Data Analysis and Big Data as Business Development Tools (3cr)
Code: C-02630-NN00HC13-3003
General information
- Enrollment
- 20.02.2026 - 30.06.2026
- Registration for the implementation has begun.
- Timing
- 01.04.2026 - 31.08.2026
- Implementation is running.
- Number of ECTS credits allocated
- 3 cr
- Institution
- Tampere University of Applied Sciences, TAMK Pääkampus
- Teaching languages
- Finnish
- Seats
- 0 - 40
- Course
- C-02630-NN00HC13
Unfortunately, no reservations were found for the realization Data Analysis and Big Data as Business Development Tools C-02630-NN00HC13-3003. It's possible that the reservations have not yet been published or that the realization is intended to be completed independently.
Objective
After completing the course, the student understands the importance of data and its analysis for business. The course introduces students to the most important statistical methods using the Python programming language and introduces them to Big Data as a concept, the internet data sources that produce it, and its analysis in the form of visualization and text analysis.
Content
1. Data analytics, business analytics, statistics, statistics, probability, risk 2. Application of statistical methods and production of graphs in the Python programming language 3. Familiarity with Big Data and the sources of information that produce it 4. Familiarity with Big Data analysis; visualization, text analysis
Content scheduling
Self-paced learning
Location and time
Summer implementation, in network
Materials
All in Moodle platform.
Teaching methods
Virtual implementation on the TUNI Moodle learning platform, https://moodle.tuni.fi.
Includes learning material, program examples, analysis examples, exercises, instructional videos, and negotiable tutoring sessions on Zoom channel. The channel is to be found on Moodle platform, at the beginning.
Moodle course key: Data_is_our_oil
Employer connections
N/A
Exam schedules
N/A
International connections
N/A
Completion alternatives
N/A
Student workload
80 h of student's work.
Qualifications
Basics of programming
Evaluation methods and criteria
Grounds for grading:
0: Points under 50,0 % out of maximum
1: Points 50,0-59,9 % out of maximum
2: Points 60,0-69,9 % out of maximum
3: Points 70,0-79,9 % out of maximum
4: Points 80,0-89,9 % out of maximum
5: Points 90,0-100,0 % out of maximum
Evaluation scale
0-5