Data Analytics (5 cr)

Code: RDI2HM102-3024

Basic information of implementation


Enrollment
02.01.2024 - 12.01.2024
Enrolment for the implementation has ended.
Timing
15.01.2024 - 15.03.2024
Implementation has ended.
ECTS Credits
5 cr
Campus
Pasila Campus
Teaching languages
English
Seats
31 - 100
Degree programmes
ATBUM Degree Programme in Aviation and Tourism Business
LEBUM Degree Programme in Leading Business Transformation
BUTEM Degree Programme in Business Technologies
HOSBUM Degree Programme in Tourism and Hospitality Business
Teachers
Veijo Vänttinen
Groups
MALEAE
Leadership and Human Resource Management, Masters, Pasila
MAENTE
Entrepreneurial Business Management, Masters, Pasila
MAEXPE
Experience Economy and Designing Services, Masters, Pasila
VIRTUAL
Virtual implementation
INSTRUCTED
Instructed virtual implementation
Course
RDI2HM102

Evaluation scale

H-5

Schedule

15.1 - 15.3.2024

Implementation methods, demonstration and Work&Study

Depending on the implementation, learning takes place in contact lessons, as independent studies, teamwork and online-studies. Implementations can include literature, assignments, R&D co-operation and company projects. The course includes the assessment of one’s own learning.

Recognition of prior learning (RPL)
If students have acquired the required competence in previous work tasks, recreational activities or on another course, they can show their competence via a demonstration. The demonstration must be agreed with the course teacher. More information and instructions for recognising and validating prior learning (RPL) are available at https://www.haaga-helia.fi/en/recognition-learning Look at "Instructions to students (master)"

Intro

In modern organizations, information is a crucial tool for management. Data analytics is a means of refining information for business needs. The objective of this course is to understand the process and methods of data analytics and to be able to apply them through practical examples. This course does not require prior programming skills.

Materials

Material given in Moodle

Teaching methods and instruction

Note: by the request of the training subscriber (degree program), starting in 2024, "Python for everyone" has been taken as the starting point instead of the previous "data analytics for everyone".
The course introduces basic features to analyze structured data and is supported by related material and assignments. Topics covered include:
- descriptive analytics
- diagnostic analytics
- time series analysis and forecasting
- introduction to machine learning.
All the necessary material will be found on Moodle including Q@A section whereby students are able to discuss matters concerning the course including assignments.

Exam dates and re-exam possibilities

Four graded assignments issued throughout the course

Learning assignments

Four assignments:
- descriptive analytics
- diagnostic analytics
- time series analysis and forecasting
- machine learning.

Assessment methods

Four assignments:
- descriptive analytics, (0 - 5 points)
- diagnostic analytics, (0 - 5 points)
- time series analysis and forecasting, (0 - 5 points)
- machine learning, (0 - 5 points)

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