Study Guide

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

Fail: Score less than 60% of maximum.
Pass: Score at least 60% of maximum.

Assessment scale

Pass/Fail

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.

Completion alternatives

N/A

Practical training and working life cooperation

N/A

International connections

N/A