Bachelor Of Computer Science (AI Development & Data Science)



Why this Program?

  • Have you wondered how intelligent agents such as Siri, Google Assistant and Alexa are able to hold such human-like conversations with you?
  • Are you curious about how computers are able to detect and recognize different human faces? How they are able to predict complex outcomes such as fraud detection in banking, anomaly detection in cybersecurity and downtime prediction in manufacturing?
  • How Big Data is making use of data sets that span decades or centuries to give us powerful, ‘Crystal ball like’ predictive ability to foresee sudden cultural shifts, like the rise of smartphones, or understanding how insights as to how people live their lives, do their spending or simply what they do for entertainment?


In Artificial Intelligence (AI) Development and Data Science specialization, students will be equipped with knowledge and skills on Deep Learning with Machine Learning to enable machines to self-learn and execute any task. They will be using Data Science in powering the data-driven transformations across industry and society today. In this specialization, students will experience end-to-end AI and Data Science development, from data gathering, data engineering, model creation, application development to live deployment. Students will learn the skillsets to build data-driven AI applications and cognitive products.


What would I learn?

Upon successful completion of the program, you will acquire:

  • Knowledge to build, train and deploy various kind of neural network architectures.
  • Proficiency in big data analysis to extract high-value insights from data, fostering data literacy across organization types.
  • Expertise in NLP algorithms to collect datasets from open websites and applying different techniques to design AI models and develop applications for real world problems.


Program Structure

The program is designed as a four-year undergraduate degree. The first year is broadly a foundation year comprising modules that will be built upon it in the subsequent years. Each semester will have five modules or projects that will deliver practical sessions to promote inquiry-based learning.

In addition, two modules are included for the development of communication skills through Academic Skills and Dzongkha Communication and four modules from management and industrial practices including life skills such as Economics, Portfolio Design and Presentation, Advanced English Skills for Career Development and Introduction to Research.

Students will have to complete 60 credits in each semester. In total, a student has to complete 480 credits to be eligible for the award of a Bachelor of Computer Science (AI Development & Data Science).


Your career prospects…

As graduates of the Bachelor of Computer Science program with specialization in AI Development & Data Science, you can work as professionals in a range of global and local organizations like financial institutions, insurance companies, business organizations as well as the government agencies and ministries. Here is a list of key job opportunities that the graduates of this program can undertake.

  • Software Analysts, Software Engineers
  • Software Solution Architects
  • Application Developers
  • Web and Mobile Application Developers
  • Project Managers, Scrum Masters
  • Software QA Engineers
  • Cybersecurity Professionals
  • IT Consultants
  • IT Entrepreneurs


And with AI and Data Science Specialization,

  • AI Application, AI Product Developers, AI Infrastructure Technicians
  • Data Engineers, Data Architects
  • Data Scientists, Data Analysts, Data Quality Engineers
  • ML Engineers
  • NLP Specialists
  • Big Data Specialists


Are you ready to be the trailblazer for Bhutan’s Digital Frontier?

Year 1

Semester I

This module aims to teach the foundation of structured programming language. Students will begin with foundational construct of a programming language which include variables manipulation, decision, repetitive statement. Students will also learn functional and objects programming that will be applied to the front end web applications for dynamic contents.

This module aims to teach the foundation of mark-up, styling and interactive language that is used in front end web development. Students will be introduced to the fundamentals of web technologies and also basic web design principle to develop a functional interactive and responsive web site. Students will also learn the production pipeline to bring their work from development to production.

This module aims to provide students with an understanding of basic concepts and working of an operating system (OS) and computer networking. Students will experience hands-on sessions on with modern operating systems using Command-Line Interfaces. Students will be taught how to write scripts based on the OS commands/system tools for user management, software installation, network administration and configuration of services. These topics are essential to future DevOps modules.

This module introduces the students to modern database system which includes both SQL and NoSQL database. Students will learn database concepts along with theoretical foundation and practical skills needed to design and implement both database systems. Students will also learn the SQL and NoSQL methods for data handling and apply them in an application context.

