The B.Tech Data Science and Engineering program at Manipal Academy of Higher Education (MAHE), Dubai, is designed to prepare students with in-depth knowledge and practical skills in Artificial Intelligence, Machine Learning, Data Science, and Big Data Technologies. This B.Tech in data science and engineering program addresses the growing industry demand for data professionals across sectors such as technology, healthcare, finance, and logistics. With Dubai emerging as a hub for innovation, graduates will find themselves well-positioned to contribute to projects like Smart Dubai’s data-powered initiatives, personalised marketing strategies in retail, or predictive analytics in the financial sector.
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MAHE's School of Engineering and IT has strong partnerships with industry leaders such as CISCO, Oracle, and DELL EMC, enhancing the program's relevance and industry alignment.
Collaborations with leading tech companies offer students valuable insights, internships, and project opportunities.
The faculty of the B.Tech Computer Science Data Science consists of seasoned professionals with expertise in Data Science, Artificial Intelligence, and Big Data, providing students with a rich learning environment.
The B.Tech Data Science and Engineering college eligibility stands on essential requirements, which are as follows:
A B.Tech degree in Data Science and Engineering opens doors to diverse and dynamic career paths across industries such as technology, finance, healthcare, and e-commerce. Dubai’s strategic initiatives, including Smart Dubai and the UAE Artificial Intelligence Strategy 2031, are driving demand for professionals skilled in data science and analytics. Graduates are highly sought after for their analytical and problem-solving skills.
Here are some of the popular career paths:
In the initial phase, students build a strong foundation in mathematics, science, and core engineering principles. They'll also develop essential skills in communication, computer usage, and practical engineering applications.
| Semester 1 | Semester 2 |
|---|---|
| Engineering Mathematics - I | Engineering Mathematics - II |
| Engineering Chemistry | Engineering Physics |
| Biology for Engineers | Mechanics of Solids |
| Basic Electrical Technology | Basic Electronics |
| Problem-Solving Using Computers (PSUC) | Basic Mechanical Engineering |
| Environmental Studies | Communication skills in English |
| Physical Fitness & Wellness | Universal Human Values & Professional Ethics |
| Engineering Graphics - 1 | Workshop Practice |
| Engineering Graphics - II |
Students master mathematical concepts, programming languages, and database systems. Additionally, they'll gain hands-on experience with data analysis, machine learning, and algorithm design through rigorous lab work.
| Semester 3 | Semester 4 |
|---|---|
| Mathematical Foundations for Data Science-I | Mathematical Foundations for Data Science-II |
| Finance & Econometrics | Database Systems |
| Introduction to Data Analytics | Machine Learning |
| Object Oriented Programming | Design & Analysis of Algorithms |
| Data Structures | Data Communications and Networks |
| Computer System Architecture | Open Elective – 1 |
| Data Analytics Lab | Database Lab |
| Object-Oriented Programming Lab | Machine Learning Lab |
| Data Structures Lab | Design & Analysis of Algorithms Lab |
Students work on advanced data analysis and manipulation. Students master Deep Learning, AI techniques, and Big Data processing alongside practical labs in these specialised areas.
| Semester 5 | Semester 6 |
|---|---|
| Mathematical Foundations for Data Science-III | Operations Research |
| Deep Learning | Artificial Intelligence |
| Operating Systems | Parallel Programming |
| Natural Language Processing | Big Data Analytics |
| Cloud Computing | Data Privacy & Security |
| Open Elective – 2 | Open Elective – 3 |
| Deep Learning Lab | Artificial Intelligence lab |
| Operating Systems Lab | Parallel Programming Lab |
| Web Technologies Lab | Big Data Analytics Lab |
The final year focuses on specialisation and project application. Students choose electives to deepen their knowledge and complete a capstone project, integrating their learning into a real-world data science challenge.
| Semester 7 | Semester 8 |
|---|---|
| Program Elective - I | Industrial Training |
| Program Elective – II | Project Work |
| Program Elective – III | |
| Program Elective – IV | |
| Program Elective - V | |
| Open Elective – 4 |
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