Computer Science

This course introduces computer engineering students to the business side of technology projects. Students learn how to assess not only the technical success of a project but also its economic, financial, and social impact. Using both quantitative and qualitative methods, students explore how to make informed decisions about project viability, sustainability, and long-term value creation. This course discusses the importance of the UN 2030 Sustainable Development Goals (SDGs) and how they shape modern business and engineering practices. 

This course introduces the principles and design of distributed systems, emphasizing communication, middleware, and web technologies. Students learn to develop secure, scalable, and fault-tolerant distributed applications and services using modern frameworks and protocols.

This course explores the fundamental concepts and activities involved in defining what a software system should do. Students learn to identify stakeholders, establish project goals, model business processes, and describe scenarios and use cases. The course covers types of requirements, elicitation and analysis methods, and techniques for resolving conflicts. Emphasis is placed on producing a well-structured Software Requirements Specification (SRS) using recognized templates and best practices.

This course introduces the statistical, computational, and algorithmic principles that underpin artificial intelligence engineering. Topic include: statistical inference; model evaluation; supervised and unsupervised methods; regularization and model selection; data preprocessing; model complexity analysis; results interpretation.

This course focuses on classical methods of reasoning and knowledge representation and explores how they are used today with examples in the areas of mobile robotics and machine learning.

The course introduces modern web application development from an engineering perspective, emphasizing model-driven design and best practices. Students learn to model data and hypertext, apply client- and server-side technologies, and implement systems using the Model-View-Controller (MVC) architecture. Topics include testing, security, deployment, and SEO. Through practical projects, students develop the skills to design, build, and document professional web solutions.

Prior experience with programming knowledge, web technologies, and software engineering fundamentals is recommended.

The course explores in-depth agile software development, covering not just how to use frameworks like Scrum, but why agile software works. Students practice managing real-world software projects that need to adapt quickly to change, while keeping the team focused on delivering value to users.  This course offers hands-on experience with agile tools, frameworks, and programming environments that support fast, flexible, and iterative development. 

Students are expected to have prior experience with software design, development, and testing.

This course offers a study of basic Machine Learning techniques including when to use Machine Learning to solve real problems, which techniques are appropriate, and how to apply them in a practical way. It examines classification and various techniques: prediction, non-supervised, and reinforcement-based ones. This course also discusses relational learning and methodological aspects of machine learning.  

Pre-requisites- Programming and Statistics 

Machine Learning is the science of how we can build abstractions of the world from data and use them to solve problems in a data-driven way. This course allows students to both understand the principles upon which Machine Learning methods are based and learn the practical skills required to apply Machine Learning to solve real problems.

In this course, students progress through a series of weekly workbooks that consist of structure practical tasks, each with specific outputs and objectives. Reference images are provided for many of these tasks, so that students may assess their own progress and determine when they have successfully achieved the objectives of a workbook. Completion of these formative tasks provides students with the skills and knowledge required to pass the assessments.