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Item Open Access Основы языка программирования C++(Suleyman Demirel University, 2015) Жапаров М. К.Учебно-методическая разработка «Microlearning in Programming Language C++:» предназначена для бакалавров по специальностям 5В03000 — «Информационные Системы» и 5В040000 — «Вычислительная Техника и Программное Обеспечение». Учебный материал основная задача которого — объяснить новичку язык программирования С++, с основ и до новейших особенностей, в том числе такие понятия, как: массивы, структуры, списки, файлы, строки, функции, шаблоны.Item Open Access Microlearning in Programming Language C++(Suleyman Demirel University, 2015) Zhaparov M.K.Methodical-educational manual « Microlearning in Programming Language C++» is designed for bachelors of specialties 5В030000 — “Information Systems” and 5В040000 — “Computing Systems and Software”. When we use the principles of Microlearning approach in our everyday life, we actually do not think about it. This book was prepared for students, who wants to learn C++ programming language by using these Microlearning principles that can be easily observed in daily life.Item Open Access Basic Java: Selected topics(Almaty, Suleyman demirel university - 2000, 2000) Hajilarov E.K.Abstract. "Basic Java Programming" is an introductory course that provides beginners with a foundational understanding of Java, a versatile and widely-used programming language. This course covers the fundamental elements of Java, including variables, data types, control structures, and basic functions. Through a combination of theoretical lessons and hands-on coding exercises, students will become proficient in Java syntax and basic programming concepts.The course also introduces the principles of object-oriented programming (OOP) and guides students in creating Java classes and objects. Students will learn to design simple Java applications, fostering problem-solving skills and modularity. "Basic Java Programming" is an excellent starting point for those looking to learn the fundamentals of programming and pave the way for further Java exploration.Item Open Access Fundamentals of Computer Networks in microleaming style: textbook(Suleyman Demirel University, 2012) Zhamanov A.M.The textbook describes the fundamentals of Computer Networks in microleaming style. Textbook represents theoretical and practicable interest contains usefiıl materials, illustrations and tables. Textbook is intended for students of IT engineers who study “Computer Networks” course in universities. In modem world, people are always busy with their concems. In addition to ali fhis not an excessive amount of relevant information is processed by our brain every day. In this regard, it is difficult to find time for leaming the requıred knowledge. For that reason I decided to write book in microleaming style, which will provide readers to gel required information in short time, because of microleaming style gives ability to ехріаіп a lot of thıngs without using much words which is separated into small parts.Item Open Access Методы машинного обучения в задачах геофизических исследований(Алматы, Сулейман Демирел университеті - 2016, 2016) Мухамедиев Р.Аннотация. Курс "Методы машинного обучения в задачах геофизических исследований" представляет собой глубокое погружение в инновационное применение машинного обучения в сфере геофизики. В данной аннотации представлен обзор ключевых компонентов и целей курса. Геофизические исследования играют важную роль в понимании нашей планеты и решении ряда глобальных задач, таких как климатические изменения, землетрясения и изучение земной коры. Машинное обучение стало мощным инструментом для анализа и интерпретации огромных объемов данных, собираемых с помощью различных геофизических инструментов. В рамках этого курса студенты углубят свое понимание методов машинного обучения, таких как нейронные сети, решающие деревья, и ансамбли моделей, и научатся применять их к геофизическим данным. Кроме того, будут рассмотрены специализированные техники, такие как обработка геофизических изображений, пространственный анализ данных, и алгоритмы для обнаружения и прогнозирования природных бедствий.Item Open Access C++ БАҒДАРЛАМАЛАУ ТІЛІ(Suleyman Demirel University, 2015) Жапаров М. К.C++ - бұл тәуелді программалау тілі, оны сипаттауға арналған C тілінің функционалды жаңағыртуымен қарым-қатынас жасайды. C++ бағдарламалау тілін пайдалана отырып, әртүрлі қолдаулы жасақтамалар, компьютерге байланысқан жүйелер, операциялық жүйелер және басқа әртүрлі құрылғыларды программалауға болады. C++ тілін пайдалану арқылы әртүрлі құрылғыларға сәйкес жүзеге асырылатын бағдарламаларды жасауға болады.Item Embargo The Art of Personalized Student-Supervisor Matchings(ADAL Kitap, 2025) Serek A.G.; Berlikozha B.A.The process of student-supervisor matching is a critical yet complex task in higher education institutions, directly influencing research productivity, student satisfaction, and workload distribution. The ability to assign students to the most suitable supervisors is essential for fostering strong academic relationships, optimizing institutional resources, and improving research outcomes. However, traditional manual assignment methods often lead to inefficiencies, subjective biases, and an imbalance in workload distribution. As a result, automated recommendation systems have emerged as a promising solution to enhance the efficiency and fairness of student-supervisor pairings. This study evaluates three recommendation algorithms—Singular Value Decomposition (SVD)-based collaborative filtering, graph-based matching using the Hungarian Algorithm, and machine learning via Random Forest Regression—to determine their effectiveness in optimizing student-supervisor assignments. A rigorous empirical analysis is conducted across five key performance metrics: accuracy, fairness, stability, scalability, and computational efficiency. The findings reveal that while collaborative filtering performs well with established