AI Courses

A practical guide to fine-tuning large language models for your use cases without massive compute.

Learn best practices for prompt engineering with LLMs like ChatGPT.

Learn the fundamentals of machine learning with practical examples. No prior experience needed.

Learn to build AI agents and applications using LangChain framework with OpenAI models.

Non-technical introduction to generative AI, covering how it works and how to use it effectively.

OpenAI's educational resource for deep reinforcement learning with implementations.

Learn how to build Retrieval Augmented Generation systems to enhance LLM responses with your data.

MIT's introductory course on deep learning methods with applications to CV, NLP, and more.

Learn the foundations of effective prompt engineering for large language models.

Master neural networks, CNNs, RNNs, and transformers with hands-on projects.

Complete NLP specialization covering transformers, attention mechanisms, and applications.

Free online introduction to AI for non-technical learners. No programming required.

Learn about LangGraph’s components and how they enable the development, debugging, and maintenance of AI agents. Integrate agentic search capabilities to enhance agent knowledge and performance. Learn directly from LangChain founder Harrison Chase and Tavily founder Rotem Weiss.

Learn when and how to fine-tune LLMs for specific tasks and domains.

Non-technical introduction to generative AI covering ChatGPT, image generation, and more.

Introduction to image processing, object detection, and basic computer vision techniques.

Practical automation tutorials combining Python scripting with AI APIs for productivity.

Learn what LLMs are, their use cases, and how to use them responsibly in applications.

A non-technical course to understand AI concepts, terminology, and what AI can and cannot do.

Learn how to fine-tune pre-trained models for your specific tasks using the Hugging Face ecosystem.

Google's fast-paced, practical introduction to machine learning with TensorFlow APIs.

Learn how generative models like Stable Diffusion and DALL-E work.

Automate tasks with Python including web scraping, file management, and API integration.

Learn Python for data analysis, visualization, and machine learning with NumPy, Pandas, and Scikit-Learn.

Prepare for TensorFlow certification with computer vision, NLP, and time series models.

Master deep RL algorithms including DQN, A3C, PPO, and their applications.

MLOps specialization covering model deployment, monitoring, and production pipelines.

Learn the essential mathematics behind machine learning algorithms. Beginner-friendly approach.

Learn to build and train neural networks using TensorFlow. Great first step into practical AI.

Hands-on introduction to building AI agents with Python. Learn state management, decision making, and tool use.

Interactive tutorials covering deep learning basics with real datasets and competitions.

Learn the basics of deploying and managing machine learning models in production environments.

Learn how agents learn to make decisions through trial and error. Includes classic algorithms and examples.

Microsoft's comprehensive introduction to AI concepts, tools, and applications for complete beginners.

Comprehensive data science program covering Python, SQL, machine learning, and data viz.

Master the art and science of crafting effective prompts for LLMs.

Introduction to NLP concepts, text processing, and working with language models.

Understand the technology behind ChatGPT, GPT-4, and other generative AI systems.

Complete data science pipeline from data acquisition to statistical inference and machine learning.

Master Pinecone, Weaviate, and Chroma for semantic search and RAG applications.

Master Stable Diffusion, ControlNet, and advanced image generation techniques.

Advanced NLP techniques using spaCy for entity recognition, parsing, and classification.

Master Claude-specific prompting techniques and best practices from Anthropic.

IBM's foundational AI specialization covering basics, ethics, and practical applications.

Explore fairness, bias, and ethical considerations in AI systems. Essential for all AI practitioners.

Understand vector embeddings and how vector databases power modern AI applications.

Learn to create images with AI. Understand prompts, settings, and creative workflows with Stable Diffusion.

Build intelligent document Q&A systems using LangChain and vector databases.

Build production-ready LLM applications with embeddings, search, and generation.

Fine-tune transformer models for custom tasks using the Hugging Face ecosystem.

Learn to build an AI from scratch with Python. Combine theory with practical implementations.

Master function calling APIs to give LLMs access to external tools and data.

Deep dive into PPO, SAC, TD3, and other state-of-the-art RL algorithms.

Master data manipulation, visualization, machine learning, and text analysis using Python.

Understand AI fundamentals and practical applications in everyday work from Google.

Interactive introduction to AI and data science fundamentals with hands-on exercises.

Learn Python, NumPy, pandas, and PyTorch. Build your first neural networks.

Learn computer vision basics using OpenCV. Build face detection, image filters, and object tracking.

Master YOLO, R-CNN, and modern segmentation architectures for real-world applications.

Build powerful automation workflows with n8n, the open-source Zapier alternative.

Learn computer vision, sensor fusion, and deep learning for autonomous vehicles.

Build RL agents for games and real-world applications using Python and OpenAI Gym.

Automate desktop and web tasks using Microsoft Power Automate Desktop.

Understand deep learning by implementing neural networks from first principles.

Advanced CV techniques including object detection, image segmentation, and interpretation.

Master autonomous agents, multi-agent systems, and complex reasoning patterns.

Experiment tracking, model registry, and deployment workflows with MLflow.

Practical techniques for writing better prompts to get the results you want from AI systems.

Learn the fundamentals of AI agents, how they perceive and act in environments, and build your first simple agent.

Understand neural networks from scratch with visual explanations and hands-on Python projects.

Deploy and manage ML models at scale using AWS services.

Introduction to machine learning operations: deployment, monitoring, and maintaining ML systems.

Hands-on introduction to reinforcement learning concepts with Python implementations and games.

From fine-tuning to deployment, master LLMs in production environments.

Learn to automate tasks using AI tools and Power Automate. No coding required.

Master AI art generation with Midjourney, Stable Diffusion, and ControlNet.

Explore autonomous agent design patterns and implement AutoGPT-style systems.

Quick overview of AI concepts, applications, and how to start your AI learning journey.

Hands-on computer vision projects using OpenCV and Python.

Create conversational AI agents using no-code tools and simple frameworks. Perfect for non-programmers.

Learn chain-of-thought, few-shot learning, and advanced prompting strategies.

Deploy and scale machine learning models using Kubernetes and TensorFlow Serving.

Learn robotic process automation with UiPath to automate repetitive business tasks.

Learn to build automated workflows using AI tools and APIs for business processes.

Essential statistics concepts for data science including hypothesis testing and regression.