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Advanced Python Workshops
November 9 @ 5:30 pm - 7:30 pm
The LINC-STEM committee is proud to present the follow-up Advanced Python Workshops course!
Computer programming has become a highly sought-after skill that affects every aspect of the financial landscape. That is why LINC-STEM is eager to equip students from all disciplines (Science, Engineering, Economics, Finance, Business, Mathematics, etc.) with this skill to prepare for the changing industry.
This 5-week long course is free and open to every student attending Lund University regardless of faculty and is ideal for people who have completed our beginner course or have some programming experience. The course will focus on different machine learning analyses methods such as regression analysis, clustering, and neural networks, which will be brought together in a final project consisting of building a data dashboard.
We will provide you with 5 weekly workshops, reading material, and a certificate of completion for those who complete the final project.
The workshops will be hosted every Tuesday and Wednesday between 17.30-19.30 starting on the 8th of November and ending on the 8th of December. When you sign up you choose the day that works best for you so we can split the participants between Tuesday and Wednesday to keep classes smaller and interactive. See below for a detailed schedule.
**In case you think you will be missing more than a single workshop, please do not sign up for this semester as spots are limited. If you know you will miss one, please notify STEM@linclund.com at least 24 hours in advance before that specific workshop. **
**Sign up by Friday the 5th of November, limited to 50 spots:**
*Note that all workshops have an academic quarter.
Tuesday, Wednesday 9, 10 November 17.30-19.30: Setting up a Web Application & APIs
Tuesday, Wednesday 16, 17 November 17.30-19.30: Linear Regression & Plotly
Tuesday, Wednesday 23, 24 November 17.30-19.30: Logistic Regression
Tuesday, Wednesday 30 November, 1 December 17.30-19.30: Clustering with K-means
Tuesday, Wednesday 7, 8 December 17.30-19.30: Introduction to Neural Networks
Sunday 12 December: Final Project Deadline