Bachelor's Degree (BSc) in Modern Computer Science
- Study level Undergraduate
- Credits 180 ECTS
- Duration 6 terms
- Location Online / Fully remote
- NEXT INTAKE Jan/Sept 2025
- Language English
- TUITION FEE €2250/term
- Accreditation Accredited >
Overview
The IT industry will fuel the advancements in our society in the coming years. With input from employers, industry professionals and academics, the 180-credit OPIT BSc degree in Computer Science was designed to provide you with a 360° foundation skills, both theoretical and applicative, in all aspects of today's Computer Science: Programming, Software development, Databases, Cloud Computing, Cybersecurity, Data Science, Artificial Intelligence.
EU accredited Institution
Tutors available on a daily basis
Recorded and live content
Professional certifications (Google, Microsoft, AWS)
Progressive assessments (no final exams)
Regular and Fast-track option (3 vs 2-years)
Career Outlook
Whether you are a working professional who wants to reskill or a high-school graduate who seeks a future career in Computer Science, this program is right for you. Career prospects:
- Software Developer & Engineer
- Data Scientist
- Web Developer
- App & Game Developer
- IT Business Analyst
- Cyber security Analyst
- Database Architect
- DevOP
Certifications
Whether you are a working professional who wants to reskill or a high-school graduate who seeks a future career in Computer Science, this program is right for you.Entry requirements
Whether you have high school qualifications or you are already working in a computer science field, you can attend our valuable degree that will help move your career forward.
Higher Secondary School Leaving Certificate
We accept qualifications from around the world
English proficiency as B2-level certificate or equivalent
If you don't have an English certificate, try our test
Credit transfer of previous study and work experience
Our admission team will support you in the processSyllabus
The Bachelor’s is structured with 5 Terms of courses and 1 final Term for the dissertation/project. Every Term lasts 13 weeks.
In Term 5, you can select 5 electives from a pool of 27, or you can specialize in one of 5 fields.
Electives availability is subject to student interest and other factors.
- Fall term from mid-late September to mid-December
- Winter term from late January to late April
- Summer term (only for fast-track option) from mid-May to August
First Term 
Technical English
The module will provide the linguistic competences necessary for the student to ultimately listen, read, write and think critically in English. Students will learn specialist terms alongside other basic English, and grammatical rules will be regularly practised and summarised to reinforce the use of the English language and discourage code-switching. The topics presented will reflect the latest developments in technology taken from popular literature and which are relevant to students’ applications.
Computer Networks
The Computer Networks module exposes students to the underlying workings of traditional networking ranging from a small office network to the internet.
Students will understand the basic network types and topologies and they will go through the process of creating packets of data, transmitting them, and routing them across the network.
Students will be introduced to the Open Systems Interconnection (OSI) Model, TCP/IP protocol, Network Operations (Ops) policies, plans and procedures, business continuity, high availability, disaster recovery, network optimization and security.
Programming Principles
The Programming Principles module is intended as the first introductory course to programming.
The module will introduce students to the inner workings of a computer and introduce them to fundamental programming concepts such as assigning and manipulating variables, using conditional statements, looping and iterations, using more complex data types and data structures, and creating simple functions.
Students will also be guided to identify and solve syntactical or logical problems, how to use libraries, and learn techniques to create efficient and effective code.
Computer Architectures
The Computer Architectures module introduces students to how a basic computer works. It starts by introducing the traditional Von-Neumann Architecture. It then goes on to explore the movement of data within a machine, from secondary to primary storage. The module then focuses on the central processing unit (CPU) and its various constituents. Once the high-level concepts are dealt with, the focus moves to a granular level and examines the fetch-decode-execute cycle and the peculiarities of different processor families.
Students will also explore how data is stored as bits, bytes, words, and how to convert between different representations as well as how to use Hamming codes and the various components of computer logic.
ICT Fundamentals
This foundation course is designed to help students understand the basic principles of problem-solving, digital devices, and software development, and to take a hands-on approach to computing. Topics covered include, among others, computational thinking, algorithms, data structures, language translators, interpreters and compilers, IT project management methodologies, computer networks, cloud computing, and future directions in Computer Science and Information Technology. After completing the module, students will be equipped to take on a variety of ICT-related tasks to be applied in a variety of daily settings.
