Bachelor of Data Science
Admission to Program
Admission to the program is explained in the HCT Admission Policy described in the Academic Policies section of this Catalogue.
Program Mission
Prepare graduates to be Information Communication Technology (ICT) professionals in technical and organizational leadership roles, embracing innovation and discovery and striving for professional growth through lifelong learning in fields associated with Data Science, with a strong focus on enhancing Information Systems.
Program Description
The Bachelor of Data Science program is designed to equip students with the necessary knowledge and skills to apply ethical values to complex and unpredictable problems, and to plan, design, implement, evaluate, and manage an organization’s ICT infrastructure.
The program provides a comprehensive understanding of information technology assets, archival, and information processing systems within the context of data science applications. Throughout their studies, students will develop proficiency in fundamental concepts and skills across various information technologies, preparing them for roles where they can harness the power of data to drive organizational success.
The Bachelor of Data Science program is structured as a set of cores, elective, general studies, and specialized courses. Within the core curriculum, students gain fundamental knowledge, skills, and competencies crucial for Information Systems, which are further enhanced by specialized courses aligned with current industry trends in Data Science. To integrate theoretical knowledge with practical experience, the program offers a year-long apprenticeship, enabling students to acquire valuable real-world skills. This holistic approach ensures graduates are well-prepared to succeed in the dynamic field of Data Science.
Program Goals
- Equip graduates with the necessary technical knowledge and skills to design and develop data-driven solutions to specific business challenges in accordance with industry best practices in data science.
- Prepare graduates for a successful career as effective decision makers with strong communication and teamwork skills and an understanding of global, ethical, and social implications of the industry and Data Science profession.
- Prepare graduates with technical and entrepreneurial leadership qualities, who support the development of innovative computing solutions in response to local, regional, or global challenges.
- Equip graduates with strong commitment to lifelong learning, continuing education, and professional growth.
Program Learning Outcomes
1. Demonstrate an understanding of critical analysis, research systems and methods, and evaluative problem- solving techniques, showing familiarity with sources of current and new research in the field of computing.
2. Analyze a complex computing problem and apply principles of computing and other relevant disciplines to identify solutions.
3. Design, implement, and evaluate a computing-based solution to meet a given set of computing requirements in the context of the program's discipline.
4. Communicate effectively in a variety of professional contexts.
5. Recognize professional responsibilities and make informed judgments in computing practice based on legal and ethical principles.
6. Function effectively as a member or leader of a team engaged in activities appropriate to the program's discipline.
7. Apply theory, techniques, and tools throughout the data science lifecycle and employ the resulting knowledge to satisfy stakeholders’ needs.
Completion Requirements
Students must successfully complete a minimum of 120 credits, including:
| Code | Title | Credit Hours |
|---|---|---|
| CIS Core Courses | 33 | |
| Data Science Specialisation Courses | 63 | |
| Elective Courses | 6 | |
| General Studies | 18 | |
| Total Credits | 120 | |
To qualify for the bachelor's degree, a student is required to:
- Successfully complete the required number of credits and courses specific to the program with a minimum cumulative GPA of 2.0.
- Complete 100 hours of volunteering.
- Meet the residency requirement that a minimum of 50% of the program credit requirements have been completed at the HCT.
| Code | Title | Credit Hours |
|---|---|---|
| CIS Core Courses | ||
| Required Credits: 33 | ||
| CIS 1313 | Introduction to Computer Systems and Networks | 3 |
| CIS 1203 | Web Technologies | 3 |
| CIS 1603 | Programming I | 3 |
| CIS 1213 | Introduction to Information Security | 3 |
| CIS 1303 | Database Systems | 3 |
| CIS 1613 | Programming II | 3 |
| CIS 2033 | User Centered Design | 3 |
| CIS 2023 | Applied Discrete Mathematics | 3 |
| CIS 2213 | Full-stack Web Application Development | 3 |
