BSc Data Science Syllabus, Subjects, Semester, Teaching Process

BSc Data Science Syllabus covers a vast array of topics and concepts related to data science. Get first-hand information about this course and subjects in this article.

BSc Data Science Syllabus: The students who want to build a career in data science can take up the BSc Data Science course. It is a 3-year course that develops their understanding of various processes and concepts involved in data science. In this article, we will take a look at the BSc Data Science syllabus and subjects in detail.

The students will learn subjects like Basic statistics, C programming, introduction to statistics, linear algebra, introduction to analytics, inferential statistics, etc. during their coursework. More about the BSc Data Science syllabus has been shared in the below sections.

Table of Contents

BSc Data Science Course, An Overview

An overview of the BSc Data Science course has been given in the below table:

BSc Data Science Course, An Overview
Particulars	Details
Name of the course	BSc Data Science
Duration	3 years
Process of admission	Entrance-Based
Entrance tests	AMET CET, SSU CET, and other CET taken by respective colleges or universities
Eligibility Criteria	Class XII (Science)
Best Colleges	Symbiosis, Navrachana University, IIT Madras, AMET i.e., Academy of Maritime Education and Training
Average course fees	Rs. 6,00,000

BSc Data Science Syllabus

The semester-wise BSc Data Science syllabus has been given below:

BSc Data Science Syllabus
Semester 1	Semester 2	Semester 3
Linear Algebra Communication Skills in English Fundamentals of Data Science Basic Statistics Programming in C Python Programming	Image Analytics Machine Learning Probability and Inferential Statistics Introduction to Geospatial Technology Discrete Mathematics Advanced Python Programming for Spatial Analytics Computer Organization and Architecture Data Structures and Program Design in C	Genomics Natural Language Processing Research Proposal Microsoft Excel Lab Programming in C Lab
Semester 4	Semester 5	Semester 6
Programming in R Lab Exploratory Data Analysis Research Publication Data Structure Lab Data Warehousing	Introduction to AI (Artificial Intelligence) Programming in Python Lab Data Visualizations Big Data Analytics Machine Learning II	Electives 1 and 2 Viva Project Work

BSc Data Science Subjects

The following subjects are covered during the course:

First Year Subjects

The subjects for the first year are mentioned below:

BSc Data Science Subjects, First Year Subjects
Subjects	Description
Linear Algebra	Determinants, linear equations, linear transformations, and other topics related to mathematical structures are covered in this subject.
Probability and Inferential Statistics	The probability of a particular event or outcome determines the inferential statistics. Inferential statistics allows us to draw generalizations from a sample.
Basic Statistics	Median, mode, mean, and other central tendencies and dispersion measures are covered in this subject.
Data Structures and Program Design in C	Data structures like stack, linked list, trees, array, and more are covered in this subject.
Computer Organization and Architecture	The internal organization and working of a computer system are explained in this subject.

Second Year Subjects

The following subjects are included in the BSc Data Science syllabus of 2nd year:

BSc Data Science Subjects, Second Year Subjects
Subjects	Description
Data Warehousing and Multidimensional Modeling	The students learn how to represent data with data cubes in this subject.
NLP (Natural Language Processing)	The ways in which computers analyze the language and draw meaningful insights from them are discussed in this subject.
Genomics	Genetic information of a living organism along with its structure and functions are covered in this subject.

Third Year Subjects

The third-year syllabus includes these subjects:

BSc Data Science Subjects, Third Year Subjects
Subjects	Description
Programming in Python Lab	The fundamentals of Python Programming and its role in data science are explained in this subject.
Data Visualizations	The ways of presenting data in the form of visuals by using charts, graphs, and diagrams are discussed in this subject.
Big Data Analytics	The various procedures of extracting trends and patterns from huge datasets are covered in this subject.
Machine Learning II	The ways in which computers learn to retrieve meanings from data are discussed in this subject.

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BSc Data Science Syllabus of IIT Madras

The BSc Data Science syllabus might vary slightly as per the university or college in which the students get admission. The data science syllabus of IIT Madras has been given below:

BSc Data Science Syllabus of IIT Madras
Semester I	Semester II	Semester III
Statistics I Math I English I Computational Thinking	Statistics I Math I English I Programming in Python	Modern Application Development 1 Business Data Management Database Management Systems Machine Learning Foundation Skill Enhancement 1 Programming, Data Structures and Algorithms Using Python
Semester IV	Semester V	Semester VI
Skill Enhancement 2 Business Analytics Programming Concepts Using Java Machine Learning Practice Machine Learning Techniques Modern Application Development 2	Skill Enhancement Courses Strategies for Professional Growth Core Courses Elective courses	Skill Enhancement Courses Core Courses Elective Courses

BSc Data Science Syllabus of Mumbai University

The BSc Data Science syllabus of Mumbai University is given below:

BSc Data Science Syllabus of Mumbai University
Semester I	Semester II	Semester III
Introduction to Programming Descriptive Statistics Precalculus Descriptive Statistics Precalculus Tutorials Introduction to Programming Practical Web Technology Web Technology Practical Project Business Communication and Information Ethics ICT Practical	Calculus Environmental Science Presentation on Data Science in Environmental Science Probability and Distributions Practical Probability and Distributions Practical R Programming Database Management	Case Studies on Microeconomics Testing of Hypothesis SPSS Practical Tutorials On Linear Algebra and Discrete Mathematics Data Warehousing Linear Algebra and Discrete Mathematics Microeconomics/Principles Of Management
Semester IV	Semester V	Semester VI
Data Structures Data Structures Practical E-Commerce and Business Ethics/Fundamentals of Accounting MATLAB Practical Algorithms In Data Science Algorithms In Data Science Practical Big Data Optimization Techniques Practical Optimization Techniques Numerical Methods Numerical Methods Practical	Artificial Intelligence Artificial Intelligence Practical Business Research Methods Business Research Methods Practical Data Visualisation with Power BI/Tableau Data Mining Data Mining Practical Campus to Corporate Project Dissertation Electives	Business Forecasting Business Forecasting Practical Cloud Computing Cloud Computing Practical Internet of Things Internet of Things Practical Machine Learning Machine Learning Practical Electives Project Implementation

