Semester 1

• [CM206] [6 ECTS] Data Engineering
  The aim of this course is to teach the fundamentals of data modelling, cleaning, transformation and storage. As such students will learn various means to model SQL and NoSQL data, organize them in different data stores, design and manage data pipelines. Students will also learn how to use state-of-the-art tools implemented in premise or cloud.
• [CM207] [6 ECTS] Advanced Databases
  This course aims are to continue with in-depth study about databases. The course is continuation of databases course from the first cycle of study and starts with some reminds of the conceptual database design (well-known entity relationship model) and schema normalization. The course continues with data storage methods, representing data elements, database system architecture, query processing and optimization, transaction processing concepts, concurrency control techniques, database recovery techniques and database security and authorization.
• [CM208] [6 ECTS] Machine Learning
  This course provides an introduction to machine learning. The course is divided into several topics and provides an overview of many concepts, techniques and algorithms from each of them. At the end of the course, students will create systems that will make decisions based on knowledge. The course will also analyze numerous case studies and applications where students will learn how to apply learning algorithms to computer vision, medical informatics, and signal analysis.
• [6 ECTS] General Elective (from SP)*
  • [EM575] Programming in Java
    Aims of the course program: To provide students regarding Java programming language with a deep, critical and systematic understanding of the principles and techniques for programming effective software applications. This course introduces fundamental structures and object-oriented programming concepts and techniques, using Java, and is intended for all who plan to use computer programming in their studies and careers.
  • [EM576] Programming in .NET
    This course introduces students to key concepts, real-world applications, and latest features of C# and .NET with hands-on exercises using Visual Studio. They will learn object-oriented programming core concepts, writing, testing, and debugging functions, implementing interfaces, and inheriting classes. The course will cover the .NET APIs for performing tasks like managing and querying data, monitoring and improving performance. At the end of the course, the students will be able to build and deploy cross-platform apps, such as websites and services using ASP.NET Core.
  • [EM577] Cryptography
    Introduces students to the compelling and evolving field of cryptography. In an age of viruses and hackers, electronic eavesdropping, and electronic fraud on a global scale, security is paramount. The purpose of this course is to provide a practical survey of both the principles and practice of cryptography. The first part of the course explores the basic issues to be addressed by a security capability and provides a tutorial and survey of cryptography and security technology. The latter part of the course deals with the practice of network security, covering practical applications that have been implemented and are in use to provide network security.
  • [EM578] Programming in Python
    The aim of this course is to introduce core Python programming basics, including data types, control structures, algorithm development, program design with functions and the fundamental principles of Object-Oriented Programming. In this course students will solve problems, explore real-world software development challenges, and create practical and contemporary applications using web development frameworks.
  • [EM579] Mobile Applications Development
    Course aims: 1. To facilitate students to understand android SDK 2. To help students to gain a basic understanding of Android application development 3. To inculcate working knowledge of Android Studio development tool
  • [EM580] Game Programming
    Course aims: • To study of basic game development principles both in 2D and 3D Worlds • To ensure that students will know how to create and use various games objects • To ensure that students will understand user interaction • Study of game data structures and game physics • Learn about programming and creating detailed code for game projects • Basic artificial intelligence concepts
  • [EM581] Parallel Processing
    This course is intended for students interested in the efficient use of modern parallel systems ranging from multi-core processors to large-scale distributed memory clusters. The course covers theoretical principles of parallel computing as well as different parallel programming techniques. It begins with a survey of common parallel architectures and types of parallelism and follows with an overview of formal approaches to assess scalability and efficiency of parallel algorithms and their implementations. In the second part, the course focus is on selected parallel programming techniques and APIs, including shared address space, many-core accelerators, distributed memory clusters and big data analytics platforms. Each component of the course involves solving practical problems on a corresponding parallel architecture.