Second Term
Introduction to Operating Systems
This Module will introduce students to Operating Systems (OS) and system programming aspects at the OS level.
Students need to understand an OS's anatomy, key functions, and different layers in order to operate OSs successfully since they are crucial pieces of software that enable machines to execute all programs.
Basic concepts found in imperative programming languages, such as variables, functions, and program flows will be used to control the different operations of the OS. The primary teaching environment used is Linux, as it is available on most devices and provides a high-security efficient environment. The C programming language will be used to perform experiments, allowing students to access low-level file input/output, manipulate memory and perform signal handling. Towards the end of the unit, students will have an excellent understanding of C and their coding level will improve drastically.
Web Development
The Web Development module is intended to give students a basic understanding of how the web works by introducing core web programming principles and presenting the opportunities and challenges of these web-based technologies.
It begins by introducing the fundamentals of the Hypertext Transfer Protocol (HTTP) and then shifts to the browser, its anatomy, and its role in client-side architecture. Students will be introduced to markup languages such as HTML, CSS, and JavaScript, as well as server-side scripting, document tree manipulation, and Web debugging techniques and tools. Most of the technologies in this module are based upon official standards issued by the World Wide Web (W3C) consortium.
Data Structures and Algorithms
Data Structures and Algorithms (DS&A) is an essential course for any programmer to understand algorithm properties, distinguish between algorithm strategies, and learn how to use them effectively. This module is divided into two parts: the first looks at elements of Discrete Mathematics to give the user a solid foundation, while the second focuses more on the applied aspect. Students will learn to program constructs such as arrays, stacks, queues, trees, graphs, linked lists, heaps, and hash tables in real-world applications using real programming languages. They will also explore different well-known algorithms, including sorting, traversing a tree, and simple graph algorithms. Finally, the unit will cover algorithmic analysis for the efficient code design.
Project Management and QA
The Project Management and Quality Assurance module provides students with an overview of different projects and their backgrounds, as well as a discussion on the organisation's culture and how this affects the successful completion or otherwise of a project. To manage the project, students must identify the project boundaries, ensure resources are available and organise them for efficient implementation, and define a governance and organisational set-up. Project reporting should be in place throughout the project based on expected milestones. Project management involves preparing quality plans, estimating resources, drawing responsibility charts, using control cubes, s-curves, bar charts, networks, and other planning methods, and executing the project effectively and efficiently. Students must also set up robust processes to ensure they reach goals, such as work approvals, allocation of resources, team management, progress measurement, forecasting, and project completion.
Foundational Mathematics
The Foundational Mathematics module provides students with basic mathematical knowledge to understand fundamental concepts and develop the necessary analytical skills useful in computer science courses.
It covers differential calculus, combinatorics, probability and statistics theory, vector geometry, matrix and determinants, (which form the basis of computer vision and graphics processing) as well as linear algebra and transformations, and vector spaces.
Third Term
Introduction to Artificial Intelligence
AI is the most important technology of the decade and this module introduces students to the fundamental concepts and how to use AI tools.
It covers topics such as the Python programming language, knowledge representation, problem-solving, decision-making, natural language processing, intelligent agents, robotics, AI ethics, and the future of AI.
By the end of the module, students will be in a better position to understand when and how to use AI.
Introduction to Databases
This module introduces students to the core concepts behind Databases (DBs) and database management systems (DBMSs). It also covers modern advances in databases such as object-oriented, semi-structured, multimedia, blockchains, and temporal database models, as well as the extensible Markup Language (XML). Finally, students will learn how to design and implement an Information System using various data models, and the importance of using a DBMS in managerial decision-making.
Cloud Computing Infrastructure
The Cloud Computing Infrastructure module aims to help students understand the growing needs for computing resources and how they can be addressed using remote computing architectures. The module will highlight the fundamental concepts behind clouds (such as virtualization, infrastructure as a service, Platform as a Service, Hybrid Models, and others) This will ensure that students decide on the best computing paradigm to use while addressing problems in the real-world applications. Additionally, it explores the logistics of establishing a true cloud environment using Microsoft Azure as a case study. Students will also be exposed to various cloud components for networking, storage (blob/file/queues), databases (SQL/NoSQL), web/mobile services, IOT and finally managing and orchestrating cloud solutions via monitoring and metrics. The business implications of employing a cloud system will also be covered.
