All Courses

Grow your AI career with foundational specializations and skill-specific short courses taught by leaders in the field.

AI Python for Beginners

Learn Python programming with AI assistance. Gain skills writing, testing, and debugging code efficiently, and create real-world AI applications.

DeepLearning.AI

Short Course

ChatGPT Prompt Engineering for Developers

Learn the fundamentals of prompt engineering for ChatGPT. Learn effective prompting, and how to use LLMs for summarizing, inferring, transforming, and expanding.

OpenAI

Course

Generative AI for Everyone

Learn how to use generative AI's capabilities & limitations. Get an overview of real-world examples, and impact on business & society for effective strategies.

DeepLearning.AI

Specialization

Machine Learning Specialization

Learn foundational AI concepts through an intuitive visual approach, then learn the code needed to implement the algorithms and math for ML.

Stanford Online

Short Course

Multi AI Agent Systems with crewAI

Automate business workflows with multi-AI agent systems. Exceed the performance of prompting a single LLM by designing and prompting a team of AI agents through natural language.

crewAI

Short Course

LangChain for LLM Application Development

Use the powerful and extensible LangChain framework, using prompts, parsing, memory, chains, question answering, and agents.

LangChain

Course

AI for Everyone

Learn about AI technologies and how to use them. Examine AI's societal impact, and learn to navigate this technological shift.

DeepLearning.AI

Courses

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Course

Machine Learning in Production

Design an ML production system: scoping, data, modeling, deployment. Prototype development, deployment & continuous improvement.

DeepLearning.AI

Course

Generative AI for Everyone

Learn how to use generative AI's capabilities & limitations. Get an overview of real-world examples, and impact on business & society for effective strategies.

DeepLearning.AI

Course

Generative AI with LLMs

Understand the generative AI lifecycle. Describe transformer architecture powering LLMs. Apply training/tuning/inference methods. Hear from researchers on generative AI challenges/opportunities.