BSc Data Science Syllabus of Andhra University

The semester-wise BSc Data Science Syllabus of Andhra University has been given below:

BSc Data Science Syllabus of Andhra University
Semester I	Semester II	Semester III	Semester IV
Math for Data Science Math for Data Science Tutorial	Introduction to Data Science with R R Programming Lab	Big Data Technology Big Data Technology through Hadoop Lab	Data Mining and Data Analysis Big Data Acquisition and Analysis Big Data Acquisition and Analysis Lab

BSc Data Science Syllabus of Osmania University

The semester-wise BSc Data Science Syllabus of Osmania University has been given below:

BSc Data Science Syllabus of Osmania University
Semester I	Semester II	Semester III
Fundamentals of Information Technology Fundamentals of Information Technology (Lab)	Problem solving and Python Programming Problem solving and Python Programming (Lab)	University Specified Subjects Mini Project Data Engineering with Python Data Engineering with Python (Lab)
Semester IV	Semester V	Semester VI
Machine Learning (Lab) Machine Learning Mini Project University Specified Subjects	Data Structures and Algorithms No SQL Databases Lab Natural Language Processing Lab No SQL Databases Natural Language Processing	Deep Learning Big Data Deep Learning Lab Big Data Lab Project (Major)

BSc Data Science Syllabus, Teaching Process

The BSc Data Science syllabus includes theoretical and practical subjects. So, the syllabus is covered through different teaching methods. These methods include lectures and practicals along with group discussions, seminars, and research papers. The students also get internships after completing their coursework. It enhances their practical experience and knowledge.

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BSc Data Science Syllabus, Main Books

The books that the students can refer to cover the BSc Data Science syllabus have been mentioned in the below table:

BSc Data Science Syllabus, Main Books
Book Name	Author Name	Details
R for Data Science	Garret Grolemund and Hadley Wickham	This book teaches how to conduct data science processes by using R.
Understanding Machine Learning: From Theory to Algorithms	Shai Ben David and Shai Shalev-Shwartz	The fundamental ideas of machine learning and related mathematical derivations are covered in this book.
Python Data Science Handbook	Jake VanderPlus	The fundamentals of Python and their application in data science are explained in this book.
Python For Data Analysis	Wes McKinney	The data science tools that Python offers are explained by the author through this book.

These were some of the key parts and components of the BSc Data Science syllabus. It is not mandatory to complete this course for pursuing a career in the data science field. The students can also increase their data analytical and programming skills by undertaking various data science certifications and online courses.

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BSc Data Science Syllabus (FAQs)

What is BSc. Data Science Course?

BSc. Data Science is a 3-year degree course that covers the vast principles and subjects associated with data science. It is meant for the students who are interested to pursue a career in data science.

Is BSc data science hard?

The students who do not have sufficient foundation in statistics, computer programming, and mathematics can find it difficult.

Is coding taught in BSc Data Science?

Yes, the BSc Data Science syllabus includes coding in C, Python, R, and other programming languages. So, the students will learn a fair bit of coding during their coursework. Yet, the primary focus of the syllabus is to teach various concepts and processes of data science.

Is BCA Data Science better than BSc Data Science?

BCA Data Science is more focussed on the computer applications used in the field of data science. BSc Data Science will give the students an idea of the core concepts of data science. So, both the courses are beneficial, and students must choose them as per their preferences.

Which course is better: BSc Data Science or B. Tech Data Science?

The syllabus and core subjects of both these courses are similar. However, B. Tech Data Science is a 4-year course and much more recognized by top IT companies. So, the students will get more industry-relevant exposure and opportunities by completing this course.

What are the benefits of BSc Data Science?

The vast BSc Data Science syllabus helps the students to grasp concepts related to data engineering, database administration, data analytics, and more. It makes them acquainted with data mining, processing, data visualisation, and data analysis tasks which are in demand in healthcare, e-commerce, IT, and many other business verticals.

Is C++ required for data science?

C++ programming is related to data structures and functions. So, learning it will help the students while handling complex computations in data science.

Which language is the best for data science?

Python and R are the two most used programming languages in data science. So, learning these languages can help the students in enhancing their skills in handling various data science tasks.

Does BSc Data Science guarantee a bright future?

Various entry-level positions as a data analyst or researcher may be available after completing the BSc Data Science course. However, the students must complete data science certifications from renowned institutes to improve their portfolio.

Who is eligible for a data science course?

The students who have completed their 12th class in the Science stream are eligible for the data science course. However, they must also possess sufficient knowledge about computers and must acquire the fundamentals of math, statistics, and computer science before applying.

Which course is the best: BSc Data Science or BSc Computer Science?

BSc Computer Science is for the students who want to pursue a career in the field of software development or testing. Those who want to pursue a career in the field of data analytics should go for the BSc Data Science course.

How much coding is required in data science?

One can survive in the field of data science with the beginner-level programming knowledge in either Python or R. The students must also possess some knowledge about database management languages like SQL to excel in this field.