Business Strategy
The Business Strategy module is designed to provide students with a comprehensive understanding of the critical concepts and frameworks for developing effective business strategies in the digital age. Students will learn how to assess the competitive environment and develop a competitive strategy to gain a competitive advantage. They will also learn the importance of developing a digital business model and implementing a digital marketing plan to drive customer acquisition and retention. By the end of the course, students will be equipped with the skills and knowledge necessary to develop and implement effective business strategies in the digital world.
Programming Paradigms
Students will need to understand programming paradigms as they will face different languages throughout their careers. The module will start by giving them a historical perspective and then go on to discuss each paradigm's strengths, weaknesses, and differences.
Through the module, students will understand the programming languages' underlying principles and their various features. Students will be exposed to the following paradigms: Imperative, Object-Oriented, Functional (using Python/Java), and Parallel/Concurrent. The focus of the course will be on the Object-Oriented paradigm.
The ultimate aim of this module is to strengthen students' understanding of object-oriented programming and provide a more comprehensive understanding of various paradigms. This will enable them to develop larger and more complex software projects.
Fourth Term
Introduction to Machine Learning
The Introduction to Machine Learning module will help students gain a multi-disciplinary overview of the field using elements from computation, statistics, and machine learning. It will cover the basic steps of a machine learning project, such as Introduction to the Python programing language, Numpy library for manipulating multidimensional arrays, data-driven modeling paradigm, data preprocessing and visualisation, model complexity and cross-validation, and simple models for classification, regression, and clustering. The module will stress the use of jupyter notebooks for developing code for machine learning projects and writing reports.
Introduction to Computer Security
This module will cover the main issues surrounding cyber security, such as cryptography and key management, user authentication and identity management, secure operating systems, network security, privacy, anonymity, and censorship, and the EU-GDPR. The module will cover the core principles and analyse the implications and trade-offs of different methodologies and also how they are evolving with the deployment of emerging technologies.
Introduction to Software Engineering
Software Engineering is the process of creating robust, reliable software systems. The module starts by looking into the elements of the system life cycle, requirements analysis, and software design methodologies and covers topics such as Classical Software Engineering principles, System Life Cycle, Object Oriented Design, Verification Techniques, Requirements Elicitation, Software Testing, Configuration Management, and Quality Standards.
Throughout the module, different software architectures, software testing, and modern concepts and methodologies in software development will be explored through the analysis of different assignments.
The emphasis is on high-quality software design, especially within a team so teamwork and project management will also be covered.
Cloud Development
The Cloud Development module is intended to train developers to create cloud solutions. Students will learn to implement complete solutions, deploy functions, utilise cloud storage, set up authentication/authorisation, and manage web apps. They will also learn how to monitor these online services, troubleshoot them and optimise them based on the number of users using the system.
To ensure a quicker learning curve, students will perform a substantial amount of work using online sandboxes. Cloud is the future of most services, so it is imperative for any student to learn cloud development since it will be an important part of most modern software development jobs.
Digital Marketing
The Digital Marketing module provides students with a critical understanding of the key concepts, fundamentals, and challenges of online marketing. It explores the impact of the internet on the traditional marketing mix, examines the key ingredients of the online micro and macro environments, and delves into analysing consumer behaviors and how they respond to social media strategies. Students will also learn to use multiple best practices to facilitate electronic commerce using media channels such as affiliate marketing, search engine optimization, and web public relations.
Fifth Term
Cloud Computing Automation and Ops
In "Cloud Computing Automation and Ops", students learn about the fundamentals of cloud computing, different cloud service models, and deployment models. They also learn how to automate tasks using various tools and techniques, including scripting and programming languages, automation frameworks, and configuration management tools. The course also covers cloud infrastructure monitoring, troubleshooting, and optimization to ensure the high availability and performance of cloud-based applications and services. Finally, students learn about security, compliance, and governance in cloud environments.
