CF

Agentic AI Programming for Python Course

2h 38m 10s
English
Paid

Tired of using AI tools for programming that result in non-functional code and leave you endlessly cleaning up after artificial intelligence? There's a more efficient solution.

Course Overview

"Agentic AI Programming for Python" is designed to teach you how to collaborate with agentic artificial intelligence—more than just a chatbot or autocompletion tool. This course offers a smart assistant that can understand your code, run tests, format your projects, and create fully functional code autonomously under your guidance.

Instructor and Learning Tools

Under the expert guidance of Michael Kennedy, you'll learn how to use tools like Cursor and Claude to develop real-world production applications—from new projects to enhancing existing systems. The course delves into code structuring, testing, error management, and the seamless integration of AI into your development workflow.

Understanding Agentic AI

Discover how agentic AI stands apart from conventional chatbots and learn to collaborate with it as if it's a talented junior developer in your team—with clear guidelines, standards, and expectations.

Unique Course Features

  • Focus on agentic AI, not just chats - learn to engage with AI that comprehends your project context and can operate autonomously.
  • Real-world examples – analyze functions and services implemented in Talk Python and Python Bytes products.
  • Custom AI workflows – discover how to train models to write clean, structured code, complete with types, tests, and error handling.
  • Practice and control – master the rules, commands, and scenarios for Cursor and Claude, turning AI into a valuable team member.
  • Legacy project support – learn strategies to enhance old code without accruing technical debt.
  • Visual design integration – use screenshots and images for precise interface design communication.
  • Safe experimentation – leverage Git for fearless AI experimentation and easy rollback.
  • Cost and model optimization – learn to choose the right models and manage usage within your budget.

Course Outcomes

By the end of the course, you will be able to:

  • Differentiate agentic AI from chat and autocomplete tools.
  • Tailor Cursor and Claude to meet your specific project needs and standards.
  • Plan and develop complex features collaboratively with AI.
  • Create robust Python applications, ranging from CLI tools to web services and full production features.
  • Work effectively with context, documentation, and self-correcting AI agents.
  • Implement tests, configure logging, and use modern Python techniques like async/await and typing.
  • Utilize AI as an efficiency booster, avoiding chaos in your workflow.

Target Audience

Who this course is for:

  • Python developers who are frustrated with current chat AI tools.
  • Professional engineers aiming to boost productivity while maintaining code quality.
  • Team leads and architects looking to integrate AI tools into their workflow.
  • Indie developers and freelancers wanting faster implementation of ideas and MVPs.
  • Developers handling legacy projects and seeking to add features with minimal technical debt.
  • AI skeptics interested in discovering how well-configured agents can genuinely aid development.

Additional

https://github.com/talkpython/agentic-ai-for-python-course

About the Author: Talk Python Training

Talk Python Training thumbnail

Talk Python Training is the paid course platform of Michael Kennedy, the host of the long-running Talk Python To Me podcast — one of the most-listened-to podcasts in the Python ecosystem. The course platform extends Michael's interview-based knowledge of the field into structured video courses taught by Michael and a curated set of guest instructors.

The course catalog covers the full Python landscape: web development with Django, Flask, FastAPI, and the broader async-Python stack; data science and pandas; LLM / RAG application development; testing and CI/CD; deployment patterns; the data-engineering side of Python; and a long list of practical Python patterns aimed at working developers. Few platforms cover the language with this much breadth from inside the Python community itself.

The CourseFlix listing under this source carries over 18 Talk Python Training courses spanning that range. Material is paid; Talk Python Training runs on per-course pricing on the original platform. Courses are aimed at developers using Python as a serious primary language rather than as a scripting tool.

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#1: Welcome to the course
All Course Lessons (32)
#Lesson TitleDurationAccess
1
Welcome to the course Demo
01:38
2
What is agentic coding, and what is it not.
04:37
3
An Agentic AI example
08:44
4
Tools and editors
05:11
5
Git the source
00:30
6
Showcase 1- Bootstrap to Bulma CSS
05:39
7
Showcase 2- Python Bytes search
05:02
8
Showcase 3- Discord bot
02:08
9
Perfection is off the mark
01:43
10
From wizardry to engineering
01:02
11
Getting started in Cursor
07:28
12
Building and reviewing the plan
08:05
13
Your git needs to be top shelf
04:55
14
Monitoring ai credits
03:32
15
Phase 1 and more
10:36
16
Phase 2- async updates
06:00
17
Fixing a couple of bugs
04:40
18
Phase 3- Gittyup working great
07:10
19
Fixing output
06:18
20
Gittyup lives!
02:11
21
Why that worked well
01:24
22
Ai for new projects only.
01:58
23
Rise of the Program Manager (PM)
03:24
24
Short, temporary chats
00:52
25
Cursor rules
06:58
26
Read the docs
08:57
27
Introducing slash commands
01:27
28
Creating a custom slash command
07:30
29
Agents
11:06
30
Visual design introduction
13:55
31
Visual design cleanup
00:57
32
Thanks and Goodbye
02:33
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Frequently asked questions

What prerequisites are needed before taking this course?
To benefit fully from this course, you should have a basic understanding of Python programming and familiarity with version control systems like Git. The course will utilize tools such as Cursor and Claude, so prior experience with AI tools or environments is helpful but not mandatory. The course is designed to guide you through integrating AI into your development workflow, so having a background in software development will be advantageous.
What projects will I work on during the course?
Throughout the course, you'll engage with several real-world projects, including a Discord bot and a Python Bytes search feature. These projects are designed to help you understand how to implement agentic AI solutions in practical scenarios. You’ll learn to structure code, run tests, and manage errors with AI assistance, enhancing both new and existing applications.
Who is the target audience for this course?
The course is ideal for Python developers interested in leveraging artificial intelligence to optimize their coding practices. Whether you are a seasoned developer looking to integrate AI into your existing projects or a software engineer wanting to understand AI's role in development, this course offers valuable insights and skills.
How does this course differ from other AI programming courses?
Unlike courses focused solely on AI as a tool for generating code snippets or chat interactions, this course emphasizes agentic AI. You'll learn to interact with AI as if it were a junior developer, capable of understanding project contexts and operating autonomously. The course provides a comprehensive look at integrating AI into your workflow, from structuring code to running tests and managing errors.
What platforms or tools will be used in this course?
The course utilizes tools such as Cursor and Claude to facilitate the integration of AI into your development processes. These tools are essential for developing real-world production applications and understanding how AI can autonomously contribute to projects. You’ll also work with Git for version control and explore various AI workflows.
What topics are not covered in this course?
This course does not cover basic Python programming or general AI theory. It assumes you have a foundational understanding of Python and focuses specifically on the practical application of agentic AI in software development. It also does not delve into AI model training or deep learning, as the focus is on using AI as a collaborative tool rather than developing AI models from scratch.
How much time should I expect to commit to this course?
The course consists of 32 lessons, and while the total runtime is not specified, you should plan to dedicate time to work through these lessons and engage with the practical projects. The time commitment will vary depending on your familiarity with the tools and concepts introduced, but expect to spend a significant amount of time practicing and applying what you learn to fully grasp the course material.