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Master of Science in Data Science and Analytics

1. Introduction

Computer and information technologies have undergone a significant paradigm shift globally. Technology is all around us, the world is more connected than ever, and computers are getting more powerful. Advanced data management and statistical computing are now more necessary than ever due to the growth of science and technology as well as the widespread use of technological tools in a variety of disciplines. This demand caused the subject of data science and analytics to develop. Numerous colleges and universities offer Data Science and Analytics program at the undergraduate and graduate levels to fill this requirement.

It has now become essential to adapt the MS program in applied statistics and its curriculum to MS in Data Science & Analytics in order to meet the demands and developments mentioned above.

2. Justification behind the change of the name of the program

Data of all forms and sizes is at the foundation of the fourth industrial revolution, which is being fueled by the interconnectedness of smart devices, the internet of things (IoT), cloud computing, automation, and artificial intelligence. In order to manage systems and make decisions effectively, it is now crucial to understand how to gather, store, analyze, and report on such a wide range of data.

In addition to that, there are several natural and man-made calamities that need to be addressed. Analyzing statistical data is also necessary for monitoring various initiatives and formulating policy. Bangladesh is actively working to meet the Sustainable Development objectives by 2030, and statistics are crucial to understanding the current state of the objectives' progress and the actions required reaching them.

This new program, the Master of Science in Data Science and Analytics, addresses the aforementioned difficulties. The program curriculum has to be updated in light of current and upcoming demands as well as recent advances. As a result, the program's new name and enhanced curriculum are obvious.

3.  Scope of the Master of Science in Data Science and Analytics

This curriculum has been carefully designed to satisfy the rising need for data scientists in Bangladesh and throughout the world. The curriculum will educate graduates for careers as data scientists and analysts, which involves applying computational, mathematical, and statistical methods to the scientific disciplines in both the public and commercial sectors.

4.  Admission Requirements

Applicants are required to have a four-year undergraduate degree in Statistics/ Mathematics/ Science/ Engineering/ 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.

5.  Program Structure

This is 40-credit hours one year program for regular students. Students are needed to complete 28 credits as core courses and the rest of the credits from elective courses. Core courses provide an understanding of the basis of all statistical methods and modeling for data science. The elective courses cover the broad areas of data science & analytics including sciences, engineering, economics, and business.

6.  Career Prospects

The future of this sector is quite bright for graduates. The use of data, as well as monitoring and decision-making are becoming more and more common. Additionally, there is a high need in academia, government, and enterprises for research consultants, business analysts, and data scientists.The numerous employers in the field of data science and analytics include NGOs, banks and insurance firms, planning and IT sectors, health research organizations, human development organizations, agricultural research institutions, etc. Additionally, data scientists and analysts are in great demand in research facilities, academic institutions, telecommunications firms, social media platforms, online and traditional entrepreneurs, and non-profit organizations.

7.  Curriculum for MS in Data Science and Analytics

Total credit hours of the program in MS in Data Science & Analytics are 40 and the credit distribution is as described below:

                        A.  Core Courses          28C
                        B.  Elective Courses      12C 
                                                 -----
                                                  40C

A. Core Courses (28C)
Students must take all 8 courses listed below:

Credit Hours
Course Number & Title
3
DSA5001: Statistical Methods and Probability
3
DSA5002: Programming for Data Science
3
DSA5003: Database Management Systems
3
DSA5004: Regression Analysis
3
DSA5005: Multivariate Statistical Analysis
3
DSA5006: Machine Learning
3
DSA5007: Big Data & Cloud Computing
7
DSA5099: Research Project
28
<= Total

B.  Elective Courses   (4 courses 12C)
Students must choose any 4 courses from the following list of courses.

Credit Hours
Course Number & Title
3
DSA5011: AI & Deep Learning
3
DSA5021: Time Series Analysis & Forecasting
3
DSA5041: Applied Econometrics
3
DSA5043: Business Process Analytics
3
DSA5045: Machine Learning for Finance
3
DSA5047: Data Analytics for Finance
3
DSA5061: Environmental Data Analysis and Climate Change
3
DSA5063: Bioinformatics
3
DSA5065: Biostatistics & Epidemiology
3
DSA5071: Generalized Linear Models
3
DSA5073: Categorical Data Analysis
3
DSA5075: Design of Experiment
3
DSA5077: Actuarial Data Analysis
12
<= Total

8.  Detailed Course Descriptions

For detailed course descriptions of the new graduate curriculum for Master of Science in Data Science & Analytics, please see Part C. It is to be mentioned here that whilst all reasonable attempts are made to ensure the accuracy of the syllabus pages that follow Part C, the Department reserves the right to make changes without notice.

