Course Structure

The growth in the field of Data Science has been enormous in recent years with a growing demand for practitioners in a variety of industries. With the ever increasing growth in data generation and collection, industries now rely heavily on appropriate analysis. Consequently, data science and analytics has become a core component of both the public and private sectors who seek a competitive advantage.


The MSc in Data Science and Analytics at MTU, a collaboration between the Department of Mathematics and the Department of Computer Science, aims to develop highly skilled and competent graduates in the rapidly expanding field of Data Science. This collaborative programme provides graduates with a thorough grounding in the theory of data science, while allowing graduates to become highly proficient in the technical and practical skills of a modern data scientist. The course will equip graduates with the skills to gather and store data, process data using advanced statistics and techniques such as machine and deep learning and deliver new insights and knowledge from the collected data.


The programme has been designed with industry experts to ensure that in the first two semesters graduates develop core skills in programming, database management, statistical modelling, time series analysis, machine learning, and data visualisation and interpretation of results. The industry based capstone project in Semester 3 is a key component of this MSc programme.



The full-time MSc in Data Science & Analytics will run over three semesters, i.e. fifteen months. Each semester accrues 30 credits.


Semester 1 – September 2021 to January 2022
Semester 2 – January 2022 to June 2022
Semester 3 – September 2022 to January 2023



The Semester 1 schedule consists of six taught modules (each 5 credits). The learner acquires a foundation in Mathematics, Statistics and Computer Science, with the signature module DATA8001 Data Science & Analytics overarching the other five modules of this semester. 


It is during the second semester that the specialisation into the “Big Data” space takes effect, with modules in Statistics for Big Data, Data Visualisation, Distributed Data Management, Time Series, and Machine Learning.


In Semester 3, the MSc learner undertakes one capstone project module (DATA9003 Research Project – Data Science) worth 30 credits. 


The graduate will gain significant practical experience, in software packages such as R, Excel, VBA, SAS, SPSS, RapidMiner, Tableau, Hadoop and Qlikview, and in the programming languages Python, SQL and NoSQL.


Click on the Modules tab at for further information and module descriptors.

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