Computer Science and Artificial Intelligence Major

Requirements - 6 courses / 18 credits (36 ECTS)
The course introduces the student to the foundations of computational techniques, using idiomatic Python. The most common numerical methods are introduced and explained in detail. Examples from Physics, Mathematics, Material Science, and Engineering are investigated providing students with hands-on experience on realistic scientific computing applications. Prerequisite(s): MATH150, PH100, IT150 Credits: 3
This course is an introduction to data mining techniques and applications. Students will learn the basic notions and tools which are used in data mining. Topics covered include data preparation and cleaning, data analysis, classification, clustering, text, and web mining. Students will become familiar with several data mining techniques and algorithms, and they will gain hands-on experience using popular data mining languages. By the end of the course students will be able to apply data mining methods to real-world problems and familiarize themselves with the concept of data-driven decision-making. Prerequisite(s): Two major IT courses Credits: 3
This course Machine offers a comprehensive study of machine learning and natural language processing (NLP). Throughout the course, students will explore the principles, algorithms, and techniques of machine learning, focusing on supervised and unsupervised learning, neural networks, and deep learning models. Students will gain insight into NLP fundamentals, such as text preprocessing, sentiment analysis, and named entity recognition. The course aims to equip students with the skills to develop and implement machine learning models specifically tailored for language-related tasks, fostering their ability to create sophisticated language-based applications and systems. Prerequisite(s): Two major IT courses Credits: 3
This course discusses the links between two important technologies with significant impact on the digital world. Students will learn how to handle and analyze huge amounts of data that require special tools and techniques. Big data, capturing, storage, processing, and analysis of massive datasets that surpass the capabilities of traditional data management systems will be thoroughly examined during the course. Students will gain a comprehensive understanding of big data concepts, such as distributed computing, data mining, and data visualization. Additionally, the course will discuss cloud computing, introducing students to the principles of virtualization, cloud architecture, and the deployment of scalable, on-demand computing resources. By the end of the course, students will be able to address the challenges and opportunities presented by big data and cloud computing, preparing them to tackle real-world projects. Prerequisite(s): Two major IT courses Credits: 3
Introduces basic concepts and methods of artificial intelligence from a computer science perspective. Emphasis will be placed on the selection of data representations and algorithms useful in the design and implementation of intelligent systems. The course will contain an overview of AI languages like Prolog and Lisp, and some discussion of important applications of artificial intelligence methodology. Prerequisite(s): IT150, IT160, MATH200 Credits: 3
Introduces discrete and continuous probability spaces, statistical independence, distributions, discrete and continuous random variables, expectations, moment generating functions, limiting distributions, estimation of parameters, confidence intervals, hypothesis testing with applications, linear regression and correlation and multiple linear regressions. Students learn to define probability as a measure of uncertainty and as a set function, apply the algebra of sets and use various counting techniques to determine elementary probabilities. The class includes calculation of probabilities, means, variances, and moment-generating functions, and investigates approximation theorems. Students also study basic statistical inference theory. Prerequisite: GE131, MATH150 Credits: 3
Electives - 1 course / 3 credits (6 ECTS)
Enhances students’ Java programming skills and prepares them to successfully obtain professional certifications. The course teaches advanced object-oriented concepts such as inheritance and polymorphism and applies them to the Java programming language so that students can gain a better understanding of interfaces & abstract classes. Other important aspects covered are concurrency (threads), generics, inner classes and exceptions. Prerequisite(s): IT150, IT200 Credits: 3
In this course you will develop the know-how to monitor, detect and respond to cybersecurity threats. Uncovering cybercrime, cyber espionage, and other networking threats are just some of the exciting cybersecurity jobs spanning across every industry. Learn the skills to join this fast-growing field and take advantage of the opportunities found in security operation centers. Feel confident that you are helping make the world a safer place by pursuing a role in this field. Prerequisites: IT150, IT160, IT265 Credits: 3
Introduces Human-Computer Interaction, the philosophy of designing user interfaces, available design techniques and methodologies, various interaction styles, available design guidelines and user interface management systems. Usability and accessibility of user interfaces is then examined and several usability evaluation methods are analyzed. Prerequisite(s): IT100, IT150, IT320 Credits: 3
The course introduces the basic methods and platforms used in game design. It focuses on analyzing the mechanics of gameplay and how these mechanics affect the player experience. It also introduces the student to the main game platforms available in the market. The students gain hands-on experience through practical assignments such as creating paper and digital prototypes and improving the overall gaming experience by iterative design processes. Special attention is paid to the Unity platform. Students practice on Unity by setting up a 2D project, creating Prefabs, working with movement buttons, action buttons and the physics of collisions, using a sprite sheet, and integrating the Dolby Audio API. Prerequisite(s): IT150 Credits: 3

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