Seminars
Program
This is an indicative syllabus of the course! For the schedule applying to this semester, please visit course schedule web page 4iz565 or 4iz566.
# | Language | Topic | Note |
---|---|---|---|
1. | Introduction | Software | |
2. | Python | Intro to Python | |
3. | Python | Organizing code | |
4. | Python | Data structures | |
5. | Python | Data preprocessing | |
6. | Python | Sci-kit learn | |
7. | Python | Case study Python | Typically replaced by invited workshop |
8. | R | Intro to R | |
9. | R | Exploratory Data Analysis in R | |
10. | R | Training Machine Learning Models in R | |
11. | R | Model Evaluation in R | |
12. | R | Case Study R | Typically replaced by invited workshop |
13. | Spark | Scala, Spark |
This outline indicates order of seminars. For schedule, refer to course information for the current semester.
Self study and E-learning
Multiple seminars use DataCamp e-learning, which you can access from home.