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Big Data Analysis

6B06103 Big Data Analysis

Profile subjects: Mathematics, Информатика.

Threshold Score (Grant): 100.

Objective of Educational Program

The goal of the study program is to provide practice-oriented training of highly qualified specialists in the field of computer science for enterprises with general cultural and professional competences in the field of big data analysis, as well as create conditions for continuous professional self-improvement, development of social and personal competencies of specialists, expansion of social mobility and competitiveness on labor market.

List of a specialist’s positions

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

Learning outcomes

Apply hardware and software services to ensure the continuity of the process of developing software systems.
Explain and understand the regulatory framework, including documents, standardization and certification procedures in the development of information and communication technologies.
Apply algorithms for collecting data from open sources, methods for preprocessing the collected data, basic and advanced models for predicting and making decisions based on this data.
Use knowledge of the regularities of random phenomena, their properties and operations on them, models of random processes and modern software environments to solve problems of statistical data processing and building predictive models.
Demonstrate knowledge of the architecture of computer systems, manage operating systems.
Apply domestic and foreign standards for software development in organizations.
Apply mathematical tools for analyzing software systems and data based on statistical and probabilistic models.
Design, develop and analyze algorithms for solving computational and logical problems, evaluate the efficiency and complexity of algorithms based on formal models of algorithms and calculated functions.
Independently analyze modern sources, draw conclusions, argue them and make decisions based on information.
Apply methods and algorithms of artificial intelligence, data mining, machine learning, neural network and fuzzy data processing to solve problems of classification, forecasting, cluster analysis and recognition of various objects.

B057 - Information Technologies

Educational group

Bachelor of Science in Information and Communication Technology in Educational Program "6B06103 - Big Data Analysis"

Awarded degree

3 years

Duration of studies

Program Structure

GED – General Education Disciplines
CC – Compulsory Component
EC– Elective Component

№	Course Cycle	Course Component	Course Code	Course Title	Academic Credits
1	GED	CC	Fiz 1112	Physical Education	2
2	GED	СС	HSS 1162 Cult 1111	Cultural Studies	2
3	GED	СС	IT1115 IKT 1105	Information and Communication Technologies	5
4	GED	CC	HSS 1115 IYa 1103	Foreign Language 1	5
5	GED	CC	HSS1145 (SIK2022)	History of Kazakhstan	5
6	GED	CC	HSS 1122 HSS 1132 (Soz 2109)	Sociology	2
7	GED	CC	Fiz1113	Physical Education	2
8	GED	CC	HSS 1215 FL2023	Foreign Language 2	5
9	GED	CC	HSS 1182 (MSP2313)	Psychology	2
10	GED	CC	Fiz1114	Physical Education	2
11	GED	CC	HSS 1132 MSP 2315	Political Science	2
12	GED	CC	Fiz 2116	Physical Education	2
13	GED	CC	K(R)Ya2105	Kazakh (Russian) Language 1	5
14	GED	CC	K(R)Ya2106	Kazakh (Russian) Language 2	5
15	GED	CC	Fil 2102	Philosophy	5
16	GED	EC	FL25 / Pred 2116 / TP 3113	Financial Literacy / Entrepreneurship / Technological Entrepreneurship	5

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

№	Course Cycle	Course Component	Course Code	Course Title	Academic Credits
1	BD	UC	—	Introduction to Programming	5
2	BD	UC	MATH 1115 MA1 1202	Calculus 1	5
3	BD	UC	CS 2155 OOP	Object-Oriented Programming	5
4	BD	UC	SUBD 2217	Database Management Systems	5
5	BD	UC	MATH 1215 MA1 1203	Calculus 2	5
6	BD	UC	MATH 2125 LA 1201	Linear Algebra	5
7	BD	UC	UP SIS 1211	Educational Practice	2
8	BD	UC	MATH 2145 DM 2207	Discrete Mathematics	5
9	BD	UC	CS 2055 ASiD 1205	Algorithms and Data Structures	5
10	BD	UC	PPP BDA	Python Programming	5
11	BD	UC	OSiKS 2302	Operating Systems and Computer Networks	5
12	BD	UC	PT 2025 BDA	Probability Theory	5
13	BD	UC	SA BDA2025	Statistical Analysis	5
14	BD	UC	ItO2025	Introduction to Optimization	5
15	BD	UC	VM 2205	Computational Mathematics	5
16	BD	UC	AK 3221	Academic Writing	5
17	BD	UC	UP 2301	Project Management	5
18	BD	EC	AMvKN 2210 / GTN BDA 2025	Analytic Methods in Computer Science / Graph Theory and Networks	5
19	BD	EC	BA 2205 / RBDNoSQL 2217	Business Intelligence / Advanced Databases (NoSQL)	5
20	BD	EC	CLAIM / SP2025	Computational Linear Algebra and Iterative Methods / Stochastic Processes	5

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

№	Course Cycle	Course Component	Course Code	Пән атауы	Academic Credits
1	MD	UC	COA	Computer Organisation and Architecture	5
2	MD	UC	SiNODP1 2304	Statistics and Data Science 1 (Python)	5
3	MD	UC	PIDD 2200	Information Retrieval and Data Mining	5
4	MD	UC	SiNODP2 2305	Statistics and Data Science 2 (Python)	5
5	MD	UC	PP 2305	Industrial Practice	4
6	MD	UC	DL DVND2025	Deep Learning	5
7	MD	UC	PMO 3300	Applied Machine Learning	5
8	MD	UC	Mill 3222	Research Methods and Tools	5
9	MD	UC	RLBD BDA2025	Reinforcement Learning for Big Data	5
10	MD	UC	BDiRA 3215	Big Data and Distributed Algorithms	5
11	MD	UC	NLP	Natural Language Processing	4
12	MD	UC	PP 3306	Industrial Practice	8
13	MD	UC	PP 3307	Undergraduate Practice	4
14	MD	EC	VV 3110 / IB 3308 / BDvPO1 3310 / RDADM	High Performance Computing / Introduction to Bioinformatics / Big Data in Law Enforcement 1 / Real-time Data Analysis and Decision Making	5
15	MD	EC	AB 3311 / TSA BDA2025 / GM / BDvPO2 3315	Advanced Bioinformatics / Time Series Analysis / Generative Models / Big Data in Law Enforcement 2	5
16	MD	EC	UIR 3330 / OIBT 3222	IT Risk Management / Information Security Fundamentals	5