Learn to build effective Agentic AI systems with Andrew Ng

Building effective agentic AI systems is one of the most valuable skills in AI today. In this course, I share best practices for doing so and you come away

today. In this course, I share best practices for doing so and you come away with a systematic understanding of how to build agentic systems. I come with the term agentic AI to describe a growing category of AI projects not

realizing that marketers would get a hold of that term and slap us a sticker on everything in site. Even though the hype on agentic AI has grown really rapidly, the reality of agentic systems being created and deployed has grown

rapidly as well. Unlike a single LM call, they just directly generates a response. Agentic AI systems can execute multiple LM driven steps. These steps

response. Agentic AI systems can execute multiple LM driven steps. These steps

can use tools, they can reason, they can iterate over the work to complete complex [music] tasks. In this course you learn how to build agentic workflows using raw Python without hiding all the steps in some framework so that you see

how each step actually works. You learn to take a complex application and decompose it into a sequence of tasks that you can then implement [music] as an agentic workflow. You also learn how to implement the four key design

patterns for agentic workflows. Having worked on many agentic systems with many teams, I found that the single biggest predictor for whether the team executes well lies in his ability to drive a disciplined error analysis process. That

is to put in place evaluations or evals so that given a complex agented workflow, you can efficiently hone in on what components to focus attention on improving. This way, you aren't just guessing how to spend time productively.

improving. This way, you aren't just guessing how to spend time productively.

you let the eval data guide you. In this course, I'll also show you how to drive this [music] process and this will put you significantly ahead of your game compared to the vast majority of teams building aicles today. This course is

taught in a vendor neutral way in raw Python and the emphasis is on teaching you the core concepts that you can then implement using any of the popular agentic AI development frameworks or using no framework. This long form

course is currently available only on the deep learning.ai website. I hope you sign up for [music] this course and when you've completed it, you know how to build aic AI systems which is one of the most in demand skills on the job market

today and that will also let you build a lot of cool applications.