Advance your Python skills and learn career development strategies to transition from academia to coding or data-related positions. This three-day course focuses on project-based learning with hands-on coding activities. Participants should have prior fundamental knowledge of Python coding, including the Python core, Numpy, and Matplotlib. By the end of the workshop, you will have a project to showcase on GitHub and insights on continuing your career development through networking and continuous skill-building.

• Introduction to Essential Python Skills (Day 1):

You will receive a brief introduction to essential Python programming skills and toolboxes needed for work outside academia, including:

• • Advanced data analysis and visualization with Pandas and Seaborn

  • Machine learning with Scikit-Learn and PyTorch

  • Exploring free and open data repositories

  • Creating interactive dashboards

  • BONUS: Web Frameworks

• Advancing Coding Skills with AI Tools (Day 2):

Practice enhancing your coding skills using AI tools, e.g., ChatGPT and Github Copilot, and other resources and delve into real-world problems that improve your coding proficiency.

• Good Coding Practice for Collaboration (Day 2):

Learn how to collaborate on larger projects by employing good coding practices, such as version control with Git and Github, and utilizing virtual environments.

• Portfolio and Showcase Project Development (Day 3):

Begin developing your portfolio with a showcase project that demonstrates your skills and knowledge. This hands-on project will be your steppingstone into the industry.

• Discussion on Future Steps (Day 3):

Engage in discussions on networking and further skill building to continue your career development journey.

• Project Presentation on GitHub (Day 3):

Present your showcase project on GitHub, receive constructive feedback from peers, and learn how to effectively communicate your work to potential employers.

The introduction to the Essential Python Skills together with using AI Tools is the basis for further learning and development on an individual basis.

Projects will be presented in small groups, fostering a collaborative environment, and providing valuable peer-to-peer feedback.

This workshop requires good knowledge of Python, as covered in the two
workshops "Fundamentals of Python" and "Python for Data Analysis and
Visualization”.

Trainer: Alexander Britz