BD-2-001 (0) - Introduction to Analytics

• 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
• Big data analytics 2022 - Big data analytics - specialised professional studies
• Big data analytics 2023 - Big data analytics - specialised professional studies

1 (2022-08-01 to 2022-10-23)

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 modelling 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 learns 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.

Basic python programming skills are required. Bases on Linear algebra and statistics are an asset. Knowledge of UNIX operative systems is recommended, but not required.

See literature as specified on Itslearning.

• Lectures - 30 hours
• Project- and production work/artistic activities - 55 hours
• Individual studies - 50 hours

• Total workload of the course: 135 hours
• Of which autonomous studies: 135 hours
• Of which scheduled studies: 0 hours

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 (27 students enrolled)

12 months after course has ended

2022-08-10 to 2022-09-06