Topics

Program Overview
Degree Offerings
Admission Requirements
Curriculum Structures
Courses
Note

Post-Graduate Programs in Data Science


Program Overview:

Data science is a growing field that applies computational and statistical techniques to analyze, understand and derive insights from data. Presently, huge amounts of data are being generated from diverse domains such as business and finance, governance, the World Wide Web (WWW), social media, the Internet of Things (IoT), healthcare, bioinformatics, physical sciences, climate modeling. Data scientists use algorithms, machine learning, statistical and visualization methods to extract knowledge from the data through collaboration with domain experts and help make data-driven decisions. Jim Gray, a Turing award-winning computer scientist, described data science as the fourth paradigm of science, adding to empirical, theoretical and computational paradigms of science.

However, Bangladesh is yet to fully leverage the availability of vast amounts of data in decision-making in most sectors due to a lack of people trained in data science. This will also delay the 4th Industrial Revolution (4IR) in the country. Moreover, many of the SDG goals of Bangladesh such as SDG 3: Healthy Lives and Well-being, SDG 11: Sustainable Cities and Communities, etc. require extensive use of data-driven technologies.

To address the above needs, we propose two Master’s and a Ph.D. program in Data Science from the Department of Computer Science and Engineering (CSE) at Bangladesh University of Engineering and Technology (BUET).

Degree Offerings

  • 1. Master of Science in Data Science (M. Sc. Data Science)
    • Duration: 18 months
    • Course Structure: 18 Credit courses + 18 Credits Thesis
    • Mode: Thesis Based

  • 2. Master of Data Science (M. Data Science)
    • Duration: 2 years
    • Course Structure: 30 Credit courses + 6 Credits Project
    • Mode: Course Based

  • 3. Doctor of Philosophy (Ph.D.) in Data Science
    • Duration: 3-5 years
    • Total Credit: 54 Credits

Admission Requirements:

For Master’s Degrees

The admission requirements for the Master’s programs are as follows:

  • 1. 4-year B.Sc. in Computer Science and Engineering (CSE)/ Electrical and Electronic Engineering (EEE)/ Computer Science (CS)/ Computer Engineering (CE)/ Electrical and Computer Engineering (ECE)/ relevant fields, or 4-year Bachelor's degree in other engineering/ other mathematical science or natural science/ business information systems/ related field.

For Ph.D. Degree

The admission requirement for the Ph.D. program is as follows:

  • 1. Master’s degree in Computer Science and Engineering (CSE)/ Electrical and Electronic Engineering (EEE)/ Computer Science (CS)/ Computer Engineering (CE)/ Electrical and Computer Engineering (ECE)/ Data Science/ relevant fields, or Master in other engineering/other mathematical science or natural science/ business information systems/ related field.

Curriculum Structures:

1. For students satisfying Group A entry requirements:

Program Mode Courses Thesis/ Project Credit Total Credit
Total Number of Courses (Credit) Number of Foundation Courses Minimum Number of Core Courses
M. Sc. (Data Science) Thesis Based 6 Courses (18 Credit) 3 (Audit course) 4 18 Credit 36 Credit
M. Data Science Course Based 10 Courses (30 Credit) 3 (Audit course) 6 6 Credit 36 Credit
Ph.D. N/A 3 Courses (9 Credit) 3 (Audit course) 2 45 Credit 54 Credit

Courses:

Foundation Courses

  • 1. CSE 5501: Foundations of Data Science
  • 2. CSE 5502: Programming for Data Science
  • 3. CSE 5503: Artificial Intelligence and Machine Learning

Core Courses

  • 1. CSE 6413: Network Science
  • 2. CSE 6501: Advanced Artificial Intelligence
  • 3. CSE 6506: Data Mining
  • 4. CSE 6510: Natural Language Processing
  • 5. CSE 6512: Advanced Machine Learning
  • 6. CSE 6513: Business Intelligence
  • 7. CSE 6514: Big Data Analytics
  • 8. CSE 6515: Data Visualization
  • 9. CSE 6708: Semantic Web
  • 10. CSE 6709: Deep Learning

Note:

  • 1. Audit courses may be waived by BPGS depending on the background of a student upon application.
  • 2. The remaining required courses (i.e., courses other than the Foundation courses and Core courses) can be taken from any PG courses.
  • 3. The thesis/project must be on a topic relevant to the program area.

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