| 🧠Machine Learning |
Algorithms that learn from data. |
Python, statistics, linear algebra, scikit-learn |
| 🔗Deep Learning |
Subset of ML using neural networks with many layers. |
Python, TensorFlow/PyTorch, neural networks, GPU usage |
| 🧩Neural Networks |
Brain-inspired computational models for prediction and classification. |
Linear algebra, backpropagation, Python, optimization techniques |
| 💬Natural Language Processing (NLP) |
Enables machines to understand and generate human language. |
Python, NLTK/spaCy, transformers, text preprocessing |
| ✨Generative AI |
AI systems that create text, images, audio, video, or code. |
Prompt engineering, LLM APIs, Python, diffusion models |
| 👁️Computer Vision |
AI that interprets images and video. |
OpenCV, CNNs, Python, image processing |
| 🎮Reinforcement Learning |
Learning through rewards and penalties in environments. |
Markov decision processes, Python, RL libraries, math foundations |
| 📚Large Language Models (LLMs) |
Large-scale neural networks trained on massive text datasets. |
Transformers, Hugging Face, prompt design, API integration |
| 🤖Robotics |
Intelligent automation in physical machines. |
ROS, C++/Python, sensors, control systems |
| 🎤Speech Recognition |
Converts spoken language into text. |
Signal processing, Python, speech APIs |
| 🔊Speech Synthesis (TTS) |
Converts text into spoken audio. |
Audio processing, TTS libraries, neural vocoders |
| 📈Predictive Analytics |
Forecasts future outcomes using historical data. |
SQL, Python/R, statistics, data visualization |
| ⛏️Data Mining |
Extracts patterns from large datasets. |
SQL, Python, clustering algorithms, data cleaning |
| 📱Edge AI |
AI processing on local devices instead of cloud. |
Embedded systems, TensorFlow Lite, IoT knowledge |
| 🚗Autonomous Systems |
Self-operating vehicles and drones. |
Computer vision, robotics, control systems, AI integration |
| ⚖️AI Ethics |
Guidelines and principles for responsible AI development, deployment and usage. |
Regulatory knowledge, bias detection, policy frameworks |
| ⚙️MLOps |
Deploying and maintaining ML models in production. |
Docker, Kubernetes, CI/CD, cloud platforms (Azure/AWS/GCP) |
| 💻AI Hardware (GPUs/TPUs) |
Specialized hardware accelerating AI workloads. |
CUDA, parallel computing, hardware optimization |
| 🗂️Knowledge Graphs |
Structured data relationships for reasoning and search. |
Graph databases (Neo4j), SPARQL, ontology design |
| 📋Expert Systems |
Rule-based systems mimicking expert decision-makin |
Logic programming, rule engines, domain expertise |