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.
Veijo Vänttinen
Material given in Moodle
Pasila Campus
Four graded assignments issued throughout the course
English
20.01.2025 - 16.05.2025
Four assignments: - descriptive analytics - diagnostic analytics - time series analysis and forecasting - machine learning.
02.01.2025 - 17.01.2025
Veijo Vänttinen
61 - 100
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)
BUTEM Degree Programme in Business Technologies, ATBUM Degree Programme in Aviation and Tourism Business, LEBUM Degree Programme in Leading Business Transformation, HOSBUM Degree Programme in Tourism and Hospitality Business, BUTUM Degree Programme in Business Technologies and Management
0.00 cr
5.00 cr
H-5
The course has lessons every week. The lessons cover the basics of data analytics applications using Python coding.
The course implementation welcomes independent study of topics with the help of ready-made examples and videos, within the guidelines of the Haaga-Helia University of Applied Sciences.
No previous experience in coding is required.
Juha Nurmonen
The learning material is mainly distributed through the Moodle learning environment. The course brings together the main techniques needed for the fundamentals of data analytics. It also provides tools for applied analytics research or thesis work. Such issues are constantly changing and the course will mainly make use of teachers’ and otherwise up-to-date material.
The course implementations are designed for students who are about to enter work life or are already working there. The course content takes into account the content used in the field.
Pasila Campus
The organisations of exam and retake will be agreed together with the course participants.
The exam will be held at the end of the course on a date to be agreed with the participants in the implementation. The date of the re-examination will also be mutually agreed with the participants of the implementation.
The exam and retakes are organised in Pasila and participants are expected to be present; particularly the identity of the examiner will be verified.
In the tests, the author has extensive access to materials and to the Internet. It is therefore not possible to conduct the test as an Exam.
English
Data analytics skills are international skills. Methodological expertise is international.
24.03.2025 - 16.05.2025
The topics presented in the lectures are learned by doing related exercises. Assignments will be returned regularly during the course, every one or two weeks. Assignments will be given and returned via Moodle. Assignments will cover the following topics: descriptive analytics, explanatory analytics, time series and time series forecasting, predictive analytics and basics of machine learning models.
07.01.2025 - 21.03.2025
The course has weekly lessons according to the timetable. A detailed weekly timetable will be made available on the Moodle learning environment if the Director of Studies decides to start this implementation. The timetable for the returnable learning assignments will follow the lecture timetable.
There are no shortcuts to learning, and doing the work is essential. Other ways of obtaining a grade in the Haaga-Helia University of Applied Sciences credit register should be requested from the teacher responsible for the course.
Juha Nurmonen
31 - 50
The determination of the implementation grade will be announced at the beginning of the implementation.
AIBUM Degree Programme in AI for Business Transformation
0.00 cr
0.00 cr
H-5
This is a virtual course. Course material (including examples and videos) will be available in Moodle.
Course material will be available in Moodle.
Pasila Campus
No exam.
English
19.08.2024 - 13.12.2024
There are three exercises. Their topics cover descriptive analytics, diagnostic analytics, time series and machine learning.
03.06.2024 - 16.08.2024
Toni Ernvall
30 - 100
Final grade is the average of assignment grades rounded to integer. All assignments must be passed.
AVO Avoin ammattikorkeakoulu
0.00 cr
5.00 cr
H-5
Juha Nurmonen
Pasila Campus
English
21.10.2024 - 13.12.2024
03.06.2024 - 18.10.2024
Juha Nurmonen
31 - 60
BUTEM Degree Programme in Business Technologies, STROME Degree Programme in Strategising in Organisations, ATBUM Degree Programme in Aviation and Tourism Business, LEBUM Degree Programme in Leading Business Transformation, AVBUM Degree Programme in Sustainable Aviation Business, HOSBUM Degree Programme in Tourism and Hospitality Business
0.00 cr
1.00 cr
H-5
In the classroom or online classes, one will learn the basics of data analytics using Python coding under the guidance of a teacher. Students can also study independently with the help of ready-made examples.
No previous coding experience is required.
Heidi Rajamäki-Partanen
https://1u.fi/hhjuhanurmonen
Pasila Campus
English
25.03.2024 - 17.05.2024
The implementation includes individual tasks where the skills learned are applied. The topics of the tasks include Descriptive analytics Diagnostic analytics Time series description and analysis Time series forecasting Predictive analytics and machine learning models
02.01.2024 - 15.02.2024
Period 2, Autumn 2024
The implementation allows one to participate in common teaching according to your own skills. The course material supports indivudual learning.
Juha Nurmonen
31 - 60
Individual assignments are assessed and each contributes its own weight to the final grade. Each individual assignment must be passed according to the criteria given in the implementation during the same course implementation.
BUTEM Degree Programme in Business Technologies, ATBUM Degree Programme in Aviation and Tourism Business, LEBUM Degree Programme in Leading Business Transformation, HOSBUM Degree Programme in Tourism and Hospitality Business
0.00 cr
0.00 cr
H-5
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.
Heidi Rajamäki-Partanen
Material given in Moodle
Pasila Campus
Four graded assignments issued throughout the course
English
15.01.2024 - 15.03.2024
Four assignments: - descriptive analytics - diagnostic analytics - time series analysis and forecasting - machine learning.
02.01.2024 - 12.01.2024
15.1 - 15.3.2024
Veijo Vänttinen
31 - 100
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)
BUTEM Degree Programme in Business Technologies, ATBUM Degree Programme in Aviation and Tourism Business, LEBUM Degree Programme in Leading Business Transformation, HOSBUM Degree Programme in Tourism and Hospitality Business
0.00 cr
5.00 cr
H-5