Big Data and Data Analysis (5 cr)

Objectives (course unit)

After completing this course student understands basic Big Data concepts, Big Data manipulation and analysis techniques.

Content (course unit)

Course covers data science concepts, Big Data basics and techniques and/or programming tools for handling Big Data all the way from source to end user visualizations.

Location and time

During year 2017 in A3-20 (TAMK premises).

Evaluation methods and criteria

Both part are graded with a grade between 0 - 5 points. The course grade is the average of these two.
The reasoning behind an individual grade will be published to tabula. For example requirements are set for a lab work and the grade depends on how these requirements are met.

Assessment scale

0-5

Teaching methods

Lectures, smaller programming projects as group work.

Learning materials

Lecturing material and other used material will be published to this courses tabula page and informed to the students.

Student workload

Aproximately 135 hours for the students. This includes 24 hours lectures.

Content scheduling

The content of the course is divided to two parts:
- 1. part handles common Big Data principles and MapReduce paradigm and we will make a lab work of MapReduce in this part. The part contains three lecturer sessions.
- 2. part handles ... (Pekka write this!) ...

Practical training and working life cooperation

We will handle IoT and Big Data related things in the course that are applied in many local SW companies in Pirkanmaa area.

Assessment criteria - fail (0) (Not in use, Look at the Assessment criteria above)

Has not done assigned duties or participated in class. Has not proven his/her competence.

Assessment criteria - satisfactory (1-2) (Not in use, Look at the Assessment criteria above)

Knows course topics and has capabilities to demonstrate this. Course assignments do not contain considerable flaws and are mainly given on time. Passable group function skills.

Assessment criteria - good (3-4) (Not in use, Look at the Assessment criteria above)

Knows how to apply course topics in real life. Course assignments are mainly done according to specifications and returned on time. Good group working skills.

Assessment criteria - excellent (5) (Not in use, Look at the Assessment criteria above)

Extensive capabilities to utilize course topics in real life and capabilities to demonstrate these traits. Course assignments are done according to specifications and returned on time. Proactive group working skills.

Assessment criteria - pass/fail (Not in use, Look at the Assessment criteria above)

Final grade will be between 0 - 5 according to TAMKs grading principles.