Agile Development and DevOps
The elective course in Agile Development and DevOps covers the principles, practices, and tools required for software development using the Agile methodology and DevOps culture. The course includes topics such as Agile project management, Agile software development, continuous integration, continuous delivery, containerization, automated testing, and infrastructure as code. Students will learn how to build software products in an agile manner, deploy and maintain them using DevOps practices, and manage the software development lifecycle with the help of various tools and techniques.
Cloud Architecture Paradigms
The elective course delves into Cloud Architecture Paradigms, covering contemporary approaches, trends, and sustainable practices. Through hands-on activities and discussions, participants gain a nuanced understanding to design, implement, and optimize cloud architectures. Topics include Cloud Computing, Big Data, Serverless Computing, IoT Integration, Media Streaming, Containerization, Multi-Tenant Architectures, Hybrid and Multi-Cloud Architectures, Case Studies, Sustainability, and Future Trends
Cloud Data Stacks
The elective course navigates the complexities of Cloud Data Storage, offering insights and practical applications for modern data architectures. Participants gain knowledge to efficiently manage cloud data stacks, ensuring integrity, scalability, and performance. Topics cover Cloud Data Storage, Transition to Cloud Architectures, Modern Data Estates, Big Data Stacks, Semantic Data Technologies, NoSQL Databases, Data Lake Concepts, Data Lakehouse Architecture, Data Mesh Principles, ELK Stack, Cloud-Specific Data Stacks, and Best Practices.
Cloud Adoption Frameworks
The elective course delves into cloud transition strategies, governance, and best practices. Covering motivation, goal setting, and optimization, it emphasizes aligning cloud strategies with business objectives. Topics include an overview of Cloud Adoption Framework, strategy development, best practices, governance, and managing cloud solutions through case studies and simulations.
Cloud and IoT Security
The elective course addresses security challenges and solutions in cloud computing and IoT. It explores techniques for ensuring data integrity, privacy, and compliance in both cloud and IoT environments, including topics such as Cloud Security Introduction, IoT Security Challenges and Solutions, Data Protection, Privacy in the Cloud, Security Protocols for IoT Devices, and Case Studies on Cloud and IoT Security Incidents.
Cybersecurity
The Cybersecurity elective covers three main aspects: security, compliance, and identity fundamentals across cloud-based systems. It will use cloud services such as Microsoft Azure to ground the theoretical aspects into real-life applications, and students will explore security methodologies, concepts and compliance principles. They will then proceed to identify principles, concepts and types, and analyse the security aspects of various systems by looking into the security management capabilities of cloud platforms. Finally, students will examine information protection risks and data lifecycle management capabilities in cloud deployments. Through this module, students will gain a good knowledge of security, compliance and identity, and will be able to try out these concepts in real-life.
Generative AI in Cybersecurity
This advanced elective course explores AI's impact on cybersecurity, including the application of generative AI models for threat detection and security solutions. It provides insights into the potential and challenges of integrating AI into cybersecurity applications. Topics include the introduction to generative AI, AI in threat detection, the application of generative models in cybersecurity, case studies of AI-driven security solutions, and the ethical implications of AI in cybersecurity.
Cryptography and Secure Communications
The elective course explores cryptography's realm, discussing techniques for secure communications, encryption methods, key management, and its role in safeguarding data during transit and rest. It covers topics such as the basics of cryptography, encryption algorithms like DES, AES, RSA, secure communication protocols including SSL and TLS, key management techniques, and real-world case studies.
Network Security and Intrusion Detection
The elective course delves into network security, examining threats and solutions. It covers intrusion detection systems, vulnerabilities, and safeguarding techniques, including topics such as network security basics, attack vectors, preventive and reactive measures, and real-world case studies.
Secure Software Development
The elective course guides students in adopting best practices for secure software development, emphasizing security throughout the software development lifecycle, from design to deployment. Topics covered include secure coding practices, threat modeling in software design, security testing, validation, patch management, vulnerability handling, and case studies on software vulnerabilities and exploits.
