MS Data Science & AI (MS DS & AI)

Transforming Data into Intelligent Solutions
Build the Future with Data and Intelligence

Introduction

The future belongs to those who can transform data into intelligent decisions.
The MS in Data Science & AI program at GU TECH is designed to prepare professionals, researchers, and innovators capable of solving real-world challenges using advanced data analytics and Artificial Intelligence technologies.

Program Summary

Data Science has emerged as a powerful discipline for enabling data-driven decision making across industries. Organizations worldwide are increasingly investing in transforming raw data into actionable knowledge and intelligent insights.

At the same time, Artificial Intelligence has become essential for building intelligent systems capable of solving complex real-world problems. Individually, Data Science and AI offer significant value; however, the future belongs to professionals who can integrate both domains to develop impactful, scalable, and intelligent solutions.

Why this Program?

• Industry aligned curriculum

• AI + Data Science integrated learning

• Real-world projects and research

• Focus on innovation and problem solving

• Hands on development of AI enabled systems
• Opportunities in healthcare, finance, business, smart systems, and emerging technologies

Interdisciplinary and Domain Focused Learning

The MS in Data Science & AI program is specifically designed for students and professionals coming from diverse academic and professional backgrounds. Whether a learner belongs to healthcare, business, engineering, social sciences, finance, education, or technology, the program enables them to leverage their existing domain expertise while harnessing the power of Data Science and Artificial Intelligence.

The combination of domain knowledge with data-centric thinking and AI-enabled problem solving empowers students to identify meaningful real-world problems, analyze complex datasets, and design intelligent products and solutions relevant to their respective industries. This interdisciplinary approach creates professionals who not only understand technology, but also understand the context and impact of the problems they are solving.

The MS in Data Science & AI program is designed to prepare future innovators and problem solvers who can:

• Analyze complex data centric challenges
• Identify meaningful patterns and feature sets
• Build AI enabled intelligent systems
• Develop practical solutions and products for real-world applications

This interdisciplinary program combines strong foundations in:

• Data Analytics
• Machine Learning
• Artificial Intelligence
• Predictive Modeling
• Decision Intelligence
• AI driven Product Development

Students will gain the knowledge and practical expertise required to solve problems from a data centric perspective while leveraging AI technologies for innovation and transformation.

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.

Career Pathways

Graduates can pursue careers as:

Data Scientists
AI Engineers
Machine Learning Specialists
Business Intelligence Analysts
AI Product Developers
Research Scientists

Program Vision

To develop future leaders capable of solving complex societal and industrial challenges through data centric thinking and AI driven innovation.

Outcome

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.

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

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

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

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.