Computer Science
Study programme title in Est.
Informaatika
Study programme title in Engl.
Computer Science
TalTech study programme code
IAPM02
MER study programme code
2013
Study programme version code
IAPM02/25
Faculty / college
I - School of Information Technologies
Head of study programme/study programme manager
Juhan-Peep Ernits
Language of instruction
Estonian
Study level
Master study
ECTS credits
120
Self-paid study programme
no
Nominal study period
4 semesters
Study programme group
Informatics and Information Technology
Broad area of study
Information and Communication Technologies
Study field
Information and Communication Technologies
Curriculum group
Software and applications development and analysis
Granting the right to conduct studies in the study programme group
õppe läbiviimise õigus
Validity date of the right to conduct studies in the study programme group
tähtajatu
No. of the decision granting the right to teach in the study programme group
112
Access conditions
Bachelor degree or education of corresponding qualification in accordance with admission requirements of TalTech.
Study programme aims and objectives
The goal of the study program is to further the knowledge of
the students in current software technologies and advance their skills in the organisation and execution of complex software development tasks involving the application of research results.
Show more...
Learning outcomes of the study programme
By completing the study program a student:
- has skills to develop modern and technologically sophisticated software;


- has skills to analyse practical problems and propose innovative technical solutions;
- has skills to apply the modern results of computer science research;
- is an effective member of industrial software development team, being able to cover different roles;
- is ready to apply their enhanced analytical and technical skills to continue their career in Estonia or abroad on technically demanding jobs or PhD programme.
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 4,60, where all grades from diploma supplement are taken into account.
Show more...
Degrees conferred
Master of Science in Engineering
Study programme version structure :
Module type
total ECTS credits
General studies
12.0
Core studies
24.0
Special studies
57.0
Free choice courses
6.0
Graduation thesis
21.0
Total
120.0
  • +
       MAIN SPECIALITY 4: computer science
    • +
         MODULE: General Studies 12.0 ECTS credits (General studies)
      Aims
      - create an understanding about the essence of entrepreneurship
      and it’s processes to supporting students in their career choice of becoming entrepreneur or entrepreneurial employee;
      - to teach to value the role of professional work and influence of knowledge in the society.
      Show more...
      Learning outcomes
      - has acquired knowledge on the basics of business;
      - understands the meaning of science, technology society and comprehends the interplay between them;


      - demonstrates the ability to discuss on social, ethical and/or philosophical topics and present his opinion.
      Show more...
      Compulsory courses:
      Course title
      Course code
      ECTS credits
      Hours per week
      Lectures
      Practices
      Exercises
      E/P-F.Ass./ Gr.Ass.
      Teaching semester
      Entrepreneurship and Business Planning
      TMJ3300
      6.0
      4.0
      1.0
      0.0
      3.0
      E
      SK
      Total: 6.0 ECTS credits
      Elective courses:
      Course title
      Course code
      ECTS credits
      Hours per week
      Lectures
      Practices
      Exercises
      E/P-F.Ass./ Gr.Ass.
      Teaching semester
      Semantics and Analytical Philosophy
      ITV9070
      6.0
      3.0
      2.0
      0.0
      1.0
      E
      SK
      Critical Thinking, Ethics and Scientific Literacy
      MNF5510
      6.0
      4.0
      2.0
      0.0
      2.0
      A
      SK
      Total: at least 6.0 ECTS credits
    • +
         MODULE: Core Studies 24.0 ECTS credits (Core studies)
      Aims
      The aim of the module is to give sufficient core knowledge for taking specialized courses,
      developing sophisticated software and being prepared to accomplish team projects and final thesis.
      Show more...
      Learning outcomes
      - knows the basics on computer science, data science and software technology;