  • Conclusion

The current MS program focuses on basic and advanced statistical theory and their applications in less computational fields. The new curriculum with a new name will add collection, management and analysis of big data, and automation alongside with most of the current courses. We, therefore, propose that the name of our presently existing program of MS in Applied Statistics be changed to MS in Data Science & Analytics. It should be mentioned here that problems of national importance in data analysis will receive great emphasis in the activities of this program.


Part A
_________________________________________________

 

Title of the Academic Program
Master of Science in Data Science & Analytics (M. S. in Data Science & Analytics)

Name of the University
East West University

Vision of the University
East West University was established with interrelated objectives of augmenting national capacity for tertiary education to a larger number of students, and thereby contributing to the country’s human capital development process.

Our university is dedicated to providing its graduates with the knowledge, abilities, and critical thinking needed to capitalize on new opportunities both domestically and internationally. By giving students from economically disadvantaged sections of society access to affordable university-level education, and by attempting to harness the power of individuals through higher education, by enhancing employable skills and enhancing access to job opportunities, higher education seeks to contribute to a more equitable and balanced society.The mission of our university is to advance human welfare by fostering a knowledge-based society and informed citizens who respect and uphold the ideals of democracy and pluralism. Its vision is to be a world-class learning center that combines excellence in education with strong human values and social responsibility. Its primary focus is on improving the quality of life for its students.

Mission of the University

  1. To become a center of excellence for higher education, making quality postsecondary education accessible to a larger section of the community at an affordable cost, leading to wide dissemination of educational opportunities, advancement of knowledge creation and promotion of economic, social, and technological progress.
  2. To excel in critical disciplines that addresses socio-economic challenges nationally and globally, and advance creative pursuits necessary for innovative solutions to societalissues.
  3. To provide a stimulating learning environment in which the faculty and students can discover, critically examine, preserve, and transmit knowledge, values, and wisdom to benefit society and improve the quality of lifeforall.
  4. To ensure that its students receive the highest quality of education, preparing them for a purposeful life, personally, professionally,andsocially.


Name of the Program Offering Entity
Department of Mathematical and Physical Sciences (MPS)

Vision Statement of Department of Mathematical and Physical Sciences
The Department of Mathematical and Physical Sciences is a department of the Faculty of Sciences and Engineering. Most important and essential subjects of any field of sciences are Mathematics, Statistics, Physics and Chemistry; and this department offers all these courses for the students of sciences and engineering.

The vision of the department is to produce highly competent Mathematician, Statistician, Physicist and Chemist who will address both national and global challenges for the sustainable development of the society by applying professional skills in any development work or excellent teaching performance or extraordinary research work in their respective areas.

Mission Statement (M) of the Department of Mathematical and Physical Sciences 

M1

To utilize advance knowledge in Mathematics and Mathematical Sciences through quality education and research towards the development of the society.

M2

To motivate research in mathematical and physical sciences by facilitating and promoting the scholarly activities.

M3

To prepare students by giving adequate knowledge and developing attitude so that graduates are in high demand in various sectors both nationally and internationally.

Objectives of the Department of Mathematical and Physical Sciences

  1. To ensure quality in teaching-learning environment by practicing Outcome-BasedEducation (OBE).
  2. To create an effective research environment.
  3. To continually maintain qualified faculty members, standard laboratory facilities and other supportiveobjects/materials.
  4. To update the program curriculum periodically to meet the requirements of national and international academic and non-academicemployers.

Name of the Degree
Master of Science in Data Science & Analytics (M. S. in Data Science & Analytics)

Description of the Program
The M.S. in Data Science & Analytics is a degree program under the department of MPS. This department started its activities in 2017 to teach/offer courses in Mathematics, Statistics, Physics and Chemistry. This program is designed carefully to meet the growing demand for applied statisticians and data science in Bangladesh and worldwide. The program will prepare graduates for the statistics, data scientist or analyst profession, which involves the application of mathematical, statistical, and computing techniques to the scientific fields in government and private sectors. After successful completion of the courses in data science and analytics each student will receive an MS certificate and a grade report.

Program Educational Objectives (PEOs) of M. S. in Data Science & Analytics
Graduates of the M. S. in Data Science & Analytics are expected to attain the following Program Educational Objectives (PEO) within a few years of graduation.

PEO-1: Establish themselves as ethical statistician, data analyst, researcher, or data scientists in both academic and non-academic sectors through rigorous understanding, critical thinking, and practical experience.

PEO-2: Carryout research and experiments in dynamic fields and help the industries and other sectors to fulfill their demands in data management and solve complex problems using expertise in a variety of data niches.

PEO-3: Pursue further higher education in this field and contribute in addressing both local and global causes and challenges.

Program Learning Outcome (PLO)
Graduates in Data Science & Analytics will be able to:

PLO1-Observation Power: Evaluate the details in a real-life data-based problem and its different aspects to choose the appropriate approach to deal or solve the problem.

PLO2-Data Management: Collect and manage data, whether small or big, and prepare them for analyses.

PLO3-Data Visualization: Use data visualization techniques to get a better insight to the data and communicate the data features effectively.

PLO4-Valid Inference: Make valid and efficient inference from both quantitative and qualitative data using probabilistic statistical tools.

PLO5-Modelling: Apply quantitative modeling techniques to model real-life events, phenomenon, and systems, and justify their effectiveness and use them for forecast and predictions.

PLO6-Computing: Use modern computing tools and facilities, and improvise one where needed, to manage and analyze data effectively.

PLO7-Research: Apply data analysis tools in dynamic experimental studies and research fields, e.g., IT, health and medical sciences, business and economics, agriculture and environment, and administration etc. to create new knowledge and solve world issues.

PLO8-Ethics: Demonstrate ethical practices in everyday activities and make well-reasoned ethical judgment for data management decisions.

PLO9-Further Learning: Recognize excellence in work and engage in life-long learning with the advancement of the world and ever-changing challenges. 

Mapping of Program Educational Objectives (PEOs) with Mission of the University

PEOs
Mission 1
Mission 2
Mission 3
Mission 4
PEO1


PEO2


PEO3



 

Mapping of Program Learning Outcomes (PLOs) with Program Educational Objectives (PEOs)

PLOs
PEO1
PEO2
PEO3
PLO1
 
 
PLO2
 
 
PLO3
 
 
PLO4
 
 
PLO5
 
 
PLO6
 
 
PLO7
 
PLO8
 
 
PLO9
 
 

Mapping of Core Courses with Program Learning Outcomes (PLOs) 

Code
Course
PLO1
PLO2
PLO3
PLO4
PLO5
PLO6
PLO7
PLO8
PLO9
DSA5001
Statistical Methods & Probability





DSA5002
Programming for Data Science





DSA5003
Database Management Systems






DSA5004
Regression Analysis




DSA5005
Multivariate Statistical Analysis






DSA5006
Machine Learning





DSA5007
Big Data & Cloud Computing


DSA5011
AI & Deep Learning





DSA5021
Time Series Analysis & Forecasting






DSA5041
Applied Econometrics





DSA5043
Business Process Analytics






DSA5045
Machine Learning for Finance






DSA5047
Data Analytics for Finance





DSA5061
Environmental Data Analysis and Climate Change




DSA5063
Bioinformatics






DSA5065
Biostatistics & Epidemiology




DSA 5071
Generalized Linear Models






DSA 5073
Categorical Data Analysis





DSA 5075
Design of Experiment






DSA 5077
Actuarial Data Analysis






DSA5099
Research Project

  

Part B
_________________________________________________

 

Structure of the Curriculum 

Duration of the Program
Years: 1.5 years
Semesters: 3

Admission Requirements
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.

Total Minimum Credit Requirement to Complete Program
40 Credits

Minimum CGPA Requirements for Graduation
2.50

Maximum Academic Years of Completion:
5 years