Double degree in Computer Science:
Data Analytics and Artificial Intelligence
Boost Your Career with the power of Data Analytics and Artificial Intelligence
Key Data
Study Form
Full-time, blended mode
Intake
September, 2024
Language
Degrees
Master of Natural Sciences in Computer Science with specialisation in Data Analytics and Artificial Intelligence (TSI)
MSc Computer Science: Data Analytics and Artificial Intelligence (UWE)
Programme
Overview
This world needs for more intelligence. Artificial Intelligence can make people stronger and empower us to reach business goals and improve our lives. Our master programme is an exciting journey to the coming world of AI. It starts from the data, develops analytical and programming skills, goes through the modern statistics and machine learning, leads to better understanding of AI-powered agents and devices, and comes to the ability to create your own, unique AI solutions.
Director of the Programme
Director of the Programme
Assoc. prof., Dr. sc. ing.,
Nadezda Spiridovska
Coordinator of the Programme
Jonathon Stadon
UWE Bristol
UWE Link Tutor
Jointly designed with our strategic UK partner University of West of England this study programme provides you with a unique opportunity to become an expert in a field of data analytics and artificial intelligence. The programme structure and all courses have been validated by the UWE Special University Validation Panel. The content of the programme is fully in line with international standards and industry demanded skills and knowledge, this becomes possible as we have carefully adopted the best and most demanded courses in the field from the UWE.
Are your first background not from the information and communication technology field? This programme offers the unique option for you to change your life and turn your career into IT field. How is it possible? We are offering you to spend a pre-master semester, which will enrich you with all necessary skills and knowledge to successfully complete the core study programme.
During your study you will have explicit experience with different industry-class tools and technologies, like R/Python, Tableau, SQL, noSQL, etc.
After successful completion of the study programme, you will be able to take positions of:
- Data Analyst
- Data Scientist
- Applied Machine Learning Engineer,
- Analytics Manager/Data Science Leader
- Consultant in the field of Data Analytics and Artificial Intelligence
- Researcher in the field of Data Science etc.
The University of the West of England is a modern and dynamic University, based near Bristol with the new state-of-the-art learning spaces and world class teaching facilities. The University is well known for its links to leading global companies such as Airbus, and for the quality of its research. The University has over 30,000 students and more than 600 courses covering a wide range of subject areas it is one of the largest and best-known universities in the UK.
The University of the West of England (UWE Bristol) has been ranked 4th amongst HEIs in the South West of England for student satisfaction by the National Student Survey (NSS) 2021 published on 15 July, 2021. As well as ranked 21 out of 121 UK institutions climbing 7 places to their highest ever position.
The University was awarded TEF gold status in the latest Government rankings for higher education providers, which is the highest rating in the Teaching Excellence and Student Outcomes Framework (TEF) 2018
I often hear that AI revolution would lead to greater inequality between those who are technologically adept and those who are not. It is true that AI-related professions are in great demand and that data scientists and data engineers earn very well. But it is not true that AI could not be taught and learned through a good MSc programme. The program designed by TSI in cooperation with UWE Bristol is what the industry needs. Together with many other international companies Deloitte has chosen our city for its regional center of AI expertise, Riga .ai Studio. Helmut Schmidt once told that people with visions should go to the doctor. I have vision of Riga as the international hub for AI science and learning. But I do not need a doctor. I need people around us who share the same conviction and who work hard towards this goal. TSI’s leaders and professors are from this cohort.
