Coverage map
The ABCD computer science framework
525 topics across five domains. Every technology follows the same ten-stage progression, so new models, chains, cloud platforms, languages and data tools slot in without redesigning the curriculum.
01 Fundamentals02 Programming03 Tools04 Development05 Architecture06 Security07 Deployment08 Advanced09 Research10 Projects
From search and knowledge representation through machine learning, deep learning and generative models to agentic AI, LLM engineering and responsible deployment.
1. AI Foundations
- AI Fundamentals
- Intelligent Systems
- Search Algorithms
- Knowledge Representation
- Expert Systems
- Probability & Statistics for AI
- Linear Algebra for AI
- Optimization
- Computational Learning Theory
2. Machine Learning
- Supervised Learning
- Unsupervised Learning
- Semi-Supervised Learning
- Self-Supervised Learning
- Reinforcement Learning
- Online Learning
- Transfer Learning
- Federated Learning
- Continual Learning
- Meta Learning
3. Deep Learning
- Neural Networks
- CNNs
- RNNs
- LSTM / GRU
- Autoencoders
- GANs
- Transformers
- Vision Transformers
- Diffusion Models
- Graph Neural Networks
- Neural Rendering
4. Generative AI
- Generative AI Fundamentals
- LLMs
- Multimodal Models
- Text-to-Image
- Text-to-Video
- Text-to-Audio
- Speech Models
- Code Generation
- AI Reasoning Models
- Foundation Models
- Small Language Models
5. AI Agents ⭐
- AI Agents
- Agentic AI
- Autonomous Agents
- Multi-Agent Systems
- Agent Memory
- Agent Planning
- Tool Calling
- Function Calling
- Agent Workflows
- Agentic RAG
- Multi-Agent Collaboration
- Agent-to-Agent Communication
- Computer-Use Agents
- Coding Agents
- Browser Agents
- Autonomous Research Agents
- Agent Evaluation
- Agent Safety
- Agent Governance
6. LLM Engineering
- Prompt Engineering
- Context Engineering
- RAG
- Advanced RAG
- Vector Search
- Embeddings
- Knowledge Graph RAG
- Fine-Tuning
- LoRA / QLoRA
- RLHF
- DPO
- GRPO
- Synthetic Data
- Model Distillation
- Quantization
- Model Compression
7. AI Infrastructure
- GPUs
- TPUs
- AI Accelerators
- CUDA
- Distributed Training
- Model Serving
- Inference Optimization
- vLLM
- TensorRT
- AI APIs
- Model Deployment
- MLOps
- LLMOps
- AI Observability
8. AI Applications
- Computer Vision
- NLP
- Speech AI
- Robotics
- Autonomous Vehicles
- Healthcare AI
- Financial AI
- Cybersecurity AI
- AI for Science
- AI for Software Development
- AI for Education
- AI + Robotics
9. Responsible AI
- AI Safety
- AI Alignment
- Explainable AI
- AI Bias
- AI Security
- Adversarial ML
- Privacy-Preserving AI
- AI Governance
- AI Ethics
- AI Regulation