Bachelor of Data Science (BDSc)

The Department of Mathematics has introduced a new program “Bachelor of Data Science (BDSc)” commencement from August, 2024. This program integrates research activities, discussions, lectures, and teaching at various levels. The entire course is highly participatory and practice-oriented. The didactics of core courses and workshops are designed in a highly participatory and practice-oriented manner. The interactive learning environment combines theory and practice through modern didactics.

The department is renowned for its dedicated and strong academic faculty, who possess diverse academic backgrounds and actively participate in a variety of research endeavours. The faculty consists of highly experienced, renowned and educated from around the world, representing diverse perspectives from academia, industry and evaluation practice.

Data Science is a rapidly growing and versatile interdisciplinary field. This course aims to familiarize students with the various components of a comprehensive Data Science project and the process of developing, implementing, and evaluating it. After completing this course, students will be prepared to begin the process of comprehensive Data Science. The course objective is to help students understand the significance of Data Science.

Program Features

  • Four years program compatible with international standards.
  • Emphasize on Statistics, Mathematics, Computer Science and Business Intelligence.
  • The emphasis of the program will be primarily on statistical methods, machine learning, data analysis, and professional development.
  • Students are exposed to wide range of problems in Science, Engineering, Business, Technology and Industries.

Objective of the Course

  • To produce future Data Scientists proficient in utilizing statistics, advanced analytics, and machine learning across various disciplines with the expertise needed to tackle intricate real-world issues and tasks.
  • To integrate fields within computer science, optimization, and statistics, creating proficient and well-rounded data scientists.
  • To offer practical and computer-based professional training to explore, organize, and analyze large data sets from various sources, thereby enabling optimal decision-making and process optimization.

Career Opportunities

  • IT and Software Industries
  • Healthcare Industries
  • Oil and Gas Industries
  • Business Houses
  • Governmental Organizations and Ministries
  • Financial Institutions
  • Academic Industries and Research Centers

Financial Aid and Scholarship

  • Merit-based full tuition fee waiver scholarships
  • Need and merit-based partial tuition fee waiver scholarships
  • Loan scholarship

Course Structure

This program will emphasize on Statistics, Mathematics, Computer Science and Business with the following course structure.

 

DETAILS OF THE COURSE STRUCTURE

Year

Semester

Course Plan of Bachelor of Data Science (BDSc) (2024 onwards)

Total Credits

I

I

DSMA 111

 

DSMA 113

DSMA 114

DSMA 115

DSMA 116

15

II

DSMA 121

DSMA 122

DSMA 123

DSMA 125

DSMA 126

DSMA 199

18

II

I

DSMA 211

DSMA 212

 

DSMA 214

DSMA 215

DSMA 216

15

II

DSMA 221

DSMA 222

DSMA 224

DSMA 225

DSMA 226

DSMA 299

18

III

I

DSMA 311

 

DSMA 313

DSMA 314

DSMA 315

DSMA 316

15

II

DSMA 321

DSMA 322

DSMA 323

DSMA 324

DSMA 325

DSMA 399

18

IV

I

DSMA 411

DSMA 412

DSMA 413

Elective I

Elective II

 

15

II

DSMA 498/ DSMA 499

06

Total

120

 

 Elective courses

DSMA 451 (Biomathematics), DSMA 452 (Health Informatics), DSMA 453 (Econometrics), DSMA 454 (Numerical Methods in ODE), DSMA 455 (Data Mining), DSMA 456 (Bioinformatics), DSMA 457 (Stochastic Models), DSMA 458 (Mathematical Modeling), DSMA 459 (Statistical Modeling), DSMA 460 Biostatistics, DSMA 461 (Industrial Statistics), DSMA 462 (Agricultural Statistics), DSMA 463 (Population Dynamics), DSMA 464 (Financial modelling)

 

Contact Information

Department of Mathematics, School of Science, KU

Contact No.: 9801670053, 9701002602

Email ID: math_hod@ku.edu.np

Website: math.ku.edu.np

 



Documents

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