Data Analysis with Python, MOOC, Data Analysis with Python

Study the course materials, complete exercises, work on the peer-reviewed project, and do the exam in the MOOC online learning environment(Avautuu uuteen välilehteen) (the link will work as the course starts).

The course is

• a MOOC (Massive Open Online Course) that is completed online (fully distance learning) in the online learning environment. 
• There are no attendance requirements.
• You can study the contents at your own pace, except for project and exam deadlines.
• The MOOC environment contains the materials and instructions necessary for completing the course.

The course is completed in three stages:

1. Exercises
2. Peer-reviewed project work, and
3. Multiple-choice exam.

• the first part of the course.
• done in the online learning environment (TMC),
• automatically assessed.
• divided into 6 parts and you need to pass 80% of the exercises in each part to proceed to the next part.
• can be completed at your own pace.

• scheduled due to peer-review.
• multiple project topic options.
  
• solutions returned in Jupyter notebook format.

• You can take the exam once you have passed all parts of TMC exercises.
• a multiple-choice exam.
• Check the exam dates in the MOOC environment.

See Course unit description (below) for:

• Prerequisites
• Contents
• Learning outcomes
• Assessment practices and criteria