Reinforcement Learning
The elective course in "Reinforcement Learning" covers the theory and application of a machine learning paradigm in which an agent learns to make decisions in an environment to maximize a reward signal. Topics include Markov Decision Processes, Bellman equations, value and policy iteration, Monte Carlo methods, temporal difference learning, Q-learning, policy gradients, and deep reinforcement learning. Applications in robotics, game playing, and recommendation systems may also be discussed. Hands-on projects and assignments are used to reinforce the concepts learned.
Machine Learning
The course in Machine Learning covers the foundational concepts and techniques of building and training intelligent computer systems. This includes topics such as probability and statistics, supervised and unsupervised learning algorithms, deep learning, natural language processing, computer vision, and reinforcement learning. Students also learn about the ethical and societal implications of machine learning, as well as practical applications in various industries such as finance, healthcare, and marketing. The course involves both theoretical lectures and hands-on projects that require programming and data analysis skills.
Complex Networks and their Applications
The course "Complex Networks and their Applications" covers the study of complex systems and networks, with a focus on their mathematical properties and real-world applications. Topics include network structure and dynamics, statistical properties of networks, network models, community detection, centrality measures, and network algorithms. The course also explores applications of network science in various fields, such as social networks, biological networks, transportation networks, and communication networks. Students will gain an understanding of the principles behind network analysis and will learn to apply network science tools and techniques to solve real-world problems.
Computer Vision
This course provides a foundation in computer vision principles, covering image processing, feature extraction, and object detection. It explores modern methods using convolutional and generative neural networks, utilizing popular frameworks like TensorFlow and PyTorch. The module emphasizes ethical considerations in computer vision, addressing privacy, bias, and responsible AI development. Topics include transfer learning, semantic segmentation, image captioning, visual recognition applications, and the ethical implications of computer vision.
Ethics of Computer Science and AI
The elective course "Ethics of Computer Science and AI" covers the ethical, social, and legal implications of the development and use of computer science and artificial intelligence (AI) technologies. The course explores topics such as privacy, security, bias, discrimination, accountability, transparency, and the impact of these technologies on society. It also examines different ethical frameworks and principles and how they apply to the design and deployment of computer science and AI systems. Additionally, the course involves case studies and discussions to foster critical thinking and ethical decision-making skills.
Natural Language Processing
In a world driven by data and communication, understanding and processing human language is a game-changer.
In this course, students will acquire the fundamental knowledge and practical skills needed to work with natural language data and develop applications that understand, generate, and interpret human language.
This module also introduces specialized libraries and tools for Natural Language Processing (NLP) based on modern deep learning methods.
Game Development
The elective course in Game Development covers the fundamentals of game design, programming, and production. It includes topics such as game engines, graphics, artificial intelligence, game mechanics, and user interfaces. Students will learn how to use programming languages and tools commonly used in game development (Unity). The course also involves working on individual or team projects to develop a complete game from start to finish. Ultimately, the course aims to provide students with the knowledge and skills to create engaging and entertaining video games.
Project Methodology and Visual Communication
The elective course navigates project management in the dynamic realms of Metaverse and Gaming. It covers methodologies, planning, Agile execution, visual communication principles, UI/UX design, and virtual reality. Topics also include project optimization, risk management, visual content creation, interactive design, data visualization, and portfolio development.
Digital Application for Digital Environments
The elective course delves into game development using Unity, Unreal, and Autodesk Maya. It covers basics, advanced features, hands-on projects, 3D modeling, and integration within game engines. Additionally, participants explore industry standards, best practices, and career paths in game development.
Digital Video, Visual Effects and Virtual Reality
The elective course explores digital storytelling, VFX, and VR. It covers video production fundamentals, scripting, shooting, editing, VFX integration, VR basics, and immersive experience creation. It culminates in a hands-on digital video and VR project workshop, providing participants with the opportunity to apply acquired skills and knowledge in a practical setting.
Sensors and Devices for VAX Reality
The elective course embarks on a transformative exploration of immersive technologies with a focus on sensors and devices essential for creating captivating virtual, augmented, and extended reality experiences. This course aims to provide participants with insights into the technological underpinnings of immersive experiences, empowering them to conceptualize, design, and implement innovative and engaging experiences leveraging sensors and devices in immersive technology ecosystems.
