AI SYSTEM DESIGN ROADMAP │ ├── 1. FOUNDATIONS │ ├── AI, ML, Deep Learning & Generative AI │ ├── Mathematics, Statistics & Probability │ ├── Python, NumPy & Pandas │ ├── Neural Networks & Transformers │ └── LLM Fundamentals & Tokenization │ ├── 2. AI MODEL ARCHITECTURE │ ├── Model Selection & Evaluation │ ├── LLMs, SLMs & Multimodal Models │ ├── Embedding Models & Rerankers │ ├── Fine-Tuning, LoRA & PEFT │ └── Model Serving & Inference │ ├── 3. DATA ENGINEERING │ ├── Data Collection & Ingestion │ ├── Data Cleaning & Preprocessing │ ├── Data Labeling & Governance │ ├── Feature & Embedding Pipelines │ └── Data Quality & Versioning │ ├── 4. LLM APPLICATION ARCHITECTURE │ ├── Prompt Engineering │ ├── Structured Outputs & Function Calling │ ├── RAG (Retrieval-Augmented Generation) │ │ ├── Document Chunking │ │ ├── Embeddings & Vector Databases │ │ ├── Hybrid Search & Reranking │ │ └── Retrieval Evaluation │ ├── AI Agents & Tool Use │ ├── Memory & Context Management │ └── Multi-Agent Systems │ ├── 5. SYSTEM ARCHITECTURE │ ├── Requirements & Workload Estimation │ ├── Monoliths, Microservices & Modular Design │ ├── API Gateway & Model Gateway │ ├── Synchronous & Asynchronous Processing │ ├── Message Queues & Event-Driven Systems │ ├── Caching & Semantic Caching │ ├── Load Balancing & Autoscaling │ └── Distributed Systems & Fault Tolerance │ ├── 6. STORAGE & INFRASTRUCTURE │ ├── SQL & NoSQL Databases │ ├── Vector Databases │ ├── Object Storage & Data Lakes │ ├── GPU / CPU Compute Infrastructure │ ├── Containers & Kubernetes │ ├── Cloud Platforms │ └── Model Serving Infrastructure │ ├── 7. AI EVALUATION & OBSERVABILITY │ ├── Offline & Online Evaluation │ ├── Accuracy, Relevance & Groundedness │ ├── Hallucination Detection │ ├── LLM-as-a-Judge │ ├── Tracing & Distributed Logging │ ├── Latency, Throughput & Token Usage │ └── A/B Testing & Continuous Evaluation │ ├── 8. SECURITY & GOVERNANCE │ ├── Authentication & Authorization │ ├── Prompt Injection Defense │ ├── Data Privacy & PII Protection │ ├── Secrets & Key Management │ ├── Guardrails & Output Validation │ ├── Model Supply Chain Security │ └── Responsible AI & Compliance │ ├── 9. PERFORMANCE & COST OPTIMIZATION │ ├── Quantization & Distillation │ ├── Batching & Parallel Inference │ ├── Model Routing & Cascading │ ├── KV Caching │ ├── GPU Utilization & Throughput │ ├── Token Budget Optimization │ └── Quality–Latency–Cost Trade-offs │ ├── 10. MLOps & LLMOps │ ├── CI/CD & Model Versioning │ ├── Automated Testing & Evaluation │ ├── Model Deployment & Rollbacks │ ├── Data & Prompt Versioning │ ├── Drift Detection & Monitoring │ └── Continuous Improvement │ └── 11. END-TO-END AI SYSTEM DESIGN ├── AI Chatbot / Customer Support ├── RAG-Based Knowledge Assistant ├── AI Coding Assistant ├── AI Search & Recommendation Engine ├── Document Intelligence Platform ├── AI Agent / Workflow Automation ├── Real-Time Voice AI System ├── Multimodal AI Application ├── Large-Scale AI Inference Platform └── Production-Ready AI SaaS ├── Requirements & Architecture ├── Data & Model Pipeline ├── APIs & Infrastructure ├── Security & Evaluation ├── Scaling & Cost Optimization └── Reliability & Production Monitoring Follow @e_opore to learn more. Bookmark and share for more people to master it.