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Applied Data Analytics

About the program

The graduate program "Applied Data Analytics" is a comprehensive and specialized educational program that equips students with the necessary skills and knowledge to analyze and interpret complex datasets. By combining statistics, mathematics, computer science, and business, students learn various data analysis techniques and gain proficiency in programming languages and tools commonly used in the field. The program emphasizes ethical considerations and practical applications, preparing graduates to tackle data-related challenges across industries. Through hands-on experience, students apply their knowledge to real- world scenarios, fostering a deep understanding of data analytics in different domains. Ultimately, graduates are well-prepared for roles such as data analysts, scientists, and consultants, making valuable contributions to organizations in an increasingly data-driven world.

7M06103 Applied Data Analytics

Objective of Educational Program

Training highly qualified scientific and applied specialists and software engineers in the field of large-volume data analysis, as well as managers and managers of software and information systems for the information technology industry and interdisciplinary industries related to data processing in various sectors of the economy of the Republic of Kazakhstan.

List of a specialist’s positions

Data Analyst
Data Scientist
Big Data Analyst
Big Data Engineer
Software Developer
Head of the organization
Deputy head of the structural unit
Head of the structural unit
Expert of the republican center
Employee of the national scientific and practical center, university

Learning Outcomes

Formulate tasks arising in the course of research activities and apply methodological and psychological approaches in research.
Possess critical thinking and academic language at a professional level that allows conducting scientific research and teaching special disciplines in universities
Apply data analysis methods to solve various applied data analysis and analytical processing tasks
Manage the team and lead the software development and data analysis process
Apply methods of designing and developing software systems to solve a wide class of applied problems in the field of analysis in various fields.
Formulate, modify and develop machine learning and artificial intelligence methods
Understand the fundamental principles and possess the mathematical knowledge underlying the methods of data analytics and machine learning
Have knowledge in related fields of project management, computer science, information security

Field of professional activity

The field of further professional activity of graduates of the program “Applied Data Analytics” includes specialization as a teacher in higher educational institutions, work as a researcher/research worker in research institutes, as well as work in production as a data analyst in the development of software for information and computing systems for various purposes.

The main activity involves the creation and management of models, methods and algorithms of data analysis in companies and institutions that specialize in the development of software tools for data analysis, as well as work in data analysis departments in industrial enterprises, design organizations, public and private enterprises.

The field of activity is not limited only to the information technology industry, but also involves participation in data analytics projects in interdisciplinary industries where a wide range of software tools are developed, implemented and used. In other words, graduates will be in demand in almost all spheres of economics and human activity.

M094 – Information technology

Group of educational programs

Master of Technical Science in Educational Program «7M06103 Applied data Analytics»

Awarded degree

2 years

Duration of study

Program Structure

BD – Basic Disciplines
UC – University Component
EC – Elective Component

№	Course Cycle	Course Component	Course Code	Course Title	Academic Credits
1	BD	UC	NONE	Higher Education Pedagogy	4
2	BD	UC	FLP	Foreign language (professiona l)	4
3	BD	UC	HPS	History and Philosophy of Science	4
4	BD	UC	PP 5206	Teaching Practicum (Internship)	4
5	BD	UC	PM	Psychology of Managemen	4
6	BD	ЕС	MII 3289 / CODE404 / Op 1	Methods and tools for data analysis / Data processing and understandin g / Optimizatio n 1	5
7	BD	ЕС	Op 2 / INN121 0 / HPCBD	Optimizatio n 2 / Introduction to neural networks / High Performance Computing for Big Data	5

MD – Major Disciplines
UC – University Component
EC – Elective Component

№	Course Cycle	Course Component	Course Code	Course Title	Academic Credits
1	MD	UC	—	Mathematics for data science	5
2	MD	UC	NONE	Programmin g for data analysis and databases	5
3	MD	UC	CODE404	Machine learning and artificial intelligence	5
4	MD	UC	TMS	Teaching methods and strategies	5
5	MD	UC	RP 1 - 2	Research Practice	10
6	MD	UC	CSDA	Case study on data Analytics	6
7	MD	UC	RP 2 - 2	Research Practice	10
8	MD	ЕС	GA / BDMT / MCDM P 4	Generative Algorithms / Big Data Methods and Tools / Markov chains and decision - making processes	4
9	MD	ЕС	HP / DDDM / RL 5120	Heterogeneo us Parallelizati on / Making decisions based on data / Reinforceme nt learning	4
10	MD	ЕС	SMPM / BPA / CTPSM / ITPM	Service model in project management / Business process analysis / Project Stakeholder Managemen t / IT Project Managemen	4

Scientific Research
UC – University Component

№	Course Cycle	Course Component	Course Code	Course Title	Academic Credits
1	Scientific Research	UC	NIRM 4	Research work of a master's student, including an internship and the completion of a master's thesis	4
2	Scientific Research	UC	NIRM 6	Research work of a master's student, including an internship and the completion of a master's thesis	6
3	Scientific Research	UC	NIRM 1-2	Research work of a master's student, including an internship and the completion of a master's thesis	2
4	Scientific Research	UC	NIRM 5216	Research work of a master's student, including an internship and the completion of a master's thesis	4
5	Scientific Research	UC	NIRM 3-2	Research work of a master's student, including an internship and the completion of a master's thesis	8
6	Qualification Examination	—	—	Writing and defense of master's thesis/projec	8