English
Intermediate studies
Degree Programme in Computer Sciences
School of Information Sciences
Learning outcomes
After completing the course the student is expected to
- know typical characteristics and common applications of big data
- know the basics of distributed file systems, databases and computing
- have gained practical data processing skills with the MapReduce framework / Apache Hadoop.
General description
The course will require, in the order of importance (most important first), the following:
- Satisfactory programming skills (including object-oriented programming). E.g. the introductory Java-based programming courses TIEP1 High Level Programming I and TIEP5 High Level Programming II.
- Basics of databases. E.g. the course TIEP3 Databases.
- Basics of statistics. E.g. the course MTTP1 Introduction to Statistics.
Enrolment for University Studies
Priority is given to 1) the students in the Master's Degree Programme in Computational Big Data Analytics and 2) students in the degree programmes in Computer Sciences and Mathematics and Statistics.
Enrolment time has expired
Teachers
Heikki Hyyrö, Teacher responsible
heikki.hyyro[ät]tuni.fi
Homepage URL
Teaching
29-Aug-2016
–
20-Dec-2016
Lectures
Wed 31-Aug-2016 - 19-Oct-2016 weekly at 14-16, Main Building LSA3
Exercises
Wed 7-Sep-2016 - 21-Sep-2016 weekly at 16-18, Pinni B0016
Wed 5-Oct-2016 - 26-Oct-2016 weekly at 16-18, Pinni B0016
Exceptions:
26-Oct-2016
at 16
–18
, Pinni B0039
Thu 6-Oct-2016 - 27-Oct-2016 weekly at 14-16, Pinni B0016
Fri 7-Oct-2016 - 28-Oct-2016 weekly, Pinni B0016