Generative AI for Python Developers - Shaun Wassell is an online course designed to help you integrate cutting-edge tools like ChatGPT and GitHub Copilot into your coding workflow. This course covers various applications, whether just getting started with scripting or diving into web development and data analysis. The focus is on practical exercises and best practices, ensuring you understand the theory and how to apply these tools effectively in your projects.
Throughout the course, you'll learn how to enhance your coding process using Generative AI technologies. This includes mastering prompt engineering techniques for scripting and data science and using AI to improve web development and data analysis. You'll also explore AI-assisted Test-Driven Development (TDD) and documentation methods, which can significantly boost your code quality and efficiency.
This course, "Generative AI for Python Developers - Shaun Wassell," is perfect for Python developers looking to stay ahead in the fast-evolving field of AI-assisted software development. By the end of the course, you'll have the skills to seamlessly integrate AI tools into your projects, enhancing your scripting, web development, and overall coding practices. All you need is a basic understanding of Python programming to get started.
Generative AI for Python Developers - Shaun Wassell Table of Contents:
- Introduction
- Generative AI for Python Developers: Introduction
- Lesson 1: Generative AI Options for Python Development
- Learning objectives
- 1.1 Set up and work with ChatGPT
- 1.2 Write basic Python code using ChatGPT
- 1.3 Get started with Github Copilot
- 1.4 Learn the basics of navigating Github Copilot
- Lesson 2: Writing Basic Scripts with GenAI
- Learning objectives
- 2.1 Write basic automation scripts with ChatGPT
- 2.2 Write basic automation scripts with Github Copilot
- 2.3 Learn prompt-engineering best practices for writing scripts
- 2.4 Exercise: Write a web-scraping script
- 2.5 Exercise: Load and modify a CSV file
- Lesson 3: Using GenAI with Jupyter, Pandas, and More
- Learning objectives
- 3.1 Learn the basics of using Generative AI alongside Jupyter
- 3.2 Use AI to assist with data visualization
- 3.3 Use AI to assist with data analysis
- 3.4 Learn prompt-engineering best practices for data science
- 3.5 Exercise: Display data on a graph
- 3.6 Exercise: Clean some data
- Lesson 4: Improving Python Web-Development with GenAI
- Learning objectives
- 4.1 Build simple Python servers with Generative AI
- 4.2 Use Generative AI to create templates
- 4.3 Learn prompt-engineering best practices for web development
- 4.4 Exercise: Create a REST API
- 4.5 Exercise: Create a server for blog articles
- Lesson 5: Using GenAI for Test-Driven Development and Documentation
- Learning objectives
- 5.1 Write basic tests using Generative AI
- 5.2 Learn prompt-engineering best practices for Test-Driven Development
- 5.3 Use Generative AI to help with writing documentation
- 5.4 Exercise: Unit test basic functions
- 5.5 Exercise: Integration test API calls
- Summary
- Generative AI for Python Developers: Summary
Who is this course for?
- Python developers looking to integrate Generative AI tools into their workflow.
- Developers aiming to enhance their scripting and web development skills with AI technologies.
- Programmers interested in adopting AI-assisted Test-Driven Development and documentation methods.
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