Live streaming and recordings of the lectures
Physical and virtual attendance to lectures and exercise sessions
The capacity of classrooms has been reduced this year due to the covid-19 pandemic. As a result, students will need to take turns participating in lectures and exercise sessions physically and virtually. To find out which weeks you should attend physically, and which weeks you should attend virtually, see the info provided in the welcome page of the course on CampusNet.
The lectures are backed reading material from various sources. These should be seen at suggestions. There's a huge community behind the tools we are working with in this course. Suggested reading materials can be found in the Weekplan below.
Lecture slides and exercise
Lecture slides and exercises are made available as Colab notebooks. See the Weekplan below.
Further information and materials will be posted soon. In the first 4 weeks, we'll introduce the basic computational tools for data science with Python. In weeks 5-12, we will cover more advanced topics such as streaming, parallel computation and relational databases.
|1: Sept 1||Self-study||Self-study||A Whirlwind Tour of Python, learnpython.org|
|2: Sept 8||Colab notebook||Colab notebook||Python Data Science Handbook, Ch. 2|
|3: Sept 15||Colab notebook||Colab notebook||Python Data Science Handbook, Ch. 3, Kaggle Pandas tutorials, Python for Data Analysis Book, from Ch. 5|
|4: Sept 22||Colab notebook||Colab notebook||Python Data Science Handbook, Ch. 4-5.|
|5: Sept 29||
|6: Oct 6|
|7: Oct 13||Holiday week|
|8: Oct 20|
|9: Oct 27|
|10: Nov 3|
|Project||Released||Due||Problem file||Contribution to final grade|
|Project 1||Tuesday, September 29||Monday, November 2, 20:00||37.5 %|
|Project 2||Tuesday, November 3||Monday, November 30, 20:00||37.5 %|
|Project 3||Tuesday, December 1||Sunday, December 23, 20:00||25 %|
Can I skip lectures/classes due to conflicting courses, travelling, ...? The is no requirement for attendance, but we recommend attending for support and coaching.