Path →