BD-2-001

• Big data analytics 2016 - Big data analytics
• Big data analytics 2017 - Big data analytics
• Big data analytics 2018 - Big data analytics
• Big data analytics 2019 - Big data analytics
• Big data analytics 2020 - Big data analytics
• Big data analytics 2021 - Big data analytics - specialised professional studies

1 (2021-08-01 to 2021-10-24)

English

Compulsory

Second

1

5 cr

The aim of the course is to introduce the
student to the different concepts of
implementing an analytics process. Students
learn the process of problem
solving in analytics from data understanding
and
preprocessing, through
modelling choices and implementation until the
interpretation, visualization
and utilization of the analysis. We will look
at
typical real-life
applications of analytics. The course will
provide hands-on lectures to
performing the steps of modeling and analysis.

At the end of the course the student is
expected
to be able to model
predictive time series problems that use
machine
learning for performing
regression. The student learn to implement an
analytics process for
forecasting and to validate results by
calculating forecasting errors

This course includes topics on analytics systems,
Python development, feature
engineering, time series forecasting,
visualization, and error calculation.

Understanding of programming.

See literature as specified on Itslearning.

Multiform education

To pass the course the student should pass the
following examinations:
Assignment 1 as specified in Itslearning.
Project 1 as specified in Itslearning.

The examinations contribute to the final grade
as follows:

Assignment 1 - 10%
Project 1 - 90%

• Scherbakov-Parland Andrej
• Westerlund Magnus

Westerlund Magnus

https://arcada.itslearning.com/ External link

No limit (46 students enrolled)

12 months after course has ended

2021-08-09 to 2021-09-05