Google C8 (A2A)

Anthropic C4

Google C7 (Gemini CLI)

LandingAI C1

Build with Andrew

DeepLearning.AI

AI Python for Beginners

OpenAI

ChatGPT Prompt Engineering for Developers

Generative AI for Everyone

Stanford Online

Machine Learning Specialization

crewAI

Multi AI Agent Systems with crewAI

LangChain

LangChain for LLM Application Development

AI for Everyone

Connect agents across different frameworks and teams using A2A, the open protocol standardizing agent-to-agent communication.

Google Cloud

IBM Research

A2A: The Agent2Agent Protocol

Equip agents with expert on-demand knowledge to enable reliable coding, research, and data analysis workflows

Anthropic

Agent Skills with Anthropic

Build real-world applications from the command line using Gemini CLI, Google's open-source agentic coding assistant that coordinates local tools and cloud services to automate coding and creative workflows.

Gemini CLI

Gemini CLI: Code & Create with an Open-Source Agent

Build agentic systems to parse documents and extract information grounded in visual components like charts, tables, and forms.

LandingAI

Document AI: From OCR to Agentic Doc Extraction

If you've never written code before, this course is for you. In less than 30 minutes, you'll learn to describe an idea in words and let AI transform it into an app for you.

Turn proof-of-concept agent demos into production-ready systems using observability, evaluation, and deployment tools from Nvidia's NeMo Agent Toolkit.

Nvidia

Nvidia's NeMo Agent Toolkit: Making Agents Reliable

Build advanced retrieval systems that represent images with multiple vectors, enabling fine-grained matching between text queries and visual content for accurate multi-modal search.

Qdrant

Multi-Vector Image Retrieval

Build AI agents that write and execute code to accomplish tasks, running safely in sandboxed cloud environments that protect your systems from untrusted code.

Building Coding Agents with Tool Execution

Speed up and reduce the costs of your AI agents by implementing semantic caching that reuses responses based on meaning rather than exact text.

Redis

Semantic Caching for AI Agents

Build practical multi-agent systems that collaborate, use tools and memory, and scale reliably to production

CrewAI

Design, Develop, and Deploy Multi-Agent Systems with CrewAI

Learn to code with AI in Jupyter notebooks. Use Jupyter AI to generate code, get explanations, and analyze data.

Project Jupyter

Jupyter AI: AI Coding in Notebooks

Learn the core principles of building, optimizing, and deploying deep learning models using PyTorch.

PyTorch for Deep Learning Professional Certificate

Learn how to apply fine-tuning and reinforcement learning techniques to shape model behavior, improve reasoning, and make LLMs safer and more reliable. 

Fine-tuning and Reinforcement Learning for LLMs: Intro to Post-Training

Integrate data governance into your agent's workflow to ensure it handles data safely, securely, and accurately.

Databricks

Governing AI Agents

Build real-time voice AI agents, from simple to multi-agent podcast systems, using Google’s Agent Development Kit.

Google

Building Live Voice Agents with Google’s ADK

In this course taught by Andrew Ng, you'll build agentic AI systems that take action through iterative, multi-step workflows.

Agentic AI

Build, evaluate, and improve a multi-agent system that plans its steps, connects to data sources, and provides insights.

Snowflake

Building and Evaluating Data Agents

Build an LLM app that uses tools from the Box MCP server to discover Box files and extract text from them. Transform it into a multi-agent system that communicates using A2A.

Build AI Apps with MCP Servers: Working with Box Files

Construct a knowledge graph and use it to enable your AI agent to find and call the right APIs in the right order.

Knowledge Graphs for AI Agent API Discovery 

Build a multi-agent system that plans, designs, and constructs a knowledge graph.

All Courses