Advanced Studies in Statistical Data Analytics, At least 80 cr

Prerequisites and the structure of studies in the Statistical Data Analytics specialisation

Prerequisities

Bachelor's degree in a suitable field or equivalent studies, and a good knowledge of English. Suitable studies include:

Basic knowledge in Statistics (~10 ECTS). Following course units or equivalent:

• DATA.STAT.110 Introduction to Statistics, 5 ECTS

• MATH.APP.210 Introduction to Probability and Statistical Inference, 5 ECTS

Basic knowledge in Computer Science and programming skills (~10 ECTS). Following course units or equivalent:

• COMP.CS.100 Programming 1: Introduction to Programming [Python language], 5 ECTS

• COMP.CS.110 Programming 2: Structures [C++ language], 5 ECTS

Complementary studies

The student’s Bachelor studies also need to include the following studies, and if not, they need to be studied during the MSc programme studies and can be included in the Free Choice Studies category as complementaty studies.

• DATA.STAT.120 Introduction to Statistical Methods, 5 ECTS. For students who enrolled during the 2020-2021 and who enroll for the 2021-22 academic year, the complementary course Introduction to Statistical Methods can be replaced by the course Computational Methods and Principles of Bayesian Inference, 5 ECTS, for which materials in English (lecture notes, exercises) are provided for independent studying and exams.

• DATA.STAT.440 Statistical Inference 1, 5 ECTS

• COMP.CS.300 Data Structures and Algorithms 1, 5 ECTS

Please note that C++ skills are required for Data Structures and Algorithms 1. The student should also be familiar or become familiar with basic mathematics including basic vector and matrix operations.

Note also that some of the course units listed above are mainly lectured in Finnish. Materials in English (lecture notes, exercises) are provided for independent studying and exams. 

Structure of studies

Master of Science degree (120 ECTS) consists of the following studies
- 50 ECTS advanced studies of the student’s specialisation

- 30 ECTS master's thesis on a topic inside the specialisation

- 40 ECTS other studies including free choice studies, joint studies like orientation and language studies, and possible complementary studies.

The Statistical Data Analytics (M.Sc.) specialisation features several similar topic areas as the Data Science (M.Sc.) specialisation, but the Statistical Data Analytics (M.Sc.) specialisation places more emphasis on such aspects of data science and artificial intelligence where statistical understanding and modeling of data uncertainty, variation and dependency is a crucial advantage. 

After completing the Statistical Data Analytics specialisation the student will have the skills and knowledge to 

• choose suitable data analysis methods for the analysis tasks at hand from a reasonably wide selection of statistical and computational methods, including methods that are necessary for integrating data from different data sources during data preprocessing and/or analysis 

• understand how the methods model data variation, uncertainty and dependency

• apply these methods to analyse data, and interpret results and associated uncertainties critically

• use efficient computational and statistical methods to manage and analyse big data, including statistical methods such as probabilistic classification and regression, graphical models, time series analysis, and Bayesian analysis, and a variety of computational algorithmic approaches such as parallel computation and deep neural networks

• visualise the data / analysis results

• apply the analysis methods in new situations 

• understand how well the methods may perform in different situations.