  • [EM582] Е-commerce
    - To develop strategic, administrative, and operational planning for new businesses, or to improve existing ones with their technologies. - Develop knowledge about the basics of E-Commerce, which are made possible by new Information Technologies - They recognize the need for the organization to continuously adapt to the changes occurring in the current business atmosphere. - Discover opportunities in the environment so that you can apply them in valid innovations and do business. - Analyze business to identify internal and external factors that can be modified to be able to move to an electronic business model. - Develop strategic, administrative, and operational planning for a new, or already existing business by establishing strategies that use information technology in the most important business processes, in order to improve their current operation and turn it into a competitive advantage. - Develop an analytical and technical foundation to understand the unpredictable world of e-commerce, by sharing three domains: o Economics: business plan, electronic banking and money, marketing and advertising, customer relationship management o Sociology: secrecy, protection of intellectual property, laws and regulatory initiatives o Technology: Internet infrastructure, network security, web services, mobile commerce network security, services, mobile commerce
  • [EM583] Computer Network Management (After Comp. Networks)
    In this course students will study the principles and practice of systems administration and management, analyzing and designing networks in a real lab environment. Students will use cloud servers and virtualized machines to explore the efficiency and security of your systems and get insights into the practices of industry companies like Cisco. Coursework includes design, installation, configuration and management of local- and wide-area network hardware and software.
  • [EM574] NoSQL Databases
    The course is a continue with extension of the knowledge in field of databases. The focus is addressed in NoSQL databases and help the student to complete its knowledge puzzle with the various database technologies. It starts with some concepts, principles and taxonomies in field on NoSQL databases and continue with NoSQL database technologies of different types. The course covers: the principles behind the NoSQL databases, modern distributed database theory, indexing and MapReduce programming model; architectures and common features of the main types of NoSQL databases (key-value stores, document databases, column-family stores, graph databases); explains of selected NoSQL database systems including practical experience; and other topics related to NoSQL databases. At the end of this course, students should be able to: • Understand NoSQL databases and technologies. • Understand distributed database systems and theory, • Understand indexes, MapReduce programming model, • Understand main types of NoSQL databases based on key-value stores, document stores, column-family stores and graph stores, and • Understand the difference between relational and NoSQL databases and important of use.
  • [EM584] Mobile and Wireless Networks
    The goal of the course is to provide students with fundamental knowledge into core concepts of the latest and next generation mobile and wireless networks. Throughout the course, students will be exposed to theoretical and practical aspects regarding the architecture and applications of Cellular, LTE, and 4G/5G systems. In addition, basic concepts of Wireless LAN (WLAN), sensor networks (IoT), Mobile Peer-to-Peer (MP2P), and emerging opportunistically connected mobile/vehicular networks (MANET and VANET), will be explored.
  • [EM585] IT Professional Ethics
    This course provides a comprehensive overview of the current ethical issues we face in the use of information technology (IT). It examines an array of long-standing and emerging issues facing IT users ranging from free speech, privacy, intellectual property, hacking, and the digital divide, to ethics in social networking and online communities. The course discusses the ethical dilemmas and responsibilities of IT users, and promotes the critical examination and responsible use of IT.
  • [EM586] Digital Logic Design and Simulation
    This course provides students with a comprehensive overview of the fundamental concepts of classical digital design and demonstrates how digital circuits are designed and analyzed today. The aim is to introduce students to the modern digital hardware hierarchy and enlighten them with the most up-to-date computer hardware design methodologies. Also, the course content gives students a basic idea of how to design and simulate logic circuits and practically implement such circuits.
  • [EM587] Numerical Methods
    This module is designed such that it can provide students with the basic concepts and methods from numerical computing. The primary intent is to provide students with a sound introduction to the numerical methods. They have a big application in solving different problems which can be solved just by using the computers, therefore solving numerical problems will help students not just to apply them in different other areas, but simply it will help them to become better computer scientists. After e brief look at the ways the numbers are placed and manipulated in computers we will deal with fundamental computational problems, such are solving the equations, system of equations followed by an approximation theory. We will deal with the accuracy of numerical solutions and also the aim is to evaluate the functions, numerical differentiation and integration.
  • [EM588] Internet of things
    The goal of the course is to provide students with fundamental knowledge into core concepts of the Internet of Things. Throughout the course, students will be exposed to theoretical and practical aspects regarding the architecture and applications of sensor networks and 4G/5G systems. Students will be able to use learned concepts through analysis of architectures and computer communication technologies for wireless Internet applications in the most diverse domains such as: smart environments, industrial and home networks of devices, as well as application in sensor and actuator networks.
  • [EM572] Introduction to Artificial Intelligence
    Introduction to the basics of artificial intelligence, intelligent agents, techniques for presenting knowledge and intelligent search and decision-making, game theory, formal logic, probability, and logical reasoning systems, learning by observation, training of neurons and learning stimulation. Also, students will be familiar with the basic concepts of LISP.