      - has sufficient knowledge and skills for completing the courses following in the curriculum.
      Show more...
      Elective courses:
      Course title
      Course code
      ECTS credits
      Hours per week
      Lectures
      Practices
      Exercises
      E/P-F.Ass./ Gr.Ass.
      Teaching semester
      Software Architecture and Design
      IDU1550
      6.0
      4.0
      2.0
      0.0
      2.0
      E
      S
      Mathematics for Computer Science
      ITB8832
      6.0
      4.0
      2.0
      0.0
      2.0
      E
      S
      Cryptography
      ITC8240
      6.0
      4.0
      2.0
      0.0
      2.0
      E
      SK
      Software Synthesis and Verification
      ITI8531
      6.0
      4.0
      2.0
      2.0
      0.0
      E
      K
      Machine Learning
      ITI8565
      6.0
      4.0
      2.0
      2.0
      0.0
      E
      K
      Advanced Algorithms and Data Structures
      ITI8590
      6.0
      4.0
      2.0
      1.0
      1.0
      E
      K
      Formalizing knowledge
      ITI8700
      6.0
      4.0
      2.0
      1.0
      1.0
      E
      K
      Data mining
      ITI8730
      6.0
      4.0
      2.0
      2.0
      0.0
      E
      S
      Introduction to Category Theory and its Applications
      ITI9200
      6.0
      4.0
      2.0
      0.0
      2.0
      E
      K
      Advanced Programming
      ITT8060
      6.0
      4.0
      2.0
      2.0
      0.0
      E
      S
      Total: at least 24.0 ECTS credits
    • +
         MODULE: Computer Science and Applied AI 45.0 ECTS credits (Special studies)
      Aims
      To improve the knowledge and skill in many fields and methods of computer science and software development.
      Learning outcomes
      - has acquired enhanced knowledge and skills in several domains of software development advanced technologies depending on the chosen subjects;

      - is familiar with methods of applied computer science, is able to independently work with relevant literature and to present results.
      Show more...
      Compulsory courses:
      Course title
      Course code
      ECTS credits
      Hours per week
      Lectures
      Practices
      Exercises
      E/P-F.Ass./ Gr.Ass.
      Teaching semester
      Studies Planning Seminar
      ITX8300
      3.0
      1.0
      0.0
      0.0
      1.0
      A
      S
      Master seminar I
      ITX8301
      3.0
      2.0
      0.0
      0.0
      2.0
      H
      K
      Master seminar II
      ITX8302
      3.0
      2.0
      0.0
      0.0
      2.0
      H
      S
      Total: 9.0 ECTS credits
      Elective courses:
      Course title
      Course code
      ECTS credits
      Hours per week
      Lectures
      Practices
      Exercises
      E/P-F.Ass./ Gr.Ass.
      Teaching semester
      Robotics
      IAS0060
      6.0
      4.0
      1.0
      3.0
      0.0
      E
      K
      Robot Guidance and Software
      IAS0220
      6.0
      4.0
      1.0
      3.0
      0.0
      E
      S
      Exact Methods in Decision Processes
      ITB8802
      6.0
      4.0
      2.0
      2.0
      0.0
      E
      S
      Theory of Computation
      ITB8821
      6.0
      4.0
      3.0
      0.0
      1.0
      E
      K
      Software Processes and Quality
      ITB8826
      6.0
      4.0
      2.0
      2.0
      0.0
      E
      S
      Special Topics of Cryptography
      ITC8290
      6.0
      2.0
      0.0
      0.0
      2.0
      H
      S
      Databases II
      ITI0207
      6.0
      4.0
      2.0
      2.0
      0.0
      E
      S
      Foundations of Artificial Intelligence and Machine Learning
      ITI0210
      6.0
      4.0
      2.0
      2.0
      0.0
      E
      SK
      Logical Programming
      ITI0211
      6.0
      4.0
      2.0
      2.0
      0.0
      H
      S
      Distributed Systems
      ITI0215
      6.0
      4.0
      2.0
      2.0
      0.0
      E
      K
      Mathematical Foundations of Machine Learning
      ITI8010
      3.0
      4.0
      2.0
      0.0
      2.0
      A
      S1
      Real-Time Software Engineering
      ITI8520
      6.0
      4.0
      2.0
      2.0
      0.0
      E
      K
      Mathematical Modelling
      ITS8010
      6.0
      4.0
      2.0
      0.0
      2.0
      E
      SK
      System Programming
      ITS8020
      6.0
      4.0
      2.0
      2.0
      0.0
      E
      S
      Computer vision
      ITS8030
      6.0
      4.0
      2.0
      2.0
      0.0
      E
      K
      Speech processing by humans and computers
      ITS8035
      6.0
      4.0
      2.0
      0.0
      2.0
      E
      S
      Natural Language and Speech Processing
      ITS8040
      6.0
      4.0
      2.0
      0.0
      2.0
      E
      K
      Large-Scale Intelligent Environmental Sensing: Theory and Practice
      ITS8055
      6.0
      4.0
      2.0
      2.0
      0.0
      E
      K
      Energy Data Science
      ITS8080
      6.0
      4.0
      2.0
      2.0
      0.0
      E
      S
      Work Based Project I
      ITS8901
      6.0
      0.0
      0.0
      0.0
      0.0
      E
      SK
      Work Based Project II
      ITS8902
      6.0
      0.0
      0.0
      0.0
      0.0
      E
      SK
      Work Based Project III
      ITS8903
      6.0
      0.0
      0.0
      0.0
      0.0
      E
      SK
      Work Based Project IV
      ITS8904
      6.0
      0.0
      0.0
      0.0
      0.0
      E
      SK
      Work Based Project V
      ITS8905
      6.0
      0.0
      0.0
      0.0
      0.0
      E
      SK
      Final Thesis Planning and Literature Review Writing
      ITX8400
      6.0
      0.0
      0.0
      0.0
      0.0
      A
      SK
      Scientific Computing
      YFX1510
      6.0
      4.0
      2.5
      0.0
      1.5
      E
      K
      Total: at least 36.0 ECTS credits
    • +
         MODULE: Practical Training 12.0 ECTS credits (Special studies)
      Aims
      - give an experience in planning, developing, presenting and defending a professional project;

