Program Overview

Master of Science in Data Science

The Master of Science (M.Sc.) in Data Science program is carefully crafted to equip students with the necessary skills and knowledge for a successful career in data analysis, computing, and applied mathematics. This program aims to enhance students' employability by providing them with a high level of expertise in the field.

Overview

Upon completion of the program, graduates will possess the skills required to excel in the public and government sectors, opening up numerous opportunities for career advancement. Additionally, the private sector also offers promising prospects for graduates, as they will have a strong understanding of statistical analysis and automated decision-making processes. This valuable knowledge makes them desirable candidates for businesses, industries, and IT firms.

Program Details

• Type: Graduate
• Duration: 2 years
• Credit Hours: 30 hours
• Intake: Fall & Spring
• Study Mode: Full & Part time
• Language: English

Admission Requirements

Regular Admission

• Accredited bachelor's degree in IT or an equivalent degree with a minimum GPA of 3.0
• EmSAT 1400
• Academic IELTS 6.0 or TOEFL (PBT 550 or IBT 79 or CBT 213)

Conditional Admission

• Accredited bachelor's degree in IT or an equivalent degree with a minimum GPA of 2.50 - 2.99
• EmSAT 1250
• Academic IELTS 5.5 or TOEFL (PBT 530 or IBT 71 or CBT 197)

Who Is This Program For?

A data science master's degree program is typically designed for individuals who have a strong background in mathematics, statistics, computer science, or a related field and are interested in pursuing a career in data science. It is a specialized program that provides advanced training and knowledge in the field of data science, combining elements of statistics, machine learning, computer science, and domain expertise.

Career Opportunities

A Master of Science in Data Science can open up a wide range of career opportunities in various industries. The demand for data scientists continues to grow as organizations seek to leverage the power of data for insights, decision-making, and problem-solving. Potential career paths include:

• Data Scientist
• Data Analyst
• Machine Learning Engineer
• Business Intelligence Analyst
• Data Engineer
• Data and Analytics Consultant
• Research Scientist

Estimated Salary Range

Salaries for Master of Science in Data Science holders in the UAE can vary depending on factors such as the level of experience, the industry, the size and reputation of the company, and the specific job role. Estimated salary ranges include:

• Entry-level Data Analyst or Data Scientist: AED 8,000 to AED 12,000 per month
• Mid-level Data Scientist or Data Engineer: AED 12,000 to AED 20,000 per month
• Senior Data Scientist or Data Science Manager: AED 20,000 to AED 40,000 per month

Study Plan

The Master of Science in Data Science is broken down into four semesters, having 30 CH course (8 courses of which 3 courses are offered each semester + 1 Master Thesis of 6 CH).

Year 1

Semester 1

1. DS601 - Fundamentals of Data Science
2. DS602 - Statistics & Probability in Data Science
3. DS603 - Advanced Database Queries and Data Warehouse in Data Science

Semester 2

1. DS621 - Research Methods in Data Science
2. DS620 - Data Visualization & Data Representation Techniques
3. DS604 - Big Data Management using Hadoop

Year 2

Semester 3

1. DSXXX - Electives 1
2. DSXXX - Electives 2
3. DS629 - Data Science Thesis

Semester 4

1. DS629 - Data Science Thesis (Continued from Semester 3)

Courses Description

• DS 601 Fundamentals of Data Science: Introduces the principles of data science field and common functionalities of toolkits suitable for a data scientist portfolio.
• DS 602 Statistics and Probability in Data Science: Covers the foundations of probability and statistics necessary for modeling and undertaking statistical decisions.
• DS 603 Big Data Management Using Hadoop: Introduces the fundamentals of managing big data and the corresponding standard big data platform.
• DS 604 Advanced Database Queries and Data Warehouse in Data Science: Provides review concepts and practices as applied to database and data warehouse.
• DS 620 Data Visualization & Data Representation Techniques: Focuses on data visualization techniques for effective communication of data science results.
• DS 621 Research Methods in Data Science: Prepares students to prepare their thesis or research project proposal.
• DS 623 Machine Learning in Data Science: Introduces machine learning techniques and methods.
• DS 624 Text mining in Data Science: Introduces text mining and manipulation techniques.
• DS 625 Social Network Analysis in Data Science: Involves hands-on practices using real-world documents.
• DS 626 Management Data Science: Applies the tools and techniques of management science to engineering problems.
• DS 628 Ethics in Data Science: Introduces ethics, policies, and legal issues that face computer professionals and data scientists.
• DS 631 Data Science Thesis: Provides an opportunity to analyze large-scale real-world problems according to the scientific methods.