  • [EM589] Cybersecurity
    In Cybersecurity, introduces the technology, operational procedures, and management practices needed for successful cybersecurity. Makes extensive use of standards and best practices documents that are often used to guide or mandate cybersecurity implementation. Going beyond these, he offers in-depth tutorials on the “how” of implementation, integrated into a unified framework and realistic plan of action. Each chapter contains a clear technical overview, as well as a detailed discussion of action items and appropriate policies. Cybersecurity aligns with the comprehensive Information Security Forum document “The Standard of Good Practice for Information Security,” extending ISF’s work with extensive insights from ISO, NIST, COBIT, other official standards and guidelines, and modern professional, academic, and industry literature.
  • [EM573] Introduction to Information Systems
    Course aims: 1. To learn the basic concepts and the terminology of Information Systems a. Basic Information Systems concepts: hardware, software, networks b. E-World: e-business and e-commerce c. Developing Processes 2. To learn about the Information Systems and technologies that improve business values and various processes inside organizations. 3. Applying concepts with various managing disciplines, during analysis, interpretation, assessments and decisions. 4. Understand the process of redesigning organizations using information systems. 5. Describe the role of information systems in decision making. 6. Examine information security, ethical, and social issues. 7. Be familiar with the Internet, electronic commerce, and e-business. 8. Prepare students to work on small scale projects, individual or group work, who by nature could fall into these categories: case studies, scientific research project, development projects or internship projects.
  • [E2802] Business Analytics
    Business Analytics teaches the fundamental concepts of modern business analytics and provides vital tools for understanding how data analysis works in today's organizations. The course takes a comprehensive approach, examining business analysis from both descriptive and predictive perspectives. Students learn how to apply fundamental principles, communicate with analytics professionals, and effectively use and interpret analytics models to make better business decisions. As tools, among others, Excel will be used, strengthening the students' skills in the program and the basic understanding of the basic concepts. Additionally, Analytic Solver as well as commercial data-mining tools will be used so that students are prepared to use these same tools when they graduate.
• [6 ECTS] Professional Elective (from the module)**
  • [EM598] Information Retrieval
    This course attempts to be a comprehensive overview of the field. Its work will require written assignments, programming and a final project. Assignments will provide exposure to commonly used IR datasets. The course offers a number of practical projects in Information Retrieval, focusing on (but not limited to) website search engines. All projects involve programming: the end result is a relatively large-scale, well-documented and efficient software package. Some of the projects may also involve some research (e.g., reading a research paper and implementing its ideas).
  • [EM599] Data Analysis with Python/R
    Aims of the course: ● To be able to understand basic data analytics methodologies ● To be able to use tools that are used for data analytics ● To be able to practically apply their knowledge from the fields of statistics and data analytics ● To be able to present their results through various reporting and data visualization techniques
  • [EM600] Mathematics for Data Science
    Course aims: On successful completion of this course students will be able to: 1. Demonstrate understanding of basic mathematical concepts in data science, relating to linear algebra, probability, and calculus. 2. Employ methods related to these concepts in a variety of data science applications. 3. Apply logical thinking to problem-solving in context. 4. Demonstrate skills in writing topics from applied mathematics and projects
  • [EM601] Social and Information Network Analysis
    The course focuses on the structure and evolution of networks, drawing on knowledge from disciplines as diverse as sociology, mathematics, computer science, economics, and physics. Online interactive demonstrations and hands-on analysis of real-world data sets will focus on a range of tasks: from identifying important nodes in the network, to detecting communities, to tracing information diffusion and opinion formation.
  • [EM602] Neural Networks and Deep Learning
    The course focuses on the theory, structure and algorithms of neural networks and deep learning. The theory and algorithms of neural networks are particularly important for understanding deep learning concepts, so these this course offers important design concepts of neural architectures in different applications. And it covers the theory and algorithms of deep learning as well, providing detailed discussions of the relationships of neural networks with traditional machine learning algorithms. This theory is linked and described with real world practical applications.
  • [EM603] Natural Language Processing
    This course helps students to explore into the exciting world of Natural Language Processing (NLP) giving an overview of major topics in the field. Students will understand how computers work with human language, learn techniques and libraries for data analysis and create natural language processing tools as well. Interactive demonstrations and hands-on analysis of real-world applications will focus on a range of tasks: language translation, text classification, text clustering, sentiment analysis, speech recognition, summarization etc.
