|Website:||website containing additional information|
|Period:||period 1 (week 36 through 45, i.e., 3-9-2018 through 9-11-2018; retake week 1)|
|Participants:||up till now 120 subscriptions|
|Schedule:||Official schedule representation can be found in Osiris|
|Contents:||At the end of this course, you will be able to:
The following study materials are required readings for the written exams, next to all lecture slides:
In addition, the following two materials are considered to be the course foundation, and are therefore considered to be required background reading:
Finally, various literature is recommended troughout the course, including but not limited to:
|Course form:||There will be 6 contact hours per week. One workshop 2-hour slot to practice with big data tools (Hadoop and Spark with R and Python within an Azure environment), and two lecture 2-hour slots for both regular and guest lectures, to respectively investigate big data technologies and their societal impact.
The following assignments are among the key parts of the course:
|Exam form:||The graded deliverables generate the final course grade as follows:
[A] Book review
[B] Mid-term exam
[C] End-term exam
[D] Optional bonus for extraordinary participation/performance
Grade = [A]*0.10 + [B]*0.40 + [C]*0.50 + [D]
|Minimum effort to qualify for 2nd chance exam:|
|Description:||This is the introductory course for the Applied Data Science profile, the Applied Data Science postgraduate MSc programme, and the Business Informatics (MBI) programme. As such, it's primary objective is to inspire and introduce you to the emerging domain of Applied Data Science from a Big Data Technologies perspective.
Communication takes place privately on MS Teams in the infomdss group.
NB: Self-study programming support is supported for free, thanks to the DataCamp for the Classroom intuitive learning platform.