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MAGISTRATURE

DATA SCIENCE (MSC)

QUALIFICATION OBJECTIVES OF THE PROGRAMME

TIUE ‘s Master of Science in Data Science program is aimed at those who want to connect their future to the field of data science as a highly skilled professional, higher education educator, and professional scientific researcher.

The purpose of training in this program is to master theoretical knowledge and acquire practical skills in the field of data science, to develop pedagogical competencies for the training of highly qualified specialists who will be able to carry out teaching activities in higher education, as well as to conduct research activities.

The teaching, methodological and scientific content of the Master’s program in Data Science includes various modules aimed at developing knowledge and skills in data science as well as scientific research in this field

Language of instruction: O’ZBEK / RUS / ENGLISH

Modes of study:

  • Full-time training: Monday through Saturday.

A Master’s degree (TIUE ) is awarded upon completion of the Data Science specialization.
Students who successfully complete their studies in English and in accordance with OTHM requirements have the opportunity to obtain an additional OTHM Level 7 Diploma in Data Science (610/2153/2).

Master’s Degree Requirement: 6 compulsory modules (subjects) totaling 180 credits (UK Credit System) must be mastered.

Term of study: 1.5 academic years (consists of 3 semesters).
Classes are held during the day in the form of lectures, seminars, practical classes, master classes and industrial practice.
Scientific and pedagogical work and thesis are carried out under the guidance of a supervisor.

The structure of the qualification consists of
6 compulsory modules totaling 180 credits for the qualification.

Duration of study for:

  • full-time students for 4 years (from October to June). Training is conducted during the day in the form of lectures, tutorials, seminars, practical classes, master classes and industrial practice.
  • The part-time program consists of two weeks of full-time classes at the end of each semester.
    The distance learning program consists of two weeks of face-to-face classes at the end of each semester.

OPEN THE DOORS TO A MODERN WORLD OF POSSIBILITIES!

REASONS FOR CHOOSING THIS PROGRAMME

1THEORETICAL KNOWLEDGE AND PRACTICAL SKILLS

Through this program, TIUE aims to develop theoretical knowledge and practical skills applicable to professional, teaching and research activities in data science.
The program is also suitable both for those who are already active professionals in the field of information technology and data science and for those who aspire to become highly qualified professionals as well as educator-researchers in the field.

2STRONG TEACHING TEAM

The strongest faculty, including both local and international specialists, who pay special attention to practical training – seminars, retreats, master classes – ensuring intensive interaction of all participants of the educational process and transfer of valuable experience from practicing experts and professionals in the field of education.

3RECOGNIZED HIGHER EDUCATION DEGREE

Upon completion of the Master’s program, graduates will receive appropriate professional teacher training and a Graduate Diploma in Data Science.

4CAREER OPPORTUNITIES

Today, in the era of informatization and digitalization, the amount of data that is collected and analyzed increases every year, and therefore specialists in this field are becoming more and more in demand.
Graduates of the program will have the necessary knowledge for professional activity both in the state and non-state sector of information technologies, as well as will be able to carry out teaching activities in higher education, research work, as well as continue their studies in the relevant doctoral programs.

Possible employment specialties:

  • Data Analyst;
  • Big Data Engineer;
  • The educator in higher education;
  • Scientific Researcher.

Tojixo’jaeva Elvira Rashidovna,
Head of Department
” DATA SCIENCE (MSC)”
System Engineer, Tashkent State Technical
University named after I.M. Gubkin. А. R. Berunii, 1996.

LEARNING STAGES

YEAR 1

Acquisition of fundamental knowledge through the study of modules on research methodology, data science, innovation and project management, data analysis and visualization, machine learning.
There is also provision for research and teaching work.

YEAR 2

Development of theoretical knowledge and practical skills through the study of advanced computer research methods.
The fulfillment of scientific and pedagogical work is also envisaged.
The training is completed by preparing and writing a master’s thesis.

CURRICULUM

Full-time education

MAGISTRATURA
1-SEMESTR

1) Methodology of Scientific Inquiry (20-credit)
2) Foundations of Data Science (20-credit)
3) Innovation and Project Management (20-credit)

2-SEMESTR.

4) Data Analysis and Visualization (20-credit)
5) Machine Learning (20-credit)
6) Research and Teaching (20-credit)

3-SEMESTR.

1) Advanced Computing Research Methods (20-credit)
2) Research and Teaching (20-credit)
3) Master’s Thesis (20-credit)

Note.
All credits are listed under the UK education system. Depending on the language of instruction, there may be slight differences in the Curriculum. At the same time, the University has the right to make some changes and additions to the Curriculum.

FACULTY LEARN MORE ‘

FACULTY LEARN MORE ‘

Ruslan Rustamovich Sultanov
Professor, Department of “DATA SCIENCE (MSC)”
Doctor of Technical Sciences (DSc) degree – Moscow Technical University of Communications and Informatics, 2022.

Sadritdinova Zulfiya Israilovna,
Associate Professor, Department of “DATA SCIENCE (MSC)”
Degree of Doctor of Philosophy (PhD), Candidate of Physical and Mathematical Sciences – Tashkent State University, 1994.

Akhmedova Iroda Nurmukhamedovna
Lecturer, Department of “DATA SCIENCE (MSC)”
Applied Mathematics, Tashkent State University,1994

Ruziev Ulugbek Shukhratovich
Lecturer, Department of “DATA SCIENCE (MSC)”
Master’s Degree in Mathematics and Computer Science – National University of Uzbekistan named after I.M. Gubkin. Mirzo Ulugbek, 2019.

TUITION FEE

For the school year


Programs


Form of training

Duration of training (academic year)

 Payment-amount of contract
PROGRAMS IN UZBEK AND RUSSIAN LANGUAGES ENGLISH PROGRAMS
Local
for students
(thousand Sum)

GRANT

 For international students
(USD)		 Local
for students
(thousand Sum)

GRANT

 For international students
(USD)
DATA SCIENCE (MSC) Full-time education 1,5 30 000 2 000 2 500 35 000 2 800

*) International students on the territory of Uzbekistan pay tuition fees in US dollars, at the exchange rate set by the Central Bank of the Republic of Uzbekistan on the day of payment. Outside Uzbekistan, the payment is made in US dollars, in the specified amount.

ADMISSION REQUIREMENTS

Admission to the first year of study

Necessary documents:

  • Document confirming secondary or specialized secondary education (certificate/diploma with an attachment)
  • Copy of passport / ID-card
  • A 5×5 photo on a white background

Academic Requirements:

  • Successful completion of the internal math exam;
  • To study in TIUE programs, all applicants must apply ONLINE ONLY ON THE UNIVERSITY’S OFFICIAL WEBSITE(tiue.uz).

Admission to the "Year 1" of the programme taught in English:

Necessary documents:

  • Document proving 12 years (9 + 3) of education (certificate/diploma with attachment) OR International Foundation Programme (IFP) certificate OR a document proving completion of the first year of studies at a local/foreign university
  • Copy of passport / ID-card
  • A 5×5 photo on a white background

Academic Requirements

Successful completion of the internal exam on:

Math;

English language proficiency or submission of an English language certificate (IELTS 5.5 or above or equivalent)

For TIUE programs, all applicants must apply ONLINE ONLY through the UNIVERSITY’S OFFICIAL WEBSITE (www.tiue.uz)

Join the Data Science (MSc) Program and open doors to the world of data and analytics! Acquire skills that are in demand in today’s society. Become part of the experts, analysts and innovators creating a data-driven future.
Apply now and start your path to success in Data Science!

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