  • [EMCS-02] Data Visualization
    The aim of this course is to introduce students to the field of data visualization. Students will learn visualization design and evaluation principles, and learn how to acquire, parse, and analyze large datasets. Students will also learn techniques for visualizing multivariate, temporal, text-based, geospatial, hierarchical, and network/graph-based data. Additionally, students will utilize Processing, D3, R and ggplot2, and many other tools to prototype many of these techniques on existing datasets.

Semester 2

• [CM194] [6 ECTS] Practicum
  On successful completion of this course, students should be able to relate academic course material to real teaching conditions at workplace; develop experience in various aspects of teaching ICT such as planning, organizing, material selection and lesson delivery, as well as adapting to workplace culture; develop appropriate work related habits and professional attitudes by observations of skilled teachers; communicate effectively in a variety of forms to students, parents and colleagues; and work in a team.
• [CM209] [6 ECTS] Big Data Systems
  Recent technological advances, decreasing hardware costs and the Internet of things has led to a rapid explosion in the amount of data generated in a variety of domains, including data-driven science, telecommunications, social media, large-scale e-commerce, medical records, and e-health. Big data refers to the ability of exploiting these massive amounts of extremely heterogeneous in structure and content data that are routinely generated at an unprecedented scale from an ever-expanding variety of data sources. Business and industry used their big data to extract a better understanding of customers’ needs and behavior, to develop targeted new products and to cut operational costs. The competitive advantages and productivity gain that big data brought led to a great number of a big data projects and a shortage of people with the required skills. This course is aimed to introduce students into this rapidly expanding and exciting area; it has been designed to build the knowledge and understanding of big data systems and architectures and to equip by the core technologies utilized in big data projects.
• [CM204] [6 ECTS] Computer Security
  This course teaches principles of computer security from an applied viewpoint and provides hands-on experience with security threats and countermeasures. The course additionally covers principles and skills useful for making informed security decisions and for understanding how security interacts with the world around it. Applied topics include cryptography, authorization control, operating systems security, and web and network security. Other topics include general security principles, human factors such as trust and social engineering, the security of complex systems, and the economics of security. The course aims to balance theory and practice.
• [6 ECTS] General Elective (from SP)*
  • [EM575] Programming in Java
    Aims of the course program: To provide students regarding Java programming language with a deep, critical and systematic understanding of the principles and techniques for programming effective software applications. This course introduces fundamental structures and object-oriented programming concepts and techniques, using Java, and is intended for all who plan to use computer programming in their studies and careers.
  • [EM576] Programming in .NET
    This course introduces students to key concepts, real-world applications, and latest features of C# and .NET with hands-on exercises using Visual Studio. They will learn object-oriented programming core concepts, writing, testing, and debugging functions, implementing interfaces, and inheriting classes. The course will cover the .NET APIs for performing tasks like managing and querying data, monitoring and improving performance. At the end of the course, the students will be able to build and deploy cross-platform apps, such as websites and services using ASP.NET Core.
  • [EM577] Cryptography
    Introduces students to the compelling and evolving field of cryptography. In an age of viruses and hackers, electronic eavesdropping, and electronic fraud on a global scale, security is paramount. The purpose of this course is to provide a practical survey of both the principles and practice of cryptography. The first part of the course explores the basic issues to be addressed by a security capability and provides a tutorial and survey of cryptography and security technology. The latter part of the course deals with the practice of network security, covering practical applications that have been implemented and are in use to provide network security.
  • [EM578] Programming in Python
    The aim of this course is to introduce core Python programming basics, including data types, control structures, algorithm development, program design with functions and the fundamental principles of Object-Oriented Programming. In this course students will solve problems, explore real-world software development challenges, and create practical and contemporary applications using web development frameworks.
  • [EM579] Mobile Applications Development
    Course aims: 1. To facilitate students to understand android SDK 2. To help students to gain a basic understanding of Android application development 3. To inculcate working knowledge of Android Studio development tool
  • [EM580] Game Programming
    Course aims: • To study of basic game development principles both in 2D and 3D Worlds • To ensure that students will know how to create and use various games objects • To ensure that students will understand user interaction • Study of game data structures and game physics • Learn about programming and creating detailed code for game projects • Basic artificial intelligence concepts
  • [EM581] Parallel Processing
    This course is intended for students interested in the efficient use of modern parallel systems ranging from multi-core processors to large-scale distributed memory clusters. The course covers theoretical principles of parallel computing as well as different parallel programming techniques. It begins with a survey of common parallel architectures and types of parallelism and follows with an overview of formal approaches to assess scalability and efficiency of parallel algorithms and their implementations. In the second part, the course focus is on selected parallel programming techniques and APIs, including shared address space, many-core accelerators, distributed memory clusters and big data analytics platforms. Each component of the course involves solving practical problems on a corresponding parallel architecture.