This module aims to provide students with the fundamental knowledge and understanding on the history Dzongkha language. Students will learn the purpose of learning Dzongkha language and the grammars involved. Students will have hands-on experience on installation of Dzongkha Unicode and Dzongkha typing. This module will focus on the development of academic listening, speaking and writing skills to enable the students to communicate effectively in both spoken and writing at the university level and beyond. This module will enhance the students’ skills in writing letter, application and agreement related to government and private sectors. The module will also enhance the students’ in using references appropriately.

Semester II

This module enables students to develop a scalable and reliable backend web applications that can handle high volume of concurrent connections, which is the need of modern day web application. Students will build application based on Object Oriented Design and MVC architecture on the server side and expose necessary APIs. The module will also cover automated test and test management.

This module aims to equip students with the interactive design knowledge for interfaces for a variety of application. Students will explore principles, patterns and process for interaction design, rapid prototyping, user interface (UI) and user experience (UX) design. They can then applied to web, mobile development to create interactive prototype using prototyping tools.

This module introduces the student to the general area of Discrete Mathematics commonly required in many areas of computer science, in particular, Graph Theory. It reinforces mathematical maturity and ability to deal with abstraction. The module will also use a programming language to implement and illustrate the mathematics concepts and techniques in the subject.

This module aims to develop the knowledge and understanding of a range of academic skills required for study at university level. The module will focus on the development of academic writing, oral presentation, as well as listening skills to enable students to communicate effectively in both spoken and written forms. The module will enhance the students’ learning throughout their studies at university and beyond, through close reading, discussions and critiquing of academic texts. Further, it will also enhance students’ capacity to reflect critically on their own learning. 

This is a cap stone module where students will develop a responsive full stack web application. The students will be required to produce a solution from requirement analysis, to conceptualisation, to system design, to prototyping, to testing and finally to ‘live’ deployment.

Year 2

Semester I

This course covers fundamental concepts and the application of data structures and algorithms. Topics may include abstract data type, dynamic array, iterators, linked list, generics, stacks, queues, binary search tree, collections, maps, hashing, graphs, and sorting. It introduces a variety of application scenarios including graphics, web programming and user interfaces.

This module aims to introduce students to design fundamentals, allowing them to identify and critique components of effective visualized data, charts and the visualization of complex relationships using popular programming language. Students will also learn to use popular data analytics tools to do data wrangling and munging to prepare the data for visualization.

This module aims to introduce the fundamental concepts of linear algebra, calculus and numerical methods and its applications to data science. This module will help the students in understanding the algorithms in programming languages and will expose students to basic theory and principles, vectors and matrices, single and multivariate vector calculus in order to understand the algorithms used in AI and Data Science.

This module provides students with the skills to analyze and evaluate information in order to obtain the greatest amount of knowledge from a piece of data, and leads students to be rational and disciplined thinkers. This will provide the best chance of making the correct decisions, reduce biases and minimize damages by developing mitigation plans.

Semester II

This module aims to provide students with the fundamental concepts in Artificial Intelligence (AI) and Machine Learning. Students will have hands-on experience in building applications that make use of machine learning. This module covers both supervised, unsupervised learning techniques as well as ensemble techniques, machine learning pipelines, data engineering process.

This module aims to provide students with an immersive experience in Agile software development. It will cover both the technical and social aspects of Agile, including pair programming, test-driven development, behaviour-driven development, continuous delivery, clean code, refactoring, Scrum, and Agile project management. Student will understand Agile software development so as to become an effective leader or member of a software development team.

This module’s aim is to provide an introduction to the fundamental concepts of statistics and probability theory, probability distributions and hypothesis testing. Students will advanced further to explore statistical modelling and fitting, Regression analysis, Bayesian thinking and modelling and Markov Chains which forms the statistical foundation for AI and Data Science.

This module gives a detailed overview of the principles of microeconomics, macroeconomics and international economics. It will also introduce the students to the basic operation of the economy focusing on the most important tools in economics and applying these concepts to clearly explain real-world economic issues and events.

This is a cap stone module where students will develop an advanced responsive full stack web and mobile solution using Agile process in a team. The students will be required to produce a solution from requirement analysis, to conceptualisation, to system design, to prototyping, to testing and finally to ‘live’ deployment.