datasets, it struggles with novel cases due to its dependence on prior interactions. The Hungarian Algorithm guarantees optimal matching but faces scalability challenges, particularly in large academic institutions with thousands of students and supervisors. Meanwhile, Random Forest Regression effectively captures complex compatibility patterns but requires extensive labeled data, limiting its applicability in cases where historical matching data is sparse or unavailable. To overcome these limitations, the study proposes an adaptive hybrid framework that integrates the strengths of all three approaches. The hybrid model leverages collaborative filtering’s ability to recognize patterns in existing data, the Hungarian Algorithm’s precision in optimal pairings, and the predictive power of machine learning. By combining these methodologies, the proposed system enhances match accuracy, ensures fair workload distribution, and remains computationally efficient for large-scale institutional implementation. Additionally, the framework introduces dynamic adaptation mechanisms that allow the system to update recommendations based on real-time changes in student preferences and supervisor availability, making it more practical for real-world applications. The research contribution is a comprehensive, empirically validated hybrid framework that improves student-supervisor matching by balancing accuracy, fairness, and efficiency. This study provides educational institutions with actionable guidelines for scalable and equitable assignment processes, ultimately contributing to more effective mentorship experiences, improved research collaborations, and enhanced academic outcomes.Item Open Access A course in information theory(Almaty, Suleyman demirel university-2009, 2009) Arslanov M.Z.Abstract. Information Theory is a fundamental field of study that plays a pivotal role in various aspects of modern technology, communication, and data science. This abstract provides an overview of a course in Information Theory, which covers the core principles and applications of this field.This course aims to introduce students to the foundational concepts of Information Theory, including entropy, information content, and coding theory. It explores the mathematical foundations of information and communication, enabling students to quantify and manipulate information in a systematic manner. Topics covered include Shannon's entropy, data compression, channel capacity, and error-correcting codes. Through a combination of theoretical lectures, practical exercises, and real-world applications, students will gain a comprehensive understanding of the principles that underlie the transmission and storage of information in various communication systems. They will also learn how these principles are applied in fields such as data compression, cryptography, and error detection and correction.The course is designed to cater to a diverse range of students, from those with a strong mathematical background to those with a more practical interest in communication and information technology. By the end of the course, students will not only be equipped with a solid theoretical foundation but will also have the skills to apply Information Theory to solve real-world problems, making it an essential part of the curriculum for anyone interested in the intersection of mathematics, computer science, and communication technology.Item Open Access PROJECT MANAGEMENT PRACTICAL WORKBOOK(SDU University, 2026) Imankulova B.B.This Practical Workbook supports a hands-on approach to project management. It helps you learn how to plan, organize, control, and close a project through real project documents and simple management tools. The workbook follows the full project life cycle and uses consistent logic, each topic leads to a practical output that a project manager can use in real work. The main goal of the workbook is to build applied skills, not only theoretical knowledge. For this reason, every part includes short explanations and a clear task. As you progress through the sections, you will create a complete project documentation package: from the project charter and stakeholder register to the schedule baseline, risk register, status reports, and final report. At the end, you will have a structured set of materials that reflect professional project management practice. This workbook can support individual work or teamwork. It fits academic courses, training programs, and independent study. It also suits different project types, because the templates and steps remain the same even when the project topic changes.Item Open Access STATISTICS. Solved problems and exercises Part 2(Suleyman Demirel University, 2009) Aliyev H.N.Inferential statistics consists of methods that use sampie results to help make decisions or predictions about a population. The point and interval estimatıon procedures are forms of statistical inference. Another type of statistical inference is hypothesis testing. In hypothesis testing we begin by stating a hypothesis about a population characteristic. This hypothesis, called the null hypothesis, is assumed to be true unless suffıcient evidence can be found in a sampie to reject it. The situation is quite similar to that in a criminal trial. The defendant is assumed to be innocent; if suffıcient evidence to the contrary is presented, however, the jury will reject this hypothesis and conclude that the defendant is guilty. In statistical hypothesis testing, often the null hypothesis is an assumption about the value of a population parameter. A sampie is selected from the population, and a point estimate is computed. By comparing the value of the point estimate to the hypothesized value of the parameter we draw a conclusion with respect to whether or not there is a suffıcient evidence to reject the null hypothesis. A decision is made and often a specific action is taken depending upon wlıether or not the null hypothesis about the population parameter is accepted or rejected.