  • [EM582] Е-commerce
    - To develop strategic, administrative, and operational planning for new businesses, or to improve existing ones with their technologies. - Develop knowledge about the basics of E-Commerce, which are made possible by new Information Technologies - They recognize the need for the organization to continuously adapt to the changes occurring in the current business atmosphere. - Discover opportunities in the environment so that you can apply them in valid innovations and do business. - Analyze business to identify internal and external factors that can be modified to be able to move to an electronic business model. - Develop strategic, administrative, and operational planning for a new, or already existing business by establishing strategies that use information technology in the most important business processes, in order to improve their current operation and turn it into a competitive advantage. - Develop an analytical and technical foundation to understand the unpredictable world of e-commerce, by sharing three domains: o Economics: business plan, electronic banking and money, marketing and advertising, customer relationship management o Sociology: secrecy, protection of intellectual property, laws and regulatory initiatives o Technology: Internet infrastructure, network security, web services, mobile commerce network security, services, mobile commerce
  • [EM583] Computer Network Management (After Comp. Networks)
    In this course students will study the principles and practice of systems administration and management, analyzing and designing networks in a real lab environment. Students will use cloud servers and virtualized machines to explore the efficiency and security of your systems and get insights into the practices of industry companies like Cisco. Coursework includes design, installation, configuration and management of local- and wide-area network hardware and software.
  • [EM574] NoSQL Databases
    The course is a continue with extension of the knowledge in field of databases. The focus is addressed in NoSQL databases and help the student to complete its knowledge puzzle with the various database technologies. It starts with some concepts, principles and taxonomies in field on NoSQL databases and continue with NoSQL database technologies of different types. The course covers: the principles behind the NoSQL databases, modern distributed database theory, indexing and MapReduce programming model; architectures and common features of the main types of NoSQL databases (key-value stores, document databases, column-family stores, graph databases); explains of selected NoSQL database systems including practical experience; and other topics related to NoSQL databases. At the end of this course, students should be able to: • Understand NoSQL databases and technologies. • Understand distributed database systems and theory, • Understand indexes, MapReduce programming model, • Understand main types of NoSQL databases based on key-value stores, document stores, column-family stores and graph stores, and • Understand the difference between relational and NoSQL databases and important of use.
  • [EM584] Mobile and Wireless Networks
    The goal of the course is to provide students with fundamental knowledge into core concepts of the latest and next generation mobile and wireless networks. Throughout the course, students will be exposed to theoretical and practical aspects regarding the architecture and applications of Cellular, LTE, and 4G/5G systems. In addition, basic concepts of Wireless LAN (WLAN), sensor networks (IoT), Mobile Peer-to-Peer (MP2P), and emerging opportunistically connected mobile/vehicular networks (MANET and VANET), will be explored.
  • [EM585] IT Professional Ethics
    This course provides a comprehensive overview of the current ethical issues we face in the use of information technology (IT). It examines an array of long-standing and emerging issues facing IT users ranging from free speech, privacy, intellectual property, hacking, and the digital divide, to ethics in social networking and online communities. The course discusses the ethical dilemmas and responsibilities of IT users, and promotes the critical examination and responsible use of IT.
  • [EM586] Digital Logic Design and Simulation
    This course provides students with a comprehensive overview of the fundamental concepts of classical digital design and demonstrates how digital circuits are designed and analyzed today. The aim is to introduce students to the modern digital hardware hierarchy and enlighten them with the most up-to-date computer hardware design methodologies. Also, the course content gives students a basic idea of how to design and simulate logic circuits and practically implement such circuits.
  • [EM587] Numerical Methods
    This module is designed such that it can provide students with the basic concepts and methods from numerical computing. The primary intent is to provide students with a sound introduction to the numerical methods. They have a big application in solving different problems which can be solved just by using the computers, therefore solving numerical problems will help students not just to apply them in different other areas, but simply it will help them to become better computer scientists. After e brief look at the ways the numbers are placed and manipulated in computers we will deal with fundamental computational problems, such are solving the equations, system of equations followed by an approximation theory. We will deal with the accuracy of numerical solutions and also the aim is to evaluate the functions, numerical differentiation and integration.