Tutors from the industry
Within the double degree study programme framework, visiting professors and industry professionals are involved in the implementation of the programme. Meet them:
Dr. Neil Rubens
Senior Data Scientist at VISA Inc. - The world’s leader in digital payments
Dr. sc. ing. Elena Kijonoka
Data Scientist/Digital Data Associate Manager at Accenture Baltics
Igor Rodin
Partner of Deloitte Central Europe
Jelena Revzina
IT Security Specialist at iPro
Dr. Neil Rubens
Senior Data Scientist at VISA Inc. - The world’s leader in digital payments
Dr. sc. ing. Elena Kijonoka
Data Scientist/Digital Data Associate Manager at Accenture Baltics
Igor Rodin
Partner of Deloitte Central Europe
Jelena Revzina
IT Security Specialist at iPro
Dr. Neil Rubens
Senior Data Scientist at VISA Inc. - The world’s leader in digital payments
Dr. sc. ing. Elena Kijonoka
Data Scientist/Digital Data Associate Manager at Accenture Baltics
Igor Rodin
Partner of Deloitte Central Europe
Jelena Revzina
IT Security Specialist at iProBenefits of the
programme
Change Career Path to IT Field
UK Quality Standarts
Partner with a Gold Award University on Teaching Excellence TEF 2018
Exclusive Access to UWE Services and Resources
Member of TSI and UWE Student & Alumni Community
Professional Network
Programme is
Supported by
Discover
More
Block A – Mandatory Courses
| Cybersecurity and data protection | 6 |
| Critical Thinking and Innovation | 6 |
| Data Mining | 6 |
Modern Database Technologies | 9 |
| Project and Requirements Management | 6 |
| Research Methodology | 9 |
| Artificial Intelligence Group Project | 9 |
| Master Thesis | 30 |
Block B – Specialization Courses
Business Intelligence and Data Visualisation  Business Intelligence and Data Visualisation introduces students to the core concepts of data visualisation and machine learning in the context of business intelligence and leads them through an independent exploration of a typical machine learning project. In the frame of the course students will have an experience to use modern visualisation tools (at example Tableau) | 6 |
| Information Systems and Technologies The course is targeted on enrichment of the students with knowledge about emerging and vivid technologies in IS domains. The aim of course is to make students familiar with different approaches to the application of Information Systems for managing the enterprise and to acquaint students with the way of solving problems and performing practical tasks of Management Automation based on modern information and telecommunication technologies. | 6 |
| Machine Learning and Predictive Analytics This course will equip students with knowledge and understanding of tools and techniques commonly utilised within the field of Machine Learning. The course will set the context of the machine learning and predictive analytics utilisation in business intelligence. Courses discusses range of applications for predictive analytics. Wide range of the machine learning techniques will be considered in the course Decision tree learning, Artificial neural networks, Naive Bayes classifier, Genetic algorithms etc. | 6 |
| Mathematics for data analytics This course will introduce and, in some cases, review mathematical concepts relevant to future work in applied data analytics. It will cover important concepts in basic and linear algebra, matrix and vector algebra, eigenvectors and eigenvalues, optimization techniques, Bayes rule, and maximum likelihood. | 6 |
| Programming for data analytics The course is designed to be accessible to non-Computer Science major students with little or no programming experience and emphasizes writing programs that can retrieve and manipulating large amount of data. The first half of the course focuses on incentive learning programming language (Python or R), while the second half of the course covers selected advanced topics such as data visualization, web scraping, database access and others. | 9 |
Block C – Elective Courses
| Big Data | 6 |
| Labour Safety, Civil Defence and Environment Protection | 3 |
Programme implementation form: full-time (in blended mode)
Study mode | Foreseen schedule (Day/Time) | Foreseen efforts (per week) |
Theoretical classes: Remote \ Synchronous mode | Tuesday-Thursday (18.15-21.30), | 2-4 classes (4-8 ac.h) |
Tutorials, practical classes, seminars, discussions, groupwork: Face-to-Face mode | Friday evenings (18.15-21.30) + Saturdays (8.45-15.45), weekly | 4-6 classes (8-12 ac.h) |
Independent individual or group studies | Within a semester | 20 ac.h in average |
Long programme (2 years, 120 CP (ECTS)) with the mandatory Pre-master semester:
Bachelor’s degree in Natural Sciences in Computer Science, Informatics, or Mathematics, or bachelor’s degree in Engineering in Electrical Engineering, Electronics, Information Technology with a mastered programme of at least 180 CP (ECTS), or first-cycle professional higher education in the relevant educational fields.
First-cycle professional higher education or bachelor’s degree in Economics, Management Science, Logistics, Finance, Business and equivalent education, with at least 1 year of professional experience in the field of Information Technology, entrance exam.
Short programme (1.5 years, 90 CP (ECTS)) without the Pre-master semester:
- First-cycle professional higher education or a bachelor’s degree in Computer Science, Informatics, or Mathematics, or a bachelor’s degree in Engineering in Electrical Engineering, Electronics, Information Technology, if at least 6 CP (ECTS) of programming and at least 4 CP (ECTS) of Database Technology have been acquired, and if the bachelor’s degree has been obtained for at least four years long studies at least 240 CP (ECTS).
For the Winter Intake 2025, you may apply for the shorter study period – the study process only 1 year + Master’s thesis.
The first step to apply to master’s studies is to fill an application at admission.tsi.lv. After you register in the system, we will contact you shortly.
For further inquiries contact admission@tsi.lv, +371 29 990 841
| Full time | Part time | Distance learning | |
|---|---|---|---|
| Duration | 1.5/2 years | ||
| Tuition fee EUR/year | 6500 EUR | ||
| Tuition fee for applicants from 🇱🇻 🇱🇹 🇪🇪 🇺🇦 🇪🇺 and EEA, EUR/year | 5400 EUR |
We are open for individual consultations at a time convenient for you and in the language of your choice – Latvian, English or Russian. Book a consultation here or write/call us directly, through the contacts listed below
Е-mail: admission@tsi.lv
Тelephone: +371 29 990 841
WhatsApp: +371 29 990 841
Skype: infotsi
