Data Analysis and Big Data as Business Development Tools (3 cr)
Code: NN00HC13-3002
General information
Enrolment period
20.02.2025 - 15.05.2025
Timing
01.04.2025 - 31.07.2025
Credits
3 op
Virtual portion
3 op
Mode of delivery
Online learning
Teaching languages
- Finnish
Seats
0 - 80
Teachers
- Harri Saarinen
Person in charge
Harri Saarinen
Groups
-
AVOINAMK
-
VAPAA
Objectives (course unit)
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 (course unit)
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
Prerequisites (course unit)
Basics of programming
Assessment criteria, pass/fail (course unit)
Fail: The student does not know enough statistical data analysis, Python programming and big data processing in relation to the performance requirements.
Pass: The student knows enough statistical data analysis, Python programming and big data processing in relation to the performance requirements and understands their significance in business and its development.
Location and time
Summer implementation, in network.
Exam schedules
N/A
Assessment 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
Assessment scale
0-5
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 two webinars.
Learning materials
All in Moodle platform.
Student workload
80 h of student's work.
Content scheduling
Self-paced learning
Completion alternatives
N/A
Practical training and working life cooperation
N/A
International connections
N/A