Statistics & Data Science
The program aims to train highly qualified specialists in statistics and data science who possess innovative problem-solving skills in statistics and data analysis. Students will gain the ability to apply their knowledge to analyze various problems in predictive analytics, marketing analytics, economics, biology, and other fields.
The educational process includes research work and the application of data analysis to real-life problems, which helps develop important academic skills such as working with databases, data analysis, programming, experimental design, academic writing, and understanding academic integrity and plagiarism.
Moreover, students will have the opportunity to participate in scientific projects that prepare them for successful admission to local and international Master’s or PhD programs in mathematical computer modeling, mathematics, and statistics.
Upon graduation, students will be equipped to pursue careers in educational and scientific institutions, IT companies, banks and insurance companies, and other organizations that utilize applied statistics, mathematics, and computer technology in their operations.
- The program enables students to apply their knowledge in probability theory, mathematical statistics, random processes, data analysis, calculus, linear algebra, differential equations, numerical analysis, optimization methods, discrete mathematics, and mathematical logic to solve practical problems encountered in written exams.
- Students will develop logical skills in programming using Python, allowing them to construct computer programs proficiently.
- They will acquire the ability to manipulate data sets, work with databases, and perform statistical analysis on collected data by constructing computer programs.
- Students will be able to utilize statistical methods, professional software, computer graphics, visualization techniques, and other relevant tools to address scientific and applied problems effectively.
- Through Modern Regression Analysis 1-2 courses, students will learn to design and test multiple linear regression models and develop strategies for constructing statistical models.
- The program encourages students to develop an understanding of government operations, market dynamics, institutional frameworks, societal relations, major ethical theories, and problems. Moreover, they will have the opportunity to demonstrate fluency in multiple languages through the study of non-area subjects such as economics, sociology, philosophy, Russian/Kazakh language, Turkish language, and more.
|Compulsory Course||Elective Course|
|– Calculus 1-3|
– Linear Algebra
– Discrete mathematics
|– Additional chapters of linear algebra|
– Spectral theory
– Introduction to Real Analysis
– Functional analysis
– Optimization methods
– Numerical methods
– Modern statistics
– Game theory
– Distributed Big Data Systems
– Mathematical Statistics in R
– Statistics and Visualization for Data Analysis
– Introduction to iOS Programming
– Introduction to Machine Learning
– Deep learning
– UX/UI design
– Linux Administration
– Natural Language Processing
– Business process design and management
– Project Management
– Product management
– Turkish language 1-4
– English language 1-2
– Kazakh language 1-2
– Russian language 1-2
Graduates with a degree in Statistics and Data Science have a wide range of career opportunities across various industries. Here are some potential career choices:
- Data Scientist: Analyzing complex data sets to extract insights and solve business problems using statistical models and machine learning techniques.
- Data Analyst: Collecting, cleaning, and analyzing data to identify patterns and trends.
- Business Analyst: Applying statistical analysis and data modeling to help organizations make informed business decisions.
- Data Engineer: Building and maintaining data infrastructure, databases, and pipelines to ensure efficient data storage and processing.
- Machine Learning Engineer: Developing and implementing machine learning algorithms and models for predictive analysis and automation.
- Statistician: Conducting statistical research, designing experiments, and analyzing data to provide insights and support decision-making.
- Risk Analyst: Assessing and managing risks using statistical models and quantitative analysis in industries such as finance and insurance.
- Research Scientist: Conducting research and experiments, analyzing data, and publishing findings in academic or industrial settings.
- Consultant: Providing data-driven insights and recommendations to clients in various industries.
- Data Manager: Overseeing data collection, storage, and governance to ensure data quality and integrity.
Moreover, graduates can continue their education in MSc and PhD programs.