  • [EM588] Internet of things
    The goal of the course is to provide students with fundamental knowledge into core concepts of the Internet of Things. Throughout the course, students will be exposed to theoretical and practical aspects regarding the architecture and applications of sensor networks and 4G/5G systems. Students will be able to use learned concepts through analysis of architectures and computer communication technologies for wireless Internet applications in the most diverse domains such as: smart environments, industrial and home networks of devices, as well as application in sensor and actuator networks.
  • [EM572] Introduction to Artificial Intelligence
    Introduction to the basics of artificial intelligence, intelligent agents, techniques for presenting knowledge and intelligent search and decision-making, game theory, formal logic, probability, and logical reasoning systems, learning by observation, training of neurons and learning stimulation. Also, students will be familiar with the basic concepts of LISP.
  • [EM589] Cybersecurity
    In Cybersecurity, introduces the technology, operational procedures, and management practices needed for successful cybersecurity. Makes extensive use of standards and best practices documents that are often used to guide or mandate cybersecurity implementation. Going beyond these, he offers in-depth tutorials on the “how” of implementation, integrated into a unified framework and realistic plan of action. Each chapter contains a clear technical overview, as well as a detailed discussion of action items and appropriate policies. Cybersecurity aligns with the comprehensive Information Security Forum document “The Standard of Good Practice for Information Security,” extending ISF’s work with extensive insights from ISO, NIST, COBIT, other official standards and guidelines, and modern professional, academic, and industry literature.
  • [EM573] Introduction to Information Systems
    Course aims: 1. To learn the basic concepts and the terminology of Information Systems a. Basic Information Systems concepts: hardware, software, networks b. E-World: e-business and e-commerce c. Developing Processes 2. To learn about the Information Systems and technologies that improve business values and various processes inside organizations. 3. Applying concepts with various managing disciplines, during analysis, interpretation, assessments and decisions. 4. Understand the process of redesigning organizations using information systems. 5. Describe the role of information systems in decision making. 6. Examine information security, ethical, and social issues. 7. Be familiar with the Internet, electronic commerce, and e-business. 8. Prepare students to work on small scale projects, individual or group work, who by nature could fall into these categories: case studies, scientific research project, development projects or internship projects.
  • [E2802] Business Analytics
    Business Analytics teaches the fundamental concepts of modern business analytics and provides vital tools for understanding how data analysis works in today's organizations. The course takes a comprehensive approach, examining business analysis from both descriptive and predictive perspectives. Students learn how to apply fundamental principles, communicate with analytics professionals, and effectively use and interpret analytics models to make better business decisions. As tools, among others, Excel will be used, strengthening the students' skills in the program and the basic understanding of the basic concepts. Additionally, Analytic Solver as well as commercial data-mining tools will be used so that students are prepared to use these same tools when they graduate.
• [6 ECTS] Professional Elective (from the module)**
  • [EM598] Information Retrieval
    This course attempts to be a comprehensive overview of the field. Its work will require written assignments, programming and a final project. Assignments will provide exposure to commonly used IR datasets. The course offers a number of practical projects in Information Retrieval, focusing on (but not limited to) website search engines. All projects involve programming: the end result is a relatively large-scale, well-documented and efficient software package. Some of the projects may also involve some research (e.g., reading a research paper and implementing its ideas).
  • [EM599] Data Analysis with Python/R
    Aims of the course: ● To be able to understand basic data analytics methodologies ● To be able to use tools that are used for data analytics ● To be able to practically apply their knowledge from the fields of statistics and data analytics ● To be able to present their results through various reporting and data visualization techniques
  • [EM600] Mathematics for Data Science
    Course aims: On successful completion of this course students will be able to: 1. Demonstrate understanding of basic mathematical concepts in data science, relating to linear algebra, probability, and calculus. 2. Employ methods related to these concepts in a variety of data science applications. 3. Apply logical thinking to problem-solving in context. 4. Demonstrate skills in writing topics from applied mathematics and projects
  • [EM601] Social and Information Network Analysis
    The course focuses on the structure and evolution of networks, drawing on knowledge from disciplines as diverse as sociology, mathematics, computer science, economics, and physics. Online interactive demonstrations and hands-on analysis of real-world data sets will focus on a range of tasks: from identifying important nodes in the network, to detecting communities, to tracing information diffusion and opinion formation.
  • [EM602] Neural Networks and Deep Learning
    The course focuses on the theory, structure and algorithms of neural networks and deep learning. The theory and algorithms of neural networks are particularly important for understanding deep learning concepts, so these this course offers important design concepts of neural architectures in different applications. And it covers the theory and algorithms of deep learning as well, providing detailed discussions of the relationships of neural networks with traditional machine learning algorithms. This theory is linked and described with real world practical applications.
  • [EM603] Natural Language Processing
    This course helps students to explore into the exciting world of Natural Language Processing (NLP) giving an overview of major topics in the field. Students will understand how computers work with human language, learn techniques and libraries for data analysis and create natural language processing tools as well. Interactive demonstrations and hands-on analysis of real-world applications will focus on a range of tasks: language translation, text classification, text clustering, sentiment analysis, speech recognition, summarization etc.
  • [EMCS-02] Data Visualization
    The aim of this course is to introduce students to the field of data visualization. Students will learn visualization design and evaluation principles, and learn how to acquire, parse, and analyze large datasets. Students will also learn techniques for visualizing multivariate, temporal, text-based, geospatial, hierarchical, and network/graph-based data. Additionally, students will utilize Processing, D3, R and ggplot2, and many other tools to prototype many of these techniques on existing datasets.

Semester 3

• [MCS-303] [6 ECTS] Research Methodology
  The purpose of this course is to provide students with knowledge and understanding of different scientific theories and methodologies. Initially the student will be introduced to the conceptual, theoretical definitions and examples of all existing methods of research, hypothesis, direct and indirect variables, validation of the results, the conclusions BIAS and scientific qualitative and quantitative methodologies, "ground research" methodology and other methodological approaches. In each chapter the student will work on practical assignments. After completing the course the student will be able to explain thoroughly and understand the importance of basic scientific concepts, effectively search and find information-relevant literature, identify, describe and formulate scientific problems, make a careful choice of alternative research approaches, thoroughly described, compare and explain the advantages and disadvantages of different scientific methods for collecting quantitative and qualitative data, apply basic scientific methods to analyze quantitative and qualitative data, understand different frameworks for building theory and review and evaluate scientific publications.
• [CM191] [6 ECTS] Advanced Algorithms and Data Structures
  This course builds on previous knowledge in the area of algorithms and data structures. The goal of the course is to acquaint students with efficient advanced algorithms and adequate data structures that are used to organize, search and optimize data. It also includes the theoretical efficiency of algorithms and its practical determination in order to be able to compare different algorithms. During the course, students will be introduced to several well-known algorithms, particularly search and optimization in complex nonlinear structures such as trees and graphs.
• [CM192] [6 ECTS] Formal Methods in Computer Science
  This course gives students a comprehensive introduction to formal methods and their application in software specification and verification. It covers some fundamentals in formal methods, including set theory, functions, finite state machines, predicate and temporal logics, and model checking. The course will give students examples of real-world application of these formal techniques.
• [6 ECTS] Professional Elective (from the module)*
  • [EM598] Information Retrieval
    This course attempts to be a comprehensive overview of the field. Its work will require written assignments, programming and a final project. Assignments will provide exposure to commonly used IR datasets. The course offers a number of practical projects in Information Retrieval, focusing on (but not limited to) website search engines. All projects involve programming: the end result is a relatively large-scale, well-documented and efficient software package. Some of the projects may also involve some research (e.g., reading a research paper and implementing its ideas).
  • [EM599] Data Analysis with Python/R
    Aims of the course: ● To be able to understand basic data analytics methodologies ● To be able to use tools that are used for data analytics ● To be able to practically apply their knowledge from the fields of statistics and data analytics ● To be able to present their results through various reporting and data visualization techniques
  • [EM600] Mathematics for Data Science
    Course aims: On successful completion of this course students will be able to: 1. Demonstrate understanding of basic mathematical concepts in data science, relating to linear algebra, probability, and calculus. 2. Employ methods related to these concepts in a variety of data science applications. 3. Apply logical thinking to problem-solving in context. 4. Demonstrate skills in writing topics from applied mathematics and projects
  • [EM601] Social and Information Network Analysis
    The course focuses on the structure and evolution of networks, drawing on knowledge from disciplines as diverse as sociology, mathematics, computer science, economics, and physics. Online interactive demonstrations and hands-on analysis of real-world data sets will focus on a range of tasks: from identifying important nodes in the network, to detecting communities, to tracing information diffusion and opinion formation.