      - develop the skills in teamwork;
      - to teach oral and written professional expression skills; in written;
      Show more...
      Learning outcomes
      Having finished the studies, a student:
      - can plan, develop, and present software development projects;


      - can work both individually and in a team;
      - can express himself/herself professionally both orally and in written.
      Show more...
      Elective courses:
      Course title
      Course code
      ECTS credits
      Hours per week
      Lectures
      Practices
      Exercises
      E/P-F.Ass./ Gr.Ass.
      Teaching semester
      Software Development Team project
      ITI8740
      12.0
      4.0
      2.0
      0.0
      2.0
      H
      SK
      Teaching Practice (Internship)
      ITI8750
      6.0
      0.0
      0.0
      0.0
      0.0
      A
      SK
      Teaching Practice
      ITI8751
      6.0
      4.0
      0.0
      0.0
      4.0
      A
      SK
      Teaching Practice I
      ITI8752
      3.0
      2.0
      0.0
      0.0
      2.0
      A
      SK
      Teaching Practice II
      ITI8753
      3.0
      2.0
      0.0
      0.0
      2.0
      A
      SK
      Practical Training (Internship)
      ITI8760
      6.0
      0.0
      0.0
      0.0
      0.0
      A
      SK
      Total: at least 12.0 ECTS credits
    • +
         MODULE: Free Choice Studies 6.0 ECTS credits (Free choice courses)
      Aims
      To be able to navigate and be acquainted both in special and
      wider problems and topics
      Show more...
      Learning outcomes
      Knows, is able to explain and apply the knowledge obtained during
      the free choice studies
      Show more...
    • +
         MODULE: Master Thesis 21.0 ECTS credits (Graduation thesis)
      Aims
      - apply the knowledge and skills acquired;
      - give an experience in solving a task;


      - to develop the ability to manage, explain, document, and present a project.
      Show more...
      Learning outcomes
      - is able to solve a problem in the field of software development;

      - is able to justify the selected solution method;
      - is able to present the solution in writing and in public presentation.
      Show more...
    • +
         STANDARD STUDY PLAN: Autumn daytime study
      • +
           1st Semester
      • +
           2nd Semester
      • +
           3rd Semester
      • +
           4th Semester
      • +
           0 Semester