A new era of autonomous AI agents has begun. The latest developments from Google I/O 2024 and OpenAI’s Spring Update confirm that all major companies are bullish on agents and that the future of AI will be ‘agentic’.
“Honestly, the path to AGI feels like a journey rather than a destination, but I think agent workflows could help us take a small step forward on this very long journey,” said Andrew Ng.
AI Agents will be ubiquitous, and the best part is that you can build them too!
Here are the top 10 free courses to help you build next-gen consumer and enterprise agent workflows that can enhance your productivity and help you solve complex problems.
Multi AI Agent Systems with crewAI
Recently, Andrew Ng unveiled this agentic short course, ‘Multi AI Agent Systems with crewAI’.
Available on DeepLearning.AI and built in collaboration with crewAI’s founder and CEO João Moura, it will teach you how to break down complex tasks into subtasks for specialised AI agents. Alongside this, it helps in discovering how to define roles, set expectations, and manage interactions among multiple AI agents.
The course also touches upon key agentic AI techniques like role-playing, tool use, memory, guardrails, and cross-agent collaboration. It also helps you build and manage your own multi-agent systems to tackle complex tasks effectively.
By the end of the course, you will also be equipped to design and deploy multi-agent architectures, driving significant progress in AI systems.
New agentic short course! Multi AI Agent Systems with crewAI, built with @crewAIInc’s founder and CEO @joaomdmoura. In this course, you’ll learn how to break down complex tasks into subtasks for multiple AI agents, each playing a specialized role, to execute.
For example, to… pic.twitter.com/qooJb8OSTm
— Andrew Ng (@AndrewYNg) May 15, 2024
Building RAG Agents with LLMs
This course by NVIDIA is perfect for developers looking to create advanced AI agents.
In this free course, you’ll learn to deploy scalable agent systems powered by LLMs and discover how LLMs excel in tool use, document interaction, and strategic planning.
You’ll also implement and evaluate RAG agents for answering research paper queries. Key topics include LLM inference interfaces, pipeline design with LangChain, Gradio, LangServe, dialogue management, and vector stores for RAG agents. By the end, you’ll have the tools to develop advanced LLM applications.
Build Agents with GPT-4o From Scratch
Learn how to build agents for multiple uses, including web search, finance, Hacker News, data analysis, and research with GPT-4o from scratch in just 11 minutes.
Agents with gpt-4o from scratch 🔥 in 11 minutes we’ll build:
🌎 Web Search Agent (2:40)
📈 Finance Agent (3:30)
🫡 Hackernews Agent (5:50)
📊 Data Analysis Agent (8:10)
🗒️ Research Agent (9:35)
code: pic.twitter.com/T3Hxxkd33n
— Ashpreet Bedi (@ashpreetbedi) May 15, 2024
Build AI Agents Smarter Than ChatGPT
The video delves into the concept of building AI agents that surpass current models like ChatGPT in functionality, focusing on their potential to complete extensive tasks quickly and autonomously.
It introduces Agency Swarm, a new framework designed for real-world business applications. It’s unique for its customisation capabilities and ease of use when building smarter AI agents.
It includes step-by-step instructions, and even those without programming skills can watch the course to learn how to adopt AI technology to stay ahead in a rapidly evolving field.
The Right Way to Build AI Agents With crewAI
This video delves into the best practices for building AI agents with crewAI, focusing on a fully local setup. It starts with an overview of crewAI’s capabilities and its approach to creating intelligent agents.
You’ll learn how to set up a local environment, define agent roles, and manage interactions between agents for various tasks. The tutorial includes practical coding demonstrations, showcasing how to implement these agents for diverse tasks. By the end, you’ll be equipped to develop efficient, scalable AI agents using crewAI’s platform, all while keeping your setup entirely local.
Create AI Agents From Scratch With Python
This video will teach you how to create AI agents from scratch using Python. It covers the fundamentals of building intelligent agents capable of decision-making and learning. You’ll learn about the key components of AI agents, including perception, action, and decision-making processes.
The tutorial then dives into coding examples, demonstrating how to implement various AI algorithms for searching, reinforcement learning, and decision trees. By the end, you’ll be equipped with the knowledge to build and deploy your own intelligent agents for a variety of applications.
Building Agentic RAG with LlamaIndex
Taught by Jerry Liu, CEO of LlamaIndex, this course ‘Building Agentic RAG with LlamaIndex’, is available on DeepLearning.AI. It will teach you to build a RAG agent with tool access for autonomous information retrieval, enabling it to answer complex questions using multi-step reasoning.
It will cover key aspects such as tool use, multi-step reasoning with tool use, and routing, where your agent will use decision-making to route requests to multiple tools. Additionally, you’ll also learn to debug and iteratively improve your agent.
I’m excited to kick off the first of our short courses focused on agents, starting with Building Agentic RAG with LlamaIndex, taught by @jerryjliu0, CEO of @llama_index.
This covers an important shift in RAG (retrieval augmented generation), in which rather than having the… pic.twitter.com/KwRvDEhENS
— Andrew Ng (@AndrewYNg) May 8, 2024
CampusX: Building AI Agents
In this course, you’ll learn how to create advanced AI agents using tools like crewAI, AutoGen, LangGraph, and AutoGPT. This course dives into AI development, teaching you to build intelligent agents capable of performing complex tasks and enhancing automation processes.
Key highlights include utilising these technologies for AI agent development, creating agents with advanced capabilities, and optimising their performance. You’ll explore how to implement AI agents to improve automation across various industries and discover techniques to optimise their performance, ensuring they operate efficiently and effectively.
Functions, Tools, and Agents with LangChain
This short course is presented in collaboration with LangChain and is available on DeepLearning.AI. It is taught by LangChain CEO Harrison Chase.
This course explores the capabilities of LLMs to call functions essential for managing structured data and form a foundation for LLM-based agents.
You’ll utilise LangChain’s expression language to develop applications that handle tagging, expression extraction, tool selection, and routing. Additionally, you’ll create a conversational agent showcasing all these features.
Can’t get enough agents? Check out the short course Functions, Tools, and Agents, taught by @LangChainAI CEO @hwchase17! 🦜🔗
This course covers the capabilities in LLMs to call functions, useful for handling structured data and a key building block for LLM-based agents.
You… pic.twitter.com/IyosgxfJFw
— DeepLearning.AI (@DeepLearningAI) May 10, 2024
The Complete Guide to Building AI Agents for Beginners
In this video, you’ll learn how to develop custom AI agent systems for companies of all sizes, from small firms to large corporations.
By the end of this video, users will be able to build their own fully functional social media marketing agency that will generate ad copy, create ad images with DALL-E 3, and reliably post them on Facebook.
