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Corporate-Color
BACHELOR OF DATA SCIENCE

Program

STRUCTURE & CURRICULUM

program-structure-bds

The academic track of SP Jain’s BDS program is made of a blend of core, ethics and employability skills and industry-collaborated projects. Our curriculum is built on the principle that subjects get more and more specialised as you progress through the program.

Year 1

The subjects undertaken in the first year of the program build a strong, general foundation in data science, math and computer science.

Year 2

In Year 2, mathematical and analytical topics are explored in considerable depth, and students are taught subjects like Data Integration and Warehousing, Advanced Calculus, Algorithms and Data Structures, Programming for Analytics, Machine Learning and Advanced Linear Algebra and Applications.

Year 3

Advanced learning continues in Year 3 through topics like Simulation Modelling, Data Mining, Social Web Analytics, and Big Data Processing Techniques and Platforms.

CAPSTONE PROJECTS

A distinguishing feature of the program is the requirement to undertake, in the final year, applied analytics capstone projects that give students practical, hands-on experience in identifying and interpreting actionable information from raw data, and using them to make informed, mathematically valid decisions.

CAPSTONE PROJECTS
INTERNSHIPS

INTERNSHIPS

Although internships are voluntary, students are always encouraged to make good use of their summer break to gain real-time industry exposure. Internships present the opportunity to build a portfolio of international work experience, develop important professional attributes, put classroom learning to practice and transform yourself into a data specialist.

SEMESTER ONE

  • Mathematics for Data Scientists
  • Introduction to Statistics and Probability
  • Foundation Skills 1: Personal & Career Foundations
  • Introduction to Computer Programming
  • Introduction to Databases

SEMESTER TWO

  • Linear Algebra
  • Calculus
  • Foundation Skills 2: Ethics and Moral Reasoning
  • Introduction to Data Science
  • Statistical Data Analysis

SEMESTER THREE

  • Advanced Calculus
  • Algorithms and Data Structures
  • Employability and Practitioner Skills Series 1: Emotional Intelligence
  • Data Integration and Warehousing
  • Visual Analytics (or Explorative Data Analysis)

SEMESTER FOUR

  • Advanced Linear Algebra and Applications
  • Programming for Analytics
  • Employability and Practitioner Skills Series 2: Leadership, Teamwork, Global Dexterity
  • Consumer Behaviour and Marketing Research
  • Machine Learning

SEMESTER FIVE

  • Simulation Modelling
  • Data Mining
  • Employability and Practitioner Skills Series 3: Communicating Effectively
  • Object Relational and NoSQL Databases
  • Data Science Capstone Project I

SEMESTER SIX

  • Social Web Analytics (or Web, Internet of Things, and Social Media Mining)
  • Advanced Analytics (Stream, Sensor and Spatio-temporal Analysis)
  • Employability and Practitioner Skills Series 4: Innovation, Creativity and Agility
  • Big Data Processing Techniques and Platforms
  • Data Science Capstone Project II

PROGRAM ARCHITECTURE

To fulfil the requirements of the BDS program, students must complete a total of 78 credits.

Core Units

66

Credits

Foundation Skills & Employability Skills Units

6

Credits

Data Science Capstone Projects

6

Credits

TOTAL

78

CREDITS

ASSESSMENT METHODS

SP Jain uses a system of continuous student evaluation, rather than a single end-of-semester final examination. The assessment types for the BDS program include organisational case studies, simulation exercises, prototype development and exhibition, reflective assignment reports, programming and laboratory exercise, tutorial exercises, use of analytical software in the classroom, simulations, mid-term exams, final exams, business decision making reports, and industry projects and reports. To learn more about our assessment methods, please refer to the Student Handbook: