B Tech Data Science & Engineering

Undergraduate Entry Requirements

Application Fee: AED 3150

Academic Qualifications: Applicants for undergraduate programs typically require a minimum academic achievement of 50% or above in their previous academic qualifications.

English Language Proficiency:

• Adequate proficiency in English is a must for all programs

Manipal University Dubai (MUD) offers various scholarships to international students to help ease the financial burden and encourage academic excellence. These scholarships are designed to recognize the hard work, talent, and potential of students, making quality education more accessible. The university’s scholarship programs are aimed at supporting students who demonstrate strong academic performance, leadership qualities, or financial need.

Merit-Based Scholarships: MUD provides merit-based scholarships to international students who have demonstrated exceptional academic achievements in their previous studies. These scholarships are awarded based on the student’s performance during the admission process, and the amount can vary depending on the program and qualifications. These scholarships are highly competitive and are awarded to students who have excelled in their respective fields.

Sports Scholarships: Students with exceptional skills in sports can avail themselves of the sports scholarships offered by Manipal University Dubai. These scholarships are aimed at encouraging student-athletes to maintain a balance between their academic and athletic pursuits. MUD provides support for international students who represent the university in various sports events and competitions.

Need-Based Scholarships: To assist students who may face financial difficulties, MUD offers need-based scholarships. These scholarships are designed to support international students from financially disadvantaged backgrounds and provide them with the opportunity to pursue higher education without financial constraints. Students are required to demonstrate their financial need and provide supporting documentation to be considered for these scholarships.

Program-Specific Scholarships: Manipal University Dubai offers several program-specific scholarships for international students enrolled in certain courses. These scholarships may vary depending on the program of study and are awarded based on academic merit or other criteria set by the university. Scholarships are available in various disciplines, including engineering, business, design, and computer science.

Graduates of the B Tech in Data Science & Engineering program from Manipal University Dubai have access to a wide array of exciting career opportunities across various sectors that are increasingly relying on data-driven decision-making. The global demand for skilled data professionals continues to rise, and this program equips students with the necessary skills to thrive in the ever-evolving world of data science and engineering. 

Data Scientist: Data scientists analyze large datasets to extract valuable insights and develop predictive models that can help businesses make data-driven decisions. They work with a variety of tools and techniques, including machine learning algorithms, statistical models, and data visualization tools.

Data Analyst: Data analysts focus on interpreting data to provide actionable insights that support business decisions. They work with data to identify trends, patterns, and correlations, and use these insights to guide strategies in areas such as marketing, finance, and operations.

Machine Learning Engineer: Machine learning engineers design and implement machine learning algorithms that allow computers to learn from data without explicit programming. They work closely with data scientists to develop models that improve over time as more data becomes available.

Big Data Engineer: Big data engineers specialize in managing, processing, and analyzing massive datasets. They are responsible for building and maintaining the infrastructure required to handle big data, including distributed computing systems, databases, and cloud technologies.

Business Intelligence Analyst: Business intelligence analysts use data analytics tools to analyze business performance and develop strategies for growth. They work closely with company leadership to transform data into actionable insights that support organizational objectives.

AI Engineer: AI engineers develop and implement artificial intelligence solutions that simulate human intelligence, such as natural language processing, computer vision, and speech recognition. They are at the forefront of developing intelligent systems that improve business processes and user experiences.

Data Engineer: Data engineers design, construct, and maintain the architecture that allows organizations to process and analyze large datasets. They ensure that data is collected, stored, and processed in an efficient and secure manner, making it available for analysis by data scientists and analysts.

Data Architect: Data architects design the structure and framework for an organization’s data storage and retrieval systems. They ensure that data is organized in a way that enables efficient access and analysis, and they work closely with IT teams to implement scalable data infrastructure.

Cloud Computing Specialist: Cloud computing specialists focus on utilizing cloud platforms such as AWS, Azure, and Google Cloud to store, process, and analyze data. They manage cloud infrastructure and design systems that leverage cloud technologies for big data processing and analytics.

Quantitative Analyst: Often found in finance, quantitative analysts use advanced statistical and mathematical models to analyze financial data and develop strategies for investment, risk management, and pricing. Their work often involves programming, data analysis, and machine learning techniques.

Cybersecurity Analyst: Cybersecurity analysts in data science protect an organization’s data from cyber threats and ensure that data systems are secure. They implement security protocols, monitor systems for vulnerabilities, and use data analytics to detect unusual behavior that may indicate a security breach.

Operations Research Analyst: Operations research analysts use data-driven methods to solve problems related to logistics, supply chain management, and optimization. They use mathematical models and analytical tools to improve operational efficiency and reduce costs.

Business Analyst: Business analysts in data science work closely with stakeholders to understand business needs and translate them into data requirements. They use data analysis and visualization to identify business opportunities and help organizations implement strategies to achieve their goals.

Database Administrator: Database administrators manage and maintain databases, ensuring that data is organized, stored, and accessible. They ensure the integrity, security, and performance of databases used for data analysis and decision-making.

Statistician: Statisticians in the data science field use mathematical and statistical models to analyze data and draw conclusions. They apply these methods to various industries, including healthcare, government, and market research.

Product Manager (Data Products): Product managers with a background in data science focus on developing and managing data-driven products. They work with data teams to create tools and platforms that leverage data to solve specific business problems and create value for customers.

Consultant (Data Science): Data science consultants work with businesses to identify their data needs and recommend solutions. They help organizations develop data strategies, implement analytics platforms, and optimize their data operations to improve business outcomes.

Entrepreneur/Data Start-up Founder: Graduates with an entrepreneurial mindset may choose to start their own data-focused businesses, such as data consulting firms, AI development companies, or tech start-ups that focus on leveraging data for innovative solutions.

Operations Manager (Data-Driven Operations): Operations managers use data to optimize operational processes, improve efficiency, and reduce costs. They use analytics tools to monitor performance and make data-driven decisions to enhance organizational productivity.