Computer Science - Junior

Course # COMP 3023

Credits 6

Pre-requisites and Co-requisites: None

Course Description

This course provides a comprehensive introduction to operating systems, focusing on the key principles, components, and techniques that underpin modern OS design. Students will learn how operating systems manage hardware resources, enable software applications, and ensure system stability, security, and performance. Through hands-on programming assignments and theoretical discussions, students will gain an in-depth understanding of process management, memory management, file systems, I/O systems, and concurrency.

Course Learning Outcomes

Upon the completion of the course, students will be able to:

• Understand the core functionalities and components of an operating system.
• Implement key OS concepts such as process scheduling and memory allocation.
• Develop programmes that manage concurrency using synchronization techniques.
• Analyze and solve common OS-level problems related to deadlocks and resource allocation.
• Demonstrate a practical understanding of file systems and I/O device management.

Course Assessments and Grading

Course # COMP 3052

Credits 6

Pre-requisites and Co-requisites: Object-Oriented Programming, Web Technologies

Course Description

The Software Engineering course provides a broad overview of software engineering concepts such as software development process, requirement engineering, quantum and cloud computing, high-performance computing, and the application of software engineering tools. The course prepares students to identify socio-economic problems in the real world and develop practical and sustainable solutions. Students are encouraged to design, implement, and evaluate small-scale software projects in teams of up to 3 people. Mobile application development with imperative and declarative paradigms using Kotlin programming language and Jetpack Compose Android toolkit are employed to illustrate software engineering concepts too. After completion of this course, students have the skills and project-based experience needed for entry into software developer careers.

Course Learning Outcomes

Upon the completion of the course, students will be able to:

• Identify, formulate, and solve software engineering problems, including the specification, design, implementation, and testing of software systems that meet specification, performance, maintenance, and quality requirements
• Work as a team member participating in the design, development, deployment, and maintenance of small and medium scale soft-/hardware projects
• Evaluate the professional, ethical, and social impact of potential solutions to software engineering problems in a global society, drawing on knowledge of contemporary issues and emerging software engineering trends, models, tools, and techniques
• Apply imperative and declarative programming paradigms using Kotlin and Jetpack Compose to Android apps
• Speedup application with multithreading, UMA, and NORMA computational parallel architectures

Course Assessments and Grading

Course # COMP 3073

Credits 6

Pre-requisites and Co-requisites: Artificial Intelligence, Statistics I

Course Description

According to Tom Mitchell “The field of Machine Learning is concerned with the question of how to construct computer programmes that automatically improve with experience”. This course covers the basic concepts and techniques of Machine Learning from both theoretical and practical perspective. The material includes classical machine learning approaches such as Linear Regression and Decision Trees, more advanced approaches such as recurrent neural network and convolution neural network, etc. The course explains how to build systems that learn and adapt using examples from real-world applications.

Course Learning Outcomes

Upon completion of the course, the students should be able to:

• Explain different machine learning techniques and select appropriate learning techniques to solve a problem.
• Examine the computation complexity of different machine learning algorithms.
• Analyze machine learning algorithms using different performance evaluation metrices.
• Apply the machine learning algorithms to real-world
• Implement machine learning algorithms using computer programing languages.

Course Assessments and Grading

Course # HUSS 3126E

Credits 6

Pre-requisites and Co-requisites: None

Course Description

The unprecedented changes brought by technological development often referred to as digitalization shape society, culture, and human identity in today’s digital world. Humans are becoming hybrids, communities are emerging online, many people live in virtual reality and the digital world certainly has altered social norms and created new forms of communication and values. This transformation required anthropologists to use relevant approaches to study the current digital phenomena. Thus, the course invites students to explore how digitalization shapes human subjectivity and social relationships between individuals, groups, organizations, and communities. The course will introduce students to the new theoretical framework for the study of digital phenomena and provide ground for the study of digital culture which is a controversial point of many current debates on digitalization and its impact on society. Thus, the goal is to use anthropological approaches to the study of digital phenomena.