  • [EM602] Neural Networks and Deep Learning
    The course focuses on the theory, structure and algorithms of neural networks and deep learning. The theory and algorithms of neural networks are particularly important for understanding deep learning concepts, so these this course offers important design concepts of neural architectures in different applications. And it covers the theory and algorithms of deep learning as well, providing detailed discussions of the relationships of neural networks with traditional machine learning algorithms. This theory is linked and described with real world practical applications.
  • [EM603] Natural Language Processing
    This course helps students to explore into the exciting world of Natural Language Processing (NLP) giving an overview of major topics in the field. Students will understand how computers work with human language, learn techniques and libraries for data analysis and create natural language processing tools as well. Interactive demonstrations and hands-on analysis of real-world applications will focus on a range of tasks: language translation, text classification, text clustering, sentiment analysis, speech recognition, summarization etc.
  • [EMCS-02] Data Visualization
    The aim of this course is to introduce students to the field of data visualization. Students will learn visualization design and evaluation principles, and learn how to acquire, parse, and analyze large datasets. Students will also learn techniques for visualizing multivariate, temporal, text-based, geospatial, hierarchical, and network/graph-based data. Additionally, students will utilize Processing, D3, R and ggplot2, and many other tools to prototype many of these techniques on existing datasets.
• [6 ECTS] Professional Elective (from the module)*
  • [EM598] Information Retrieval
    This course attempts to be a comprehensive overview of the field. Its work will require written assignments, programming and a final project. Assignments will provide exposure to commonly used IR datasets. The course offers a number of practical projects in Information Retrieval, focusing on (but not limited to) website search engines. All projects involve programming: the end result is a relatively large-scale, well-documented and efficient software package. Some of the projects may also involve some research (e.g., reading a research paper and implementing its ideas).
  • [EM599] Data Analysis with Python/R
    Aims of the course: ● To be able to understand basic data analytics methodologies ● To be able to use tools that are used for data analytics ● To be able to practically apply their knowledge from the fields of statistics and data analytics ● To be able to present their results through various reporting and data visualization techniques
  • [EM600] Mathematics for Data Science
    Course aims: On successful completion of this course students will be able to: 1. Demonstrate understanding of basic mathematical concepts in data science, relating to linear algebra, probability, and calculus. 2. Employ methods related to these concepts in a variety of data science applications. 3. Apply logical thinking to problem-solving in context. 4. Demonstrate skills in writing topics from applied mathematics and projects
  • [EM601] Social and Information Network Analysis
    The course focuses on the structure and evolution of networks, drawing on knowledge from disciplines as diverse as sociology, mathematics, computer science, economics, and physics. Online interactive demonstrations and hands-on analysis of real-world data sets will focus on a range of tasks: from identifying important nodes in the network, to detecting communities, to tracing information diffusion and opinion formation.
  • [EM602] Neural Networks and Deep Learning
    The course focuses on the theory, structure and algorithms of neural networks and deep learning. The theory and algorithms of neural networks are particularly important for understanding deep learning concepts, so these this course offers important design concepts of neural architectures in different applications. And it covers the theory and algorithms of deep learning as well, providing detailed discussions of the relationships of neural networks with traditional machine learning algorithms. This theory is linked and described with real world practical applications.
  • [EM603] Natural Language Processing
    This course helps students to explore into the exciting world of Natural Language Processing (NLP) giving an overview of major topics in the field. Students will understand how computers work with human language, learn techniques and libraries for data analysis and create natural language processing tools as well. Interactive demonstrations and hands-on analysis of real-world applications will focus on a range of tasks: language translation, text classification, text clustering, sentiment analysis, speech recognition, summarization etc.
  • [EMCS-02] Data Visualization
    The aim of this course is to introduce students to the field of data visualization. Students will learn visualization design and evaluation principles, and learn how to acquire, parse, and analyze large datasets. Students will also learn techniques for visualizing multivariate, temporal, text-based, geospatial, hierarchical, and network/graph-based data. Additionally, students will utilize Processing, D3, R and ggplot2, and many other tools to prototype many of these techniques on existing datasets.

Semester 4

• [CST-THESIS-120] [30 ECTS] Master Thesis
  This module enables students to transfer their skills and knowledge to research and carry out more complex tasks related to their master thesis. The module is designed to be fully practical and students to acquire the necessary knowledge and skills to approach writing the thesis. The module has unique return result-to enable students to write the master thesis with minimal difficulties, and with maximum efficiency. The course aims to improve research techniques and style of writing the paper, taking into account the prevention of the usage of illegal means, such as plagiarism and infringement of copyright, which are prohibited by the Statute of SEEU.