Enrolment options
Data Science
Course modified date: 13 Dec 2020
- ExpertTrainer: Henrik Leopold
- Enrolled students: 51
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Course content
- Announcements
- Frequent Python Issues
- Syllabus
- Session 1: Introduction (Slides) - Updated
- Session 2: Python Basics for Data Science (Slides)
- Session 3: Python Basics for Data Science (Exercise sheet)
- Session 3: Python Basics for Data Science (Solution sheet)
- Session 4: Supervised Learning I (Slides - updated)
- Session 5: Supervised Learning I (Exercise sheet)
- Session 5: Supervised Learning I (Python solution - Exercise 1)
- Session 5: Supervised Learning I (Python solution - Exercise 2)
- Session 5: Boston Housing Data Set
- Session 5: Insurance Data Set
- Session 6: Supervised Learning II (Slides)
- Session 7: Supervised Learning II (Exercise sheet)
- Session 7: Supervised Learning II (Solution sheet - Part I)
- Session 7: Banknote Data Set
- Session 8: Supervised & Unsupervised Learning (Slides)
- Session 9: Supervised & Unsupervised Learning (Exercise sheet)
- Session 9: Diabetes data set
- Session 9: Python Solution (Decision tree)
- Session 9: Python Solution (Random forest)
- Session 9: Python Solution (SVM)
- Session 10: Text Mining (Slides)
- Session 11: Text Mining (Exercise sheet)
- Session 11: Tweet data file
- Session 11: Python skeleton
- Session 11: Process Mining (Slides)
- Assignment Guide
Instructors
- 33 courses632 students
Henrik Leopold