TU Delft
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2017/2018 Universiteitsdienst MOOCs for Credits
Data Analysis: Take it to the MAX (MOOC)
Responsible Instructor
Name E-mail
Dr.ir. F.F.J. Hermans    F.F.J.Hermans@tudelft.nl
Contact Hours / Week x/x/x/x
NA (self-paced MOOC). Required study period: March-May 2018
Education Period
Different, to be announced
Start Education
Exam Period
Different, to be announced
Course Language
Expected prior knowledge
Basic high school math. The course is intended for non-computer science students that want to learn about programming.
Course Contents
Programming and data analysis are more important today than ever before and as a student, you are bound to deal with it at one point: in a course, for a project, for your graduation project or when you start your career.
But how do you handle your data? With Excel, with Python, with MatLab? How to quickly build a program that exactly solves your problem? The one library you thought could help does not compile and the code form this paper does not cover your edge case. Help!

Using video lectures and hands-on exercises, we will teach you techniques and best practices that will boost your data analysis skills.
We will take a deep dive into data analysis with spreadsheets: PivotTables, VLOOKUPS, Named ranges, what-if analyses, making great graphs - all those will be covered in the first weeks of the course. After, we will investigate the quality of the spreadsheet model, and especially how to make sure your spreadsheet remains error-free and robust.
Finally, once we have mastered spreadsheets, we will demonstrate other ways to store and analyze data. We will also look into how Python, a programming language, can help us with analyzing and manipulating data in spreadsheets.
Study Goals
•Students can perform basic data analysis in Excel, including the use of:
oArray formulas
oPivot Tables
oLookup formulas
oGraph Databases
•Students know the pros and cons of all above methods and can reason about when to use which one
•Students know how to document, structure and test their spreadsheets
Education Method
Self-paced MOOC,required study period: March-May 2018.
Note: 1 ECTS equals 28 hours
Literature and Study Materials
All study material is available through the EdX site.
Making a video (30%)
Final Assignment (70%)
In addition you will need to score 60% of the MOOC Data analysis to the MAX()
All assignment requirements will be detailed on edX.
Enrolment / Application
This course is open for a limited number of students from TU Delft and partner universities who are participating in the Credits for MOOCs project.
TU Delft students: For more information and the application procedure see: http://www.tudelft.nl/creditsformoocs
Other interested students: Please contact your home university for more information. TU Delft will not accept applications from individual students.
Special Information
To enrich the portfolio of students the TU Delft and other leading universities started the Credits for MOOCs project. Students should be able to benefit from the available MOOCs offered by experts in the field by incorporating these MOOCs in their study programme.
TU Delft now offers ca 10 MOOCS in this project.
This course covers the same material as IN4400 Programming and Data Science for the 99% (5EC). However, IN4400 has classes (discussions/presentations) whereas this course UD9004 is completely online. Topics and the assignments are the same for both courses, as is the number of ECTS. TU Delft students are eligible for both courses, students from partner universities can only opt for UD9004.