Course Learning Outcomes

Upon completion of the course students will be able to:

• Identify key theoretical frameworks and important debates in digital anthropology
• Apply anthropological approaches to study digital phenomena and their societal impacts as well as to digital technologies and practices
• Analyze the ways that digital experiences can differ across social, cultural, and political contexts
• Reflect on how digital technologies and practices are changing anthropological
• research
• Employ the methods of digital anthropology to organize, conduct, and analyze research

Course Assessments and Grading

Course # DMNS 3032E

Credits 6

Pre-requisites and Co-requisites: Introduction to Probability and Statistics; Calculus-I

Course Description

This course introduces advanced topics in statistics for computer science majors. This course teaches essential background and techniques for understanding advanced statistical methods, enabling students to perform data analysis and evaluate research. The course starts with a review of introductory statistics and probability, then covers topics such as sampling distributions, point estimation, inference, ANOVA, and an introduction to machine learning. Python and/or R programming packages will be used to enhance understanding and application of statistical techniques taught throughout the course.

Course Learning Outcomes

Upon completion of the course, students should be able to:

• Define sampling distribution and its properties.
• Test statistical hypotheses and determine significance.
• Analyze data using programming language and interpret results.
• Select appropriate statistical models and justify choice.
• Regress data using programming language and interpret results.
• Predict and draw conclusions using linear and multiple regression.
• Analyze data using programming packages.

Course Assessments and Grading

Course # ECON 4010

Credits 6

Pre-requisites and Co-requisites: None

Course Description

This course uses a project-based learning approach to help students provide useful applications and concrete contributions in support of local development. For Communication and Media students the focus is on audio and video production. Students work in teams (of four or five students) to integrate music, graphics and video technologies into entrepreneurial projects aimed at supporting the local communities. For Computer Sciences students, a variety of mobile applications, augmented virtual reality applications, Big Data applications, Internet of Things, Video Game Experiential Marketing applications, Machine Learning Methods, Mobile Operating Systems and Mobile Signals and Sensors applications and many more are on offer. Whenever possible, multidisciplinary collaborations between students will be suggested and recommended. The aim is to boost local development, preferably in the Naryn Oblast.

The student projects can be implemented in a variety of sectors such as tourism, agriculture, food processing, manufacturing, hospitality services (sports, leisure & recreation), public services, health, education, transportation, or any sector that contributes to support the development of local communities. However, an emphasis will be put on the tourism sector which has the potential to substantially contribute to Naryn’s economic progress.

Course Learning Outcomes

Upon completion the course, students should be able to:

• Define local development priorities and strategies
• Explain how specific digital projects can contribute to these goals
• Collect relevant data on which to build a digital project
• Determine the needs expressed by actors on the ground and design potential solutions to address those needs
• Relate their theoretical knowledge to the design and implementation of concrete projects on the ground
• Develop appropriate technical solutions to serve the specific needs of economic and social actors in the region
• Present to the public at large specific finalized projects

Course Assessments and Grading

Course # COOP 3001

Credits 2

Course # HUSS 3082

Credits 0

Pre-requisites and Co-requisites: None

Course description

The purpose of physical education is to strengthen health and develop the physical and mental abilities of students. Physical exercises and sports games are the way to a powerful and functional body, clear mind and strong spirit. The course is both practical and theoretical, it covers basic concepts of anatomy and physiology as well as health and safety requirements.  

Course learning outcomes

Upon completion of the course, students should be able to: 

• Perform a range of physical activities
• Understand health and safety requirements for a range of physical activities
• Describe the role and progress of sport in Central Asia
• Choose an appropriate physical activities programme for their age and gender
• Identify tiredness and its symptoms to control the body during athletic exercises
• Describe the technique of running for a long and a short distance and jumping
• Accomplish running for a short and a long distance and jumping according to all necessary norms
• Describe the rules of a range of sports games

Course Assessments and Grading

The course will be graded with PASS/FAIL.