Study programme title in Est.
Tehisintellekt äris
Study programme title in Engl.
AI in Business
TalTech study programme code
MAIM26
MER study programme code
261019
Study programme version code
MAIM26/26
Faculty / college
M - School of Business and Governance
Head of study programme/study programme manager
Helery Tasane
Language of instruction
Estonian
Self-paid study programme
yes
Nominal study period
3 semesters
Study programme group
Business and Administration
Broad area of study
Business, Administration and Law
Study field
Business and administration
Access conditions
a) Master's degree or equivalent qualification
b) Higher education
in another field with a nominal value of at least 240 ECTS and at least 1 year of work experience as a manager or specialist
c) Higher education and at least 3 years of work experience as a manager or specialist Show more... Study programme aims and objectives
The aim of the programme is to train experts who can develop
basic artificial intelligence (AI) solutions from identifying a business need to presenting a prototype or implementation plan in a way that aligns clearly with the strategic goals of the organization. Show more... Learning outcomes of the study programme
The graduate:
- independently analyses an organisation's business model, target customer and internal processes;
- critically assesses the potential for AI implementation, taking into account data availability, quality, and business impact;
- uses AI and data analysis tools (including Python and BI tools) to prototype and pilot solutions;
- designs AI implementation strategies across various horizons (e.g., process optimisation, service transformation, business model innovation);
- leads interdisciplinary AI implementation projects and evaluates their business impact (KPIs, ROI);
- takes into account ethical, legal, and social considerations when implementing AI. Show more... Graduation requirements
Completion of the curriculum in the required amount, and the successful defence of the graduation paper in conformity with the requirements set by the TalTech Senate.
In order to obtain cum laude diploma the graduation paper must be defended for the grade "5" and the weighted average grade must be at least 4,600, where all grades from diploma supplement are taken into account. Show more... Degrees conferred
Master of Arts in Social Sciences
Study programme version structure :
Module type
total ECTS credits
+
MAIN SPECIALITY 1: AI in Business
+
MODULE: Introduction to Strategic Management of AI 6.0 ECTS credits (General studies)
Aims
The objective of this module is to provide learners with an understanding of the foundations of strategic management of artificial intelligence (AI).
The focus is on the role of technology and innovation in organisational development and the ability to design AI-based business strategies that support value proposition, efficiency, and competitiveness. The module uses service design and business model frameworks to teach how to design AI solutions based on business needs. Show more... Learning outcomes
Upon completion of the module, the student:
- explains the role of technology and AI in innovation and organisational change;
- analyses business models and strategies and identifies opportunities to apply AI to create business value;
- applies service design and strategic management tools to design AI-based solutions and development plans;
- interprets the impact of strategic technologies, including AI, on internal processes and external markets;
- develops an initial AI solution or action plan based on the organisational context and customer needs. Show more... Compulsory courses:
Course title
Course code
ECTS credits
Hours per week
Lectures
Practices
Exercises
E/P-F.Ass./ Gr.Ass.
Teaching semester
MMO3988
6.0
4.0
2.0
0.0
2.0
H
S
+
MODULE: Foundations of Artificial Intelligenc 12.0 ECTS credits (Core studies)
Aims
The objective of this module is to provide students with practical
and theoretical knowledge necessary for the successful implementation of artificial intelligence (AI) at the organizational level. The focus is on the fundamentals of data science, data flow analysis, process models, and enterprise architecture in order to build a foundation for integrating AI-based solutions into existing business processes. In addition, students will develop skills in process visualization and the design of data-driven workflows. Show more... Learning outcomes
Upon successful completion of the module, the student:
- positions
data science as a field and understands its role in data-driven management and AI implementation within organizations;
- describes the data analysis workflow from data collection and processing to model testing and interpretation;
- applies programming and analytical skills to solve basic data-driven and machine learning-based tasks;
- analyzes an organization's enterprise architecture and business processes to identify bottlenecks and opportunities for AI and digital solutions;
- navigates international standards in data management and enterprise architecture and applies them to design systematic and high-quality solutions. Show more... Compulsory courses:
Course title
Course code
ECTS credits
Hours per week
Lectures
Practices
Exercises
E/P-F.Ass./ Gr.Ass.
Teaching semester
ITB8807
6.0
4.0
2.0
0.0
2.0
E
SK
ITX0020
6.0
4.0
2.0
2.0
0.0
E
S
+
MODULE: AI in Business 21.0 ECTS credits (Special studies)
Aims
The objective of this module is to equip students with practical and theoretical knowledge required to implement AI solutions in business processes.
Students will develop the ability to identify business problems, apply data analytics, and prototype AI business applications that address specific organizational challenges. Show more... Learning outcomes
Upon successful completion of the module, the student:
- understands
the principles of data analytics and data-driven management and can apply suitable methods to solve business-related problems;
- prototypes basic AI solutions using modern programming and automation tools;
- evaluates the impact of AI applications on business outcomes (e.g., customer experience, operational efficiency) and is able to design pilot stages. Show more... Compulsory courses:
Course title
Course code
ECTS credits
Hours per week
Lectures
Practices
Exercises
E/P-F.Ass./ Gr.Ass.
Teaching semester
MMK5190
6.0
3.0
1.0
0.0
2.0
E
S
MMO3979
6.0
4.0
2.0
0.0
2.0
E
K
Elective courses:
Course title
Course code
ECTS credits
Hours per week
Lectures
Practices
Exercises
E/P-F.Ass./ Gr.Ass.
Teaching semester
MMM5550
3.0
4.0
2.0
0.0
2.0
A
K2
MMO5788
3.0
2.0
1.0
0.0
1.0
A
S
MMT5790
6.0
4.0
2.0
0.0
2.0
E
S
TMK0200
3.0
2.0
1.0
0.0
1.0
E
S
Total: at least 9.0 ECTS credits
+
MODULE: Free Choice Studies 3.0 ECTS credits (Free choice courses)
Aims
The aim of free choice studies is to give the student the opportunity to acquire competencies in a field of interest to them.
Learning outcomes
A student who has completed free choice studies has acquired competencies in a field that interests them.
+
MODULE: Final Examination 18.0 ECTS credits (Graduation exam)
Aims
The objective of the final examination is to integrate the knowledge and skills acquired throughout the study programme via an applied project. In this project,
the student develops an AI implementation strategy for specific organization or business problems. Using service design and business model tools, the student models how the AI solution creates value and aligns with the organization’s business strategy, processes, and technological architecture. Show more... Learning outcomes
Upon passing the final examination, the student:
- develops an AI implementation strategy for a specific business context, using strategic design and innovation frameworks;
- identifies problem areas within an organization or market where AI solutions can create value and designs an appropriate solution considering data availability, processes, and technological readiness;
- presents their project clearly and convincingly, both in writing and orally, justifying decisions from the perspective of various stakeholders;
- is prepared to pilot or further develop their solution, including evaluating its impact on business performance metrics (e.g., KPIs, ROI). Show more... Compulsory courses:
Course title
Course code
ECTS credits
Hours per week
Lectures
Practices
Exercises
E/P-F.Ass./ Gr.Ass.
Teaching semester
MMO5599
18.0
0.0
0.0
0.0
0.0
E
S
+
STANDARD STUDY PLAN: Autumn daytime study
+
STANDARD STUDY PLAN: Autumn session-based study