| CIS 2113 | Introduction to Software Engineering | 3 |
| CIS 3603 | Project Management | 3 |
| Code | Title | Credit Hours |
|---|---|---|
| Data Science Specialisation Courses | ||
| Required Credits: 63 | ||
| CDS 2413 | Programming for Data Science | 3 |
| CDS 2433 | Business Process Modeling and Optimization | 3 |
| CDS 2443 | Advanced Database Systems | 3 |
| CSE 2623 | Algorithms and Data Structures | 3 |
| CDS 3513 | Data Mining Techniques | 3 |
| CDS 3523 | Statistical Inference | 3 |
| CDS 3533 | Big Data Analytics | 3 |
| CDS 3543 | Data visualization for Decision making | 3 |
| CDS 3613 | Enterprise Solution Management | 3 |
| CDS 3623 | Data Mining for Enterprise Solutions | 3 |
| CDS 3633 | Machine Learning for Business Analytics | 3 |
| CDS 3643 | Time Series Analysis and Forecasting | 3 |
| CIS 3503 | Technopreneurship | 3 |
| CDS 4723 | Capstone Project I | 3 |
| CDS 4733 | Business Process Automation | 3 |
| CDS 4823 | Capstone Project II | 3 |
| CDS 4833 | IT and Data Strategy and Governance | 3 |
| CDS 4716 | Apprenticeship I (*) | 6 |
| CDS 4816 | Apprenticeship II (*) | 6 |
| *Apprenticeship Courses | ||
| Code | Title | Credit Hours |
|---|---|---|
| Elective Courses | ||
| Required Credits: 6 | ||
| CIB 4003 | E Business Applications Development | 3 |
| CIB 4113 | Accounting and Finance Analytics | 3 |
| CIS 4003 | Green Computing | 3 |
| CSF 4613 | Security Intelligence | 3 |
| Code | Title | Credit Hours |
|---|---|---|
| General Studies | ||
| Required Credits: 18 | ||
| LSM 1013 | Mathematics for Computing | 3 |
| LSC 1103 | Professional Written Communication | 3 |
| LSS 1133 | Critical Thinking and Research Skills | 3 |
| CIS 1703 | Introductory Statistics and Probability | 3 |
| CIS 2603 | Artificial Intelligence Foundations | 3 |
| AES 1003 | Emirati Studies | 3 |
| Description | Data |
|---|---|
| Total Required Credits | 120 |
| Maximum Duration of Study | 6 years |
| Minimum Duration of Study | 4 years |
| Cost Recovery Program | No |
| Program Code | BADSC |
| Major Code | CDS |
Recommended Sequence of Study
| Year 1 | ||
|---|---|---|
| Semester 1 | Credit Hours | |
| CIS 1313 | Introduction to Computer Systems and Networks | 3 |
| CIS 1203 | Web Technologies | 3 |
| CIS 1603 | Programming I | 3 |
| LSM 1013 | Mathematics for Computing | 3 |
| LSC 1103 | Professional Written Communication | 3 |
| Credit Hours | 15 | |
| Semester 2 | ||
| CIS 1213 | Introduction to Information Security | 3 |
| CIS 1303 | Database Systems | 3 |
| CIS 1613 | Programming II | 3 |
| CIS 1703 | Introductory Statistics and Probability | 3 |
| LSS 1133 | Critical Thinking and Research Skills | 3 |
| Credit Hours | 15 | |
| Year 2 | ||
| Semester 3 | ||
| CIS 2033 | User Centered Design | 3 |
| CIS 2023 | Applied Discrete Mathematics | 3 |
| CIS 2213 | Full-stack Web Application Development | 3 |
| CIS 2113 | Introduction to Software Engineering | 3 |
| CIS 2603 | Artificial Intelligence Foundations | 3 |
| Credit Hours | 15 | |
| Semester 4 | ||
| CDS 2413 | Programming for Data Science | 3 |
| CDS 2433 | Business Process Modeling and Optimization | 3 |
| CDS 2443 | Advanced Database Systems | 3 |
| CSE 2623 | Algorithms and Data Structures | 3 |
| AES 1003 | Emirati Studies | 3 |
| Credit Hours | 15 | |
| Year 3 | ||
| Semester 5 | ||
| CDS 3513 | Data Mining Techniques | 3 |
| CDS 3523 | Statistical Inference | 3 |
| CDS 3533 | Big Data Analytics | 3 |
| CDS 3543 | Data visualization for Decision making | 3 |
| CIS 3603 | Project Management | 3 |
| Credit Hours | 15 | |
| Semester 6 | ||
| CDS 3613 | Enterprise Solution Management | 3 |
| CDS 3623 | Data Mining for Enterprise Solutions | 3 |
| CDS 3633 | Machine Learning for Business Analytics | 3 |
| CDS 3643 | Time Series Analysis and Forecasting | 3 |
| CIS 3503 | Technopreneurship | 3 |
| Credit Hours | 15 | |
| Year 4 | ||
| Semester 7 | ||
| CDS 4716 | Apprenticeship I | 6 |
| CDS 4723 | Capstone Project I | 3 |
| CDS 4733 | Business Process Automation | 3 |
| 4000 Level Elective | 3 | |
| Credit Hours | 15 | |
| Semester 8 | ||
| CDS 4816 | Apprenticeship II | 6 |
| CDS 4823 | Capstone Project II | 3 |
| CDS 4833 | IT and Data Strategy and Governance | 3 |
| 4000 Level Elective | 3 | |
| Credit Hours | 15 | |
| Total Credit Hours | 120 | |
Aaesha Mohammed Rashed Saif A Al Shehhi, Master of Applied Science, Project Management, Higher Colleges of Technology, United Arab Emirates
Abdul Haque Farquad Mohammed, PhD, Computer Science, University of Hyderabad, India
Ahmed Bani Mustafa, Ph.D., Data Science and Artificial Intelligence, University of Wales, Aberystwyth (Aberystwyth University), United Kingdom
Akram Al-Kouz, Ph.D., Computer Science, Technical University, Berlin, Germany