Leadership and Business Development for the Metaverse
The elective course is a forward-looking course delving into the transformational landscape of the metaverse and its profound impact on business strategies, leadership, and consumer interactions. It navigates through the historical evolution of virtual reality in business contexts, paving the way for a comprehensive exploration of the metaverse's emerging realm.
Parallel and Distributed Computing
This elective covers challenges with building parallel and distributed applications, including testing, debugging, and performance evaluation.
The module covers a variety of topics, such as multithreaded programming, asynchronous and synchronous computation, concurrent control, parallel algorithms, load balancing, fault tolerance, scalability and performance analysis, and distributed data storage/computing.
Different programming languages will be used, depending on the specific application scenario including C/C++ and Java.
Front-end Programming
The course in "Front-end Programming" covers the essential concepts and tools required for building responsive and interactive web applications. Students will learn the fundamentals of HTML, CSS, and JavaScript and how to use libraries and frameworks such as React and Angular to create dynamic user interfaces. Additionally, the course covers topics such as web accessibility, user experience design, and web performance optimization. Students will also develop practical skills through hands-on projects and assignments, allowing them to build a portfolio of real-world applications.
Mobile Programming
The course in Mobile Programming covers the development of mobile applications for iOS and Android platforms. It includes topics such as app development frameworks, user interface design, data management, debugging, and testing. Students learn programming languages (such as Java, Kotlin, Swift, and Objective-C), as well as mobile development tools such as Xcode and Android Studio. The course also covers advanced topics such as mobile security, cloud integration, and cross-platform development. Students are required to develop a mobile app as a project to demonstrate their skills.
Software Engineering
The elective course in "Software engineering" covers the principles and practices of designing, developing, and maintaining software systems. Students learn about software development methodologies, such as agile and waterfall, as well as programming languages, software testing, and project management. The curriculum also includes software architecture, database design, and human-computer interaction. Students work on projects individually or in teams, gaining hands-on experience with software development tools and techniques. The goal of the course is to prepare students for careers in the software industry or further study in computer science.
Sixth Term
Dissertation
The final-year thesis is the most significant assignment given to students during their degree program since it consolidates abilities and gets them ready for subsequent assignments. The thesis is the most challenging project offered to students and calls for a full term of planning and rigorous effort.
The supervisor's role is to mentor the student, and the work's quality should answer a particular research topic in depth.
Internships with corporate partners can be available to students as a means of employment while they finish their thesis.
The student presents their work and responds to queries as they deliver their thesis before a committee.
EU Accredited
OPIT is a fully accredited Higher Education Institution under the European Qualification Framework (EQF) and the MFHEA Authority (Malta Qualification Framework – MQF – License number n.005-2023). As such, OPIT’s accredited programs have full legal value in Europe and are professionally recognized by employers
Value for money
Thanks to several funding options, our fees start at an affordable rate per term. Plus, online learning will save you money as you won't need to relocate to pursue your degree
Fully inclusive
Our course fees are all-inclusive, with no hidden charges
Scholarships & Funding
We have different financing options to fund your degree
Credit Transfer Policy
Contact us at hello@opit.com
Bachelor Fees
€2250/term
-
Different payment plans available -
10% discount on the total fee if you pay upfront (not cumulative with the early bird)
Top-notch academic leaders
Our selection process focused on recruiting Professors with great academic experience, a strong knowledge of today's Computer Science, and a hands-on teaching approach.
Lokesh Vij
Software Engineer @ Symantec, Part-Time Faculty @ Seneca College
Raj Dasgupta
AI/ML Research Scientist @ US Naval Research Laboratory, former Full Professor @ University of Nebraska
Panagiota Katsikouli
Researcher @ University of Copenhagen, PhD in Computer Science @ University of Edinburgh
Pierluigi Casale
Former Innovation Officer @ European Parliament, Principal Data Scientist @ TomTom.
By designing our degrees from scratch we redefined the learning experience in a way that both the academic and professional worlds require today.
Prof. Francesco Profumo
OPIT Head of Institution
Former Minister of Education in Italy
Former Minister of Education in Italy
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