Year 3

Semester I

This module aims to help students understand the capabilities, challenges, and consequences of deep learning and prepare them to participate in the development of modern AI technology. Students will be guided through setting up popular Python frameworks, prepare data by cleaning and preprocessing it for deep learning. Students will get hands-on training with single and multiple layers of neurons and subsequently to other popular neural network architectures such as CNNs, RNNs and AEs and learn how to build models from scratch.

This module aims to train students to be conversant with the terminology, the core concepts and practical skills behind big data problems, applications, and systems. Students will explore and think about how Big Data might be useful in real world problem and make use of one of the most common frameworks for big data analysis so as to realize the increasing the potential for data to transform the world.

This module aims to prepare the students to handle the DevOps pipeline process starting from Agile to development, software version control, continuous integration (CI), automated test and continuous delivery (CD). This modules will provide students with hands on experience in building the pipeline process to eventually deploy a project live using CI/CD with automated testing.

Design thinking for Innovation is a human-centred, interdisciplinary approach towards innovation, and particularly valuable for sketchy and complex problems. In this module, students will learn the different stages of the design thinking approach, and also the various methods supporting each of the stages. Learning will be largely experiential in nature; students will work in small groups and gain first-hand experience working on a design challenge using design thinking approach and methods.

This module aims to provide the basic IT professional certification for the students. Students will be prepared for industrial recognized certification so as to bench mark their standard and build the necessary credential for future IT employment.

Semester II

This module aims to extends the students knowledge of deep learning to study and implement advanced models. Starting with a review on multi-layer perceptrons (MLPs), convolutional neural networks (CNNs), and recurrent neural networks (RNNs), the students will be introduced to more cutting-edge techniques of deep neural network architectures, including ResNet and DenseNet. Next, they will create variational autoencoder (VAE), learn how GANs and VAEs have the generative power to synthesize data that can be extremely convincing to humans. They will also implement DRL such as Deep Q-Learning and Policy Gradient Methods, which are critical to many modern results in AI.

This module acquaints the students with the theories and practices of scientific research. It aims to develop their competency in designing, conducting and effectively communicating their research by using pertinent methodologies/techniques and tools. Moreover, it elucidates various issues and considerations along the path of a research journey that the students shall embark upon in this module. The skills and knowledge acquired in the module are deemed useful for a range of upcoming projects and inquiry-based problem-solving endeavors.

This is a mini cap stone module where students will undergo the full software development life cycle using Agile process. Students will work together in small groups to come up with innovative solutions for real-life problems and It can serve as an opportunity to demonstrate knowledge mastery and creative thinking.

Year 4

Semester I

This module aims to be an introduction to NLP. Students will study different approaches to NLP tasks, and perform exercises in programming to understand the process of preparing datasets for NLP models. Students will use advanced NLP algorithms and visualization techniques to collect datasets from open websites, and to summarize and generate random text from a document. Students will also use NLP to create a chatbot that detects positive or negative sentiment. By the end of this module, students will be equipped with the essential NLP tools and techniques to solve common business problems that involve processing text.

This module prepares the students to design, implement and present algorithmic approaches to a variety of programming scenarios in a timely manner. Students will apply the recurring themes from earlier data structure and algorithms modules to a variety of domains, including string processing, geometry, graphs, trees, combinatorics and number theory.

This module aims to discuss ethical problems that computer scientists face, the codes of ethics of computing professional societies, legal issues involved in technology, and the social implications of computers, computing, and other digital technologies. The students will be able to understand concepts of impact of social media, economic implications of globalization, intellectual property rights, computer crimes and security related legal redress.

Semester II

This module aims to provide the advanced IT professional certification for the students. Students will be prepared for industrial recognized certification so as to bench mark their standard and build the necessary credential for future IT employment.

This is the final capstone project is designed to provide the students with a hands-on environment to test and apply the knowledge and skills, tools and techniques, learned throughout the programme in a practical, real world setting. The focus of this project is to encourage students to think critically, solve challenging problems, and develop skills such as oral communication, public speaking, research skills, teamwork, planning and goal setting when given a real industry project.