MS Data Science and AI (MSDSAI)

Introduction

Driven by its aims to create an ecosystem of technology and innovation, the MS in Data Science and AI at GU TECH, Al Ghazali University is designed to prepare its students to work in the IT sector from the very outset and instill into them an innovation flair. The program presents a framework that maps specialized courses and an enormous range of opportunities for its students. The salient features of the program are as follows:

Core Technical Skill Development in Data Driven Decision Making and AI Technologies

This program is designed to equip students with the core skills of Data Science and Artificial Intelligence (AI) at the MS level, empowering them to drive innovation and lead the global tech industry of the future. With a strong focus on developing core technological competencies, the program provides hands-on experience in machine learning, deep learning, big data analytics, and AI-driven solutions. Graduates will be prepared to contribute to cutting-edge advancements, solve real-world problems, and shape the future of technology through research, development, and industry leadership.

Innovation and Incubation Center

Our focus is aligned with Today's educational landscape that is redirected from "job seekers" to "job givers” and from “tool users” to “tool creators”. For this paradigm to transform, our academic settings must embrace innovation and foster the emergence of a start-up culture. The Center is founded in line with this shifting paradigm to serve the needs of the demanded innovation pipeline that will become instrumental for Tech industry in future growth. The ICC aimed to commercialize the high-tech developed products in local and international market through working collaborations with market leaders. The shared workspace will be provided under the GU TECH IIC which will house innovation seekers, with researchers and Tech companies under one roof.

In addition, collaboration, at this stage also, will continue and will be extended to international universities, industry, research centers, and technology hubs like Silicon Valley. Foreign collaborations will be established with France, China, the US, UK, Turkey, Qatar, and Saudia. Cases in innovation and technology from Silicon Valley will be presented to students.

Program Overview

The MS in Data Science and AI program offered by GU TECH is a minimum of 2 years Master’s Program with two regular semesters per year i.e. Spring and Fall. The two-year program is split into multiple semesters.

1.1

Objectives

Following are the objectives of MSDSAI program:

Develop Core Competencies:
Build expertise in Data Science, AI, and Machine Learning through theoretical foundations and practical applications.
Foster Innovation & Research:
Encourage cutting-edge AI-driven innovation and research to address real-world challenges.
Enhance Technical & Analytical Skills:
Strengthen skills in big data analytics, deep learning, and computational modeling to solve complex problems.
Prepare Industry Leaders:
Train professionals to lead the global tech industry by leveraging AI and data-driven decision-making.
Promote Ethical & Responsible AI:
Instill a strong understanding of ethical AI practices, ensuring responsible and fair technological advancements.
Bridge Academia & Industry:
Facilitate collaboration with industry leaders, startups, and research institutions to drive impactful contributions.
Encourage Problem-Solving & Critical Thinking:
Develop problem-solving abilities for tackling global tech challenges using AI and data science.
Support Career Growth & Entrepreneurship:
Equip graduates with the skills to excel in top tech companies, research labs, or start their own AI-driven ventures.

1.2

Outcomes

After completion of the program, a student is expected to meet the following outcomes:

Master Core AI & Data Science Skills:
Demonstrate expertise in machine learning, deep learning, big data analytics, and AI-driven solutions.
Lead Innovation in Tech Industry:
Apply cutting-edge AI techniques to drive technological advancements and industry transformation.
Develop AI-Powered Solutions:
Design and implement scalable AI models for real-world applications in healthcare, finance, robotics, and more.
Enhance Decision-Making with Data:
Utilize data-driven insights for strategic decision-making in research and industry settings.
Bridge Academia and Industry:
Collaborate with leading tech firms, startups, and research institutions to contribute to AI and data science advancements.
Apply Ethical AI Practices:
Develop responsible AI solutions with a strong understanding of ethical, social, and legal considerations.
Excel in Global Careers:
Secure high-impact roles in AI research, data science, technology leadership, and entrepreneurship.
Drive Technological Transformation:
Contribute to the global tech landscape by developing innovative AI applications and leading research initiatives.

1.3

Essential Requirements for the MS Degree:

The following are the fundamental requirements to get admission and complete Computing degrees at Al Ghazali University.

