The PG Diploma in Data Science at Manipal Academy of Higher Education, Dubai, combines campus-based and online learning, catering to the needs of aspiring professionals. Students also explore machine learning, deep learning and natural language processing, culminating in the ability to develop recommendation systems. Our data science course in Dubai introduces participants to the field's core aspects. It covers programming languages, algorithms, statistical models and optimisation techniques crucial for tackling complex decision-making problems. The program adheres to industry standards, focusing on practical skills for data management—from acquisition and cleaning to transformation—and the application of business intelligence tools and visualisations within cloud computing environments.
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This PG Diploma in Data Science begins with preparatory courses, which ensure students have the essential background knowledge. They lay the groundwork for successful engagement with the more advanced topics, setting a solid foundation for future learning and application. Programming for Data Science and Statistical Techniques for Data Science are the preparatory courses introduced to students before Term 1.
The PG Diploma in Data Science at Manipal Academy of Higher Education, Dubai, further employs a dynamic learning methodology that includes case studies, tool-based learning, project-based learning, group activities, workshops and seminars. This approach ensures a comprehensive understanding of data science, fostering critical thinking and problem-solving skills. Furthermore, it prepares students for real-world challenges by simulating practical scenarios and collaborative projects.
The following are the key eligibility criteria for prospective students:
The PG Diploma in Data Science course from Manipal Academy of Higher Education, Dubai, opens doors to many career opportunities in the rapidly evolving data-driven landscape. Students can step into various roles, including:
The first term sets the foundation by introducing students to the fundamental principles and tools essential for data science. It is designed to build a strong base in data handling, analysis and the application of machine learning techniques.
| Term 1 |
|---|
| Data Science Toolkit |
| Machine Learning |
Students get the opportunity to specialise in one of two areas, based on their interests and career goals. This term emphasises analytical frameworks, data modelling and innovations in the field, preparing individuals to align their learning with the latest industry demands and methodologies.
Term 2 (Specialisation) Artificial Intelligence for Data Science | Term 2 (Specialisation) Business and Data Analytics |
|---|---|
| Advanced Machine Learning | Data Analytics Toolkit |
| Natural language Processing | Business Intelligence |
It is dedicated to applying the comprehensive skill set acquired in the previous terms to practical and real-world situations. Students select electives that allow them to explore specific interests further. Additionally, a significant component of this term is devoted to project work, where students engage in hands-on projects, demonstrating their readiness to enter the professional world of data science.
| Term 3 |
|---|
Elective - 1: Advanced Visualisation Big Data Technologies |
| Project Work/Practice School |
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