Master of Science in Data Science and Analytics

COURSE OVERVIEW

Data is all around us. Every day, we gather and keep a greater variety and quantity of data—from the most basic retail transactions to the intricate and personal medical records of millions of people. The need for managers, supervisors, and analysts with the ability to oversee and provide insight into data usage is growing. These people need to be knowledgeable about statistics, mathematics and computer science in addition to being acquainted with the various data requirements and procedures that are needed in the commercial, government, healthcare, and environmental sectors.

Our Data Science and Analytics Masters degree offers you the opportunity to develop a range of relevant skills including:

1. analyzing structured and unstructured data
2. analyzing large datasets
3. critically evaluating results in context
4. getting insights from data

The course combines expertise from the disciplines of Mathematics, Statistics, Computer Science, Business, and Economics. This combination allows you to benefit from a range of data science perspectives and applications, allowing you to tailor the course to match your own career ambitions.

Details of the Course Curriculum

WHY STUDY AT EWU

1. Our faculty members are globally-renowned researchers who can teach you the latest of the data science and analytics courses, shaping your learning with the latest thinking in areas such as mathematics, statistics and computer technology along with machine learning and artificial intelligence applied to real life practical problems.
   
   
2. Advance your knowledge and skills in key areas of data science, both theoretically and practically.
   
   
3. Tailor the degree to suit your specific interests with a broad selection of optional modules to choose from such as machine learning for financial technology, data analytics for finance, applied econometrics, AI and deep learning and many more.
   
   
4. Put theory into practice by conducting a project which focuses on a real-world problem, giving you the chance to apply the knowledge acquired throughout the course and demonstrate independent research skills necessary for a professional or academic career.
   
   
5. Access excellent teaching facilities including world-class library and computing equipment throughout the university.
   
   
6. Theoretical and practical teaching is delivered by a program team made up of academics who are experts in the field of data science and analytics

We are really happy to invite you to meet us here at EWU to learn about the exciting field of data science and analytics and discuss about the opportunities and future prospects of the graduates of MS in Data Science and Analytics with our leading academics and professionals.

Faculty members teaching data science and analytics have a variety of skill sets that are necessary for this new field. The curriculum offers advanced instruction in data science and analytics approaches and principles, emphasizing how these fields can be used to solve issues in a range of business, governmental, and academic contexts. The most in-demand core competences in the market are technical abilities like programming, statistics, and mathematics. These competencies are what the Master's program is intended to provide.

Join us at East West University and become a Data Scientist.

Financial Assistance

There is a provision for 100%, 75%, and 50% tuition waiver depending on the previous academic credentials of the applicants.

Faculty Members involved in Teaching MS in Data Science and Analytics

Ahmed Wasif Reza,  PhD; Professor; AI & Deep Learning

Sohel Rana, PhD; Associate Professor; Multivariate Statistical Analysis

Mostofa Kamal Rasel, PhD; Assistant Professor; Database System

Muntasir Chaudhury, PhD; Assistant Professor; Applied Econometrics

M. Rifat A. Rashid, PhD; Assistant Professor; Programming for Data Science

M.H.M. Imrul Kabir, MSc; Senior Lecturer; Time Series Analysis

F.M. Ariful Rahman, MSc; Senior Lecturer; Regression Analysis

Syed Akhter Hossain, PhD; Professor, Adjunct, Database Systems

Zakir Hossain, PhD; Professor, Adjunct, Statistical Methods, Probability Theory

Rezaul Karim, PhD; Associate Professor, Adjunct, Machine Learning & Big Data

Anamul Haque Sajib, PhD; Associate Professor, Adjunct, Regression Analysis, Biostatistics

Admission Eligibility

1. Minimum GPA of 2.50 in both SSC and HSC Examinations. Or Candidates must have passed University of London and Cambridge GCE ‘O’ Level in at least five subjects and ‘A’ Level in at least two subjects. Only the best five subjects in ‘O’ Level and best two subjects in ‘A’ Level will be considered. Out of these seven subjects, a candidate must have at least 4B’s or GPA of 4.00 in the four subjects and 3 C’s or GPA of 3.5 in the remaining three subjects. (in the scale of A=5, B=4, C=3, D=2 and E=1).
2. Applicants are required to have a four-year undergraduate degree in Statistics/ Mathematics/Engineering/Science/Business/Economics with good background of Mathematics, or a three-year undergraduate degree and one-year master’s degree in any of the above-mentioned subjects with a minimum CGPA of 2.50 out of 4.
   
   

Tuition and Others Fee

Document Verification Fee
Students will pay the document verification fee (if applicable) for the verification of their previous academic documents.