Alexandros Alexandropoulos, Doctorate in Philosophy, Computing, The University of Manchester, United Kingdom
Amala Rajan, PhD, Computer Science and Engineering, Middlesex University, London, United Kingdom
Anang Hudaya Bin Muhamad Amin, Ph.D, Artificial Intelligence, Monash University, Australia
Anas Arram, Ph.D., Computer Science, National University of Malaysia (UKM), Malaysia
Anatoliy Lut, Master of Engineering, Computer Science and Technology, University of Electronic Science and Technology of China, China
Ashraf Abou Tabl, Ph.D., Computer Engineering, University of Windsor, Canada
Asif Malik, Master of Science, Distributed Computing System, University of Greenwich, United Kingdom
Divya Prakash Shrivastava, Doctor of Philosophy, Computer Science, Barkatullah University, India
Eslam Badran, Master of Science, Computer Science, Universiti Putra Malaysia, Malaysia
Fatema Abdulla Mohammed Ghallab Ali, Master of Applied Science, Info SysMgt (Innovation & Design), Higher Colleges of Technology, United Arab Emirates
Fatimah Ishowo-Oloko, Ph.D., Interdisciplinary Engineering, Masdar Institute of Scie & Tech, United Arab Emirates
Fatmah Mohamed Hassan Morad, Masters, Quality Management, University of Wollongong, United Arab Emirates
Fethi Guerdelli, Ph.D., Computer Science, University of Québec at Montréal, Canada
Ghazi Ben Ayed, Ph.D., Information Systems, University of Lausanne, Switzerland
Ghulam Bhatti, Ph.D., Computer Science, Boston Univ, United States
Hatem Tamimi, Ph.D., Management Information Systems, Anglia Ruskin University, United Kingdom
Heba Mohammad, Ph.D., E-Business, University of Salento, Italy
Imad Ahmed, Ph.D. Comp.& Automated Sys. Software, University of Leeds, UK
Jaber Jemai, Ph.D., Computer & Information Science, Tunis University, Tunisia
Jim Otieno, Ph.D., Computing, Middlesex University, UK
Keletso Letsholo, Ph.D., Computer Science, The University of Manchester, United Kingdom
Kheir Eddine Bouazza, Ph.D., Computer Engineering, Univ Henri Poincare- Nancy, France
Lennox Nkqubela Ruxwana, Ph.D., Information Technology, Nelson Mandela Metropolitan University, South Africa
Lina Daouk, Master of Science, Instructional Technology, New York Institute of Tech, United States
Marwa Al Shamsi, Bachelor of Science, Management Information System, Univ of Sharjah, United Arab Emirates
Melina Silva, Master of Business Administration, Management Info Technology, Nanyang Technological Univ, Singapore
Milan Dordevic, Doctor of Science, Computer Science, University of Primorska, Slovenia
Mohammed Abdul Rahim, Ph.D. Computer & Information Science, Anglia Ruskin University, Cambridge UK
Mohammed Hassouna, Ph.D., Information Systems and computing, Brunel University, United Kingdom
Muhammad Hashmi, Ph.D., Computer Science, University of Paris VI, France
Munir Naveed, Ph.D, Computer Science, University of Huddersfield, United Kingdom
Mustafa Akpinar, Ph.D., Computer and Information Engineering, Sakarya University, Turkey
Nor Azizah Hitam, Ph.D., Computer Science, Int'l Islamic Univ Malaysia, Malaysia
Nor Shahriza Abdul Karim, Ph.D., Information Science and Technology, Syracuse University, USA
Nur Siyam, Doctorate, Computer Science, British University in Dubai, United Arab Emirates
Osama Harfoushi, PhD, Information Systems, University of Bradford, United Kingdom
Oussama Hamid, PhD, Science, Reinforcement Learning, Otto-von-Guericke University, Germany
Pedro Flores, Ph.D., Information Technology, St. Paul University, Philippines
Ramakrishnan Raman, Masters in Engineering, Computer Science & Engineering, Anna University, India
Rejitha Ravikumar, Master of Science, Operations Research and Computer Applications, National Institute of Technology, Trichy, India
Rula Al Kayyali, Ph.D., Education, RMIT University, Australia
Shaikha Saoud Khalid Humaid Al Qasemi, Master of Applied Science, Information System Management, Higher Colleges of Technolgy, United Arab Emirates
Sharmila Siddartha, Master of Science, Informatics(Knowledge & DataMgt), British University in Dubai, United Arab Emirates
Shawulu Nggada, Ph.D, Computer Science, The University of Hull, United Kingdom
Shazia Asif, Master of Science, Information Technology, Preston University, Pakistan
Suaad Hasan Ali Ebrahim Al Mansoori, Ph.D., Computer Science, British University in Dubai, United Arab Emirates
Syed Shah Khan, Master of Science, Electrical Engineering Tech, Case Western Reserve Univ, United States
Vishwesh Laxmikant Akre, PhD, Software Engineering, University of Salford, United Kingdom
Yun-Ke Chang, Ph.D., Information Science, University of North Texas, United States
Zakea IL-Agure, Ph.D., Computer & Information Science, Staffordshire University, United Kingdom
Zamhar Ismail, Ph.D., Informatics, The University of Manchester, United Kingdom