🎓 AI & ML Courses

Learn prompt engineering best practices for application development.

Comprehensive introduction to machine learning, datamining, and statistical pattern recognition. Covers supervised learning, unsupervised learning, and best practices.

Deep dive into deep learning architectures for computer vision tasks.

Top-down teaching approach. Learn to train state-of-the-art models without lots of math.

Cutting-edge research in deep learning for NLP. Covers RNNs, attention, transformers.

Foundational AI course covering search, games, MDPs, reinforcement learning, and more.

Part 2 of fast.ai course. Build deep learning library from scratch.

Learn the core ideas in machine learning with scikit-learn.

The classic ML course that started the MOOC revolution.

Learn about generative AI, LLMs, and responsible AI.

Learn AI concepts and Azure AI services.

5-course specialization covering neural networks, CNNs, RNNs, and more.

Learn deep reinforcement learning from beginner to expert.

Handle missing values, non-numeric values, data leakage, and more.

Use TensorFlow and Keras to build and train neural networks.

Learn the fundamentals of generative AI and LLMs.

Learn to design, build, and maintain ML systems in production.

Google’s fast-paced, practical introduction to machine learning.

Learn about transformers and how to use them for NLP tasks.

MIT’s official introductory course on deep learning methods with applications.

Learn to build LLM applications with LangChain.

Learn to fine-tune LLMs for your specific use cases.

Advanced course on deep RL covering policy gradients, Q-learning, model-based RL.

Learn about diffusion models for image generation.

Become an expert in neural networks with PyTorch.