How to Generate Code Faster and Tackle Coding Challenges using AI & LLMs

How to Generate Code Faster and Tackle Coding Challenges using AI & LLMs


In this short and focused training, you will learn how Large Language Models (LLMs) such as Chat GPT, can help you generate code faster and in a more productive way using Python.

You will also explore how LLMs can improve how you tackle coding challenges, make your code documentation clearer and provide constructive feedback on code reviews.

The course will include examples and practical coding exercises using Google Colab

Who it is for

  • Coders, developers
  • Software & applications developers
  • Software architects
  • Team leader, IT project manager

What you will learn

  • Insights into the architecture, technology, and historical development of ChatGPT and open source LLMs
  • Code generation: how to generate code and tackle coding challenges.
  • Code debugging: efficient techniques with LLMs expert.
  • Code documentation: how to improve your code documentation.
  • Code reviews: learn how to conduct code reviews and provide valuable feedback.
  • Project Management: An introduction to Master project planning, task management and collaboration with ChatGPT.

Meet your faculty

Alexandre Rouxel

Data Scientist

Alexandre is a Data Scientist and AI project Engineer at the EBU Technology and Innovation department. He holds a Master's Degree in Statistical Signal Processing as well as Data Science. He has an extensive background in Research and Development acquired within Nasdaq listed high tech companies. During his 18 years of experience, he contributed to research projects and innovative product design involving machine learning and signal processing. He has 12 patents granted and four publications in conferences. He is a data enthusiast, passionate about algorithms designed to extract meaningful information from a large dataset.