Eligibility Criteria, Duration of the Program and Award of Degree:

Applicants applying to the MS “Data Science and AI” Program must have their Bachelor’s (or Master’s) degree in any one of the following areas:

Any Engineering Discipline such as Electrical, Civil, Mechanical, Environmental, Chemical, Aeronautical etc.
Computer Science
Economics and Social Sciences
Accounting, Finance, Marketing, and Business Administration
Basic Sciences such as Physics, Biology, Chemistry etc.
Other related disciplines have exposure to computational problem solving, foundations of linear algebra, and introductory probability theory.

Relevant Knowledge and Skills:

Applicants from related disciplines should have foundational knowledge in:

Computational Problem-solving
Linear Algebra
Introductory Probability Theory.

Those with non-computing backgrounds may be required to take prerequisite courses, as determined by the Al Ghazali Admissions Committee depending on the academic background of the applicant. Options for fulfilling these prerequisites will be provided to accepted applicants who need them

MS DSAI Electives:

-	Stream Electives	Alternate Stream Electives
	Big Data Analytics	AI Strategy Development
	Deep Learning	Ethical and Responsible AI for Policy Making
	Computer Vision	Agentic Systems
	Digital Image Processing	Data to Knowledge Transformation
Applied Probability	Dynamic Programming and Reinforcement Learning	Data and AI Policy Making
Advanced Linear Algebra	Design and Analysis of Algorithms	Large Language Model Systems
Convex Optimization	Data Mining	Cloud Development for AI Systems
Information Theory and Machine Learning	Intelligent Computing	MLOps and Scalable AI Solutions
Introduction to Data Science	Multi Agent Systems	Advanced Computational Data Science
	Data Analytics for Business	TinyML and AI for Edge Devices
	Data, Systems, and Sustainability	Explainable AI
	Data to Knowledge Visualization
	Social Network Analysis
	Biological Networks
	Computational Genomics and AI
	System Biology
	Introduction to Game Theory
	Business Analytics
	Human centered AI Assisted Systems

Program Flexibility:

The electives within the MS DSAI program have been designed to provide students flexibility to choose the stream of their own interest.

Stream Electives:

While Stream Electives provide a traditional and rigorous way to develop mathematical and computational knowledge, preparing students to pursue higher education degree e.g. PhD.

Alternate Stream Electives:

The Alternate Stream Electives provide an alternate stream to those who aim to build their skills for pursuing a successful career in local as well as international Data Science, AI and software industry.

Below is a sample plan.
NOTE: students are free to choose electives of their choice, this is only a sample plan.

Two are – non-credit mandatory courses:

Research Methods and Innovation Strategies
Programming for AI and Data Analysis

Core Foundations of DS/AI/ML

Sr #	Requirement	Course Code	Course Name	Credit Hours
1	Mandatory	AI xxx	Foundations of AI	3
2	Mandatory	AI xxx	Machine Learning	3
3	Mandatory	AI xxx	Digital Transformation, Data Analytics and Knowledge Framework	3

Mathematical & Statistical Foundation of AI/ML

Sr #	Requirement	Course Code	Course Name	Credit Hours
		AI xxx	Applied Probability
		AI xxx	Advanced Linear Algebra
4	Student may take 1 course from this list	AI xxx	Convex Optimization	3
		AI xxx	Information Theory and Machine Learning
		AI xxx	Introduction to Data Science

Breadth in AI/ML

Sr #	Requirement	Course Name	Credit Hours
		Big Data Analytics
		Deep Learning
		Computer Vision
		Digital Image Processing
		Dynamic Programming and Reinforcement Learning
		Intelligent Computing
		Data Mining
		Design and Analysis of Algorithms
5	Student may take any 4 courses from this list	Data Analytics for Business	12
		Data, Systems, and Sustainability
		Data to Knowledge Visualization
		Social Network Analysis
		Biological Networks
		Computational Genomics and AI
		System Biology
		Introduction to Game Theory
		Business Analytics
		Human centered AI Assisted Systems

The remaining 6 Credit Hours can be completed as:

MS with Thesis Option: 6 Credit Hours Thesis
Or 2 additional electives of the student’s choice.