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     AI assisted Python projects

Summary

This AI-Enhanced Python workshop introduces a modern approach to learning Python programming and teaches:

  • Python fundamentals including variables, data types, control flow, and functions with AI-enhanced learning methods
  • how to effectively use AI tools like ChatGPT and Claude for solving programming challenges
  • how to teach yourself programming using AI assistance, setting you up for continued learning
 

Target groups

The course has two distinct target audiences:

  • Beginners: Scientists and researchers new to programming who want to start their Python journey with modern AI-assisted learning methods. Participants should be prepared to invest significant time after the course for self-study, applying the AI-assisted learning techniques taught in the workshop.
  • Advanced Programmers: When booked for a group of researchers, the course can be adapted for experienced programmers, focusing purely on AI-assisted development while skipping Python basics. Advanced participants get access to all on-demand course materials for self-study of any fundamentals if needed.

Course structure

The course combines pre-recorded lecture videos, live Zoom sessions with hands-on project work. It contains:

  • Initial 2-hour Zoom session covering:
    • Development environments and AI tool setup
    • Python fundamentals
    • AI-assisted learning techniques
    • Introduction to project work
  • 1-2 weeks of independent project work applying these techniques
  • Follow-up 2-hour Zoom session for project discussion and advanced concepts
  • Pre-recorded comprehensive video lectures for additional support
Content

Session 1: Foundations and AI Tools

  1. Development Environment Setup
    • IDEs and Jupyter Notebooks
    • AI Assistant Integration (ChatGPT, Claude, Anaconda Assistant)
  2. Python Fundamentals with AI Support
    • Variables and data types (strings, integers, floats, booleans)
    • Control flow (if-statements, loops)
    • Functions and basic programming concepts
    • Using AI to explain code and concepts
  3. AI-Assisted Learning Techniques
    • Effective prompting
    • Problem-solving strategies
    • Code improvement with AI
  4. Project Introduction

Project Phase

  • Hands-on programming projects using AI assistance
  • Self-paced learning with provided video materials
  • Practical application of AI-assisted problem-solving

Session 2: Project Discussion and Advanced Topics

  1. Project Presentations and Discussion
  2. Common Challenges and Solutions
  3. Advanced AI Tool Usage
  4. Strategies for Continued Learning

FAQ (Frequently Asked Questions

Prior experience isn’t required but can be advantageous; those familiar with MATLAB tend to find the course easier.

The lecture video for the first module is an hour and 40 minutes long. During the project phase you need to plan at least an entire work day (8 hours) to familiarize yourself with AI-assisted coding and to get your project to a good result. You can obviously spend a lot more time on it, especially if you work on your own data/project, that directly benefits your work.

The Zoom meeting will be maximum 2 hours each. In total that adds up to roughly 14 hours.

Certainly. In the tutorials, we’ll start by going over the lecture and the projects. Instead of choosing one of the example projects you can work on your own data.

If you engage in the tutorials and present your project, you’ll earn a certificate upon course completion.

If you go for self-study with the on-demand course but still want a certificate, you can schedule a one-on-one Zoom call to check your understanding. Passing the assessment grants you the certificate. Get in touch with us if you’re interested.

Course overview

Since 2023 the specialization courses Good Programming Practice in Python and Advanced Plotting in Python are integrated into Python for Scientists and Python for Biologists

Module / Course

Programming projects with AI

Syntax, PEP8, Keyboard Shortcuts, Numpy

Advanced Numpy, File IO, Pandas, AI

Advanced Matplotlib & Interactive Plots

GIT, String Formatting, Video Creation, Code structure

Interpolation, Fitting, Filtering, Data analysis

File Creation, Generators, Parallelization, Sympy

Biopython: DNA sequencing & visualization, BLAST

Scikit Image: Image analysis & processing

✔ meaning the topics are both covered in the lecture and the tutorials
^ meaning participants have access to the lecture materials but we will pick 1 or 2 topics to discuss in the tutorials

On-demand courses

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Contact

Are you interested or have any questions about the Python for Scientists & Engineers course? Reach out any time!

+49 156 78448154

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