Course Information
Registration period
Year-round Recruitment
Course Level
Study Mode
Duration
9 Hour(s) 15 Minute(s)
Language
English
Taught by
Mohsen Hassan, Ilyass Tabiai
Certificate
- Available
- *The delivery and distribution of the certificate are subject to the policies and arrangements of the course provider.
Rating
Course Overview
AutoGen, ChatGPT API, Streamlit, Google Cloud, build and deploy LLM AI Agents based apps (locally or at scale)
In this course you'll learn about this new way of using LLM Agents: deploying multiple agents to work together as teams to accomplish more complex tasks for you!
Everything is taught step by step and the course is fully practical with multiple examples and one complete AI Agents-based App that we build together.
One of the things we use to accomplish this is ChatGPT's API so we can use ChatGPT through Python.
We also use AutoGen to enable our Agents to work together and communicate with one another (to accomplish tasks with no human intervention).
We also provide a few optional sections. One of these sections teaches to have a front-end, using Streamlit, to more easily interact with your AI Agents.
Another optional section is for those who want to run AI Agents at scale! Here we show you how to deploy your LLM Agents on Google Cloud, so anyone can use your product.
Lastly, one more optional section is available showing how to set up a payment system/subscription model using Stripe for those who want to monetize their AI Agents-based App!
Everything is explained simply and in a step-by-step approach. All code shown in the course is also provided.
Please not that the OpenAI API is not free, you will need to fund your OpenAI developer account with about $5-10 to follow through with the class and build your own app. We clearly show and explain how to do this and minimize your OpenAI costs during this class.
Course Content
- 9 section(s)
- 49 lecture(s)
- Section 1 Intro to LLM Agents
- Section 2 LLM Agents Implementation (with OpenAI's ChatGPT)
- Section 3 [Optional] Running Open Source LLMs Locally (Free) instead of OpenAI's ChatGPT
- Section 4 LLM Agents Implementation Continued
- Section 5 AutoGen Chat Structures
- Section 6 Application: Using Agents for Stock Analysis
- Section 7 Deploy Your AI Agent App
- Section 8 [Optional] Add Subscription - Payments to your App
- Section 9 Bonus Lecture
What You’ll Learn
- Build teams of AI Agents that can achieve complex tasks
- Build LLM Agents based Apps
- Use ChatGPT's API
- Use AutoGen to enable AI Agents to communicate with one another
- Build a front-end to communicate with your team of AI Agents (optional)
- Run a AI Agent App at scale using Google Cloud (optional)
- Set up a payment system to charge users to use your AI Agents based App (optional)
Skills covered in this course
Reviews
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FFernandez Recio Miguel Rogelio
I have gained substantial knowledge about LLM agents, and after completing some practical exercises, I find their implementation to be relatively straightforward. Prior to this course, I believed that artificial intelligence was highly complex; however, I now understand that it primarily revolves around communication between agents, leveraging logic and tools to build effective solutions.
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PPaulo Rosa
I like the fact theres a section for a payment processing which is interesting. however, it wasnt clear to me that st-paywall did all the magic of using the secrets in the .txt and working together with streamlit automatically, all in just a few lines of code
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SSamir Tamhane
I liked the hands-on experience and the pace at which the course was designed.
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BBrijesh Shah
This is really excellent for a beginner with no coding experience and no knowlege of GenAI. Trainer is really very very excellent in explaining the concepts and help to code in slow manner so that others have chance to understand and try at the same time
