PGDM Data Science And Business Analytics Programme Structure

Programme Structure

The PGDM in Data Science and Business Analytics offers a comprehensive and industry-oriented curriculum designed to transform you into a data-driven decision-maker. Whether you’re a beginner, someone switching careers, or simply looking to upskill, this program is designed for everyone with no prior coding background required.

We aim to make you learn the power of data to solve real-world business problems, predict trends, and drive impactful decisions. This program breaks down complex concepts into easy-to-understand modules, teaching you everything from the basics of Python, R, and SQL to advanced topics like machine learning, predictive analytics, and data visualization.

Students will also learn how to apply these tools strategically, turning raw data into actionable insights that can transform businesses.

With targeted and assisted industry internships, students gain relevant work experience. The program emphasizes collaborative learning through group projects, hackathons, and case studies, allowing you to work on real business challenges alongside peers and industry experts.

PGDM Data Science And Business Analytics Year 1

In the first year, students establish a strong foundation in both business management and data science. Core business subjects are introduced such as Marketing Management, Financial Accounting, Organizational Behavior, and Business Economics to understand how companies operate. Simultaneously, they are introduced to data science concepts, including data analysis, statistics, and programming languages like Python and R, which are essential for data manipulation and visualization. This combination ensures that students grasp the fundamentals of business operations and the role of data in decision-making.

PGDM Data Science And Business Analytics Year 2

In the second year, the program goes into advanced analytics and specialized areas. Students explore machine learning, which involves teaching computers to learn from data and make predictions. They also study big data technologies like Apache Hadoop and Spark, which are used to handle large amounts of information. The curriculum offers elective courses, allowing students to specialize in areas such as Financial Analytics, Marketing Analytics, or Operations Analytics, based on their interests. Practical experience is a key component, with opportunities for internships and industry projects that enable students to apply their knowledge to real-world business challenges.

Programme Summary

TRIMESTER	TOTAL CREDITS	CEC	TERM-END	TOTAL MARKS
TRIMESTER-I	25	450	400	900
TRIMESTER-II	25	450	400	850
TRIMESTER-III	25	450	400	850
TRIMESTER-IV	25	450	400	850
TRIMESTER-V	22	400	300	700
TRIMESTER-VI	12	200	200	400
Summary	134	2400	2150	4550

TRIMESTER	TOTAL CREDITS	CEC	TERM-END	TOTAL MARKS
TRIMESTER-I	25	450	400	900
TRIMESTER-II	25	450	400	850
TRIMESTER-III	25	450	400	850
TRIMESTER-IV	25	450	400	850
TRIMESTER-V	22	400	300	700
TRIMESTER-VI	12	200	200	400
Summary	134	2400	2150	4550

Detailed Programme Breakdown

OBJECTIVE▼

Our two-year full-time PGDM in data science and business analytics seamlessly integrates learning modules with hands on training on top data science tools making you learn management via data efficiently.

AWARD OF DEGREE/ DIPLOMA/ CERTIFICATE▼

Programme degree will be awarded at the end of the trimester VI examination by taking into consideration the performance of all semester examinations after obtaining a minimum CGPA of 4 out of maximum of 10 CGPA.

SPECIALIZATION▼

Specializations include data mining, big data, data visualization, machine learning, and artificial intelligence.

FEE▼

9.85 Lakhs

INTAKE▼

ASSESSMENT▼

Each course will have a weightage of 100 marks wherein 50% will be of Continuous Evaluation Components & 50% will be of Term End Examination.

STANDARD OF PASSING▼

Maximum Grade Point (GP) is 10 corresponding to O (Outstanding). For all courses, a student is required to pass both Continuous Evaluation Components and Term End Examination separately with a minimum Grade Point of 4 corresponding to Grade PASS. Students securing less than 40% absolute marks in each head of passing will be declared FAIL.

MEDIUM OF INSTRUCTION

English

DURATION
(IN MONTHS)

24 (Full Time)

PROGRAMME PATTERN

Trimester

ELIGIBILITY

The candidate must hold a bachelor’s degree or equivalent examinations in any discipline with at least 60% marks or an equivalent CGPA. The candidate must have appeared for any recognized Management Entrance Examination like CMAT, CAT, MAT, XAT etc and NBSAT (NBS Aptitude Test), a national-level management entrance exam devised by Narayana Business School, which accesses the candidate’s Mathematical Aptitude, General Knowledge, Verbal Ability & Abstract Reasoning.

SELECTION PROCEDURE

Students will be evaluated on the following parameters:

NBSAT Score (out of 100, scaled down to 40 marks)	40%
Academic Performance & Prior Work Experience	20%
Statement of Purpose (SOP)	20%
Personal Interview	20%
Total	100%

PGDM Data Science & Analytics Course Curriculum Details

COURSE CODE	COURSE NAME	CREDIT	CEC	TERM END	TOTAL
TRIMESTER 1 - CORE COURSES
1PGDMDSA01	Fundamentals of Programming Using Python	3	50	50	100
1PGDMDSA02	Statistics for Data Science - I	3	50	50	100
1PGDMDSA03	Data Visualization Techniques - I	3	50	50	100
1PGDMDSA04	Relational Database Management Systems	3	50	50	100
1PGDMDSA05	Effective Business Communication	3	50	50	100
1PGDMDSA06	Perspective Management	3	50	50	100
1PGDMDSA07	Managerial Economic	3	50	50	100
1PGDMDSA08	Foundations of Data Science	2	50	50	100
1PGDMDSA09	Shell Scripting for Beginners	2	50	**	50
	TOTAL CREDITS	25	TERM-END	TOTAL MARKS	850

COURSE CODE	COURSE NAME	CREDIT	CEC	TERM END	TOTAL
TRIMESTER 2 - CORE COURSES
2PGDMDSA01	Big Data Analytics using Hadoop -I	3	50	50	100
2PGDMDSA02	Statistics for Data Science - II	3	50	50	100
2PGDMDSA03	Data Visualization Techniques using Python	3	50	50	100
2PGDMDSA04	Data warehousing	3	50	50	100
2PGDMDSA05	Data Mining Techniques	3	50	50	100
2PGDMDSA06	Marketing Principles and Applications	3	50	50	100
2PGDMDSA07	Human Resource Management	3	50	50	100
2PGDMDSA08	Financial reporting &Analytics	3	50	50	100
2PGDMDSA09	Personal Competence and capability Building -II	1	50	**	50
	TOTAL CREDITS	25	TERM-END	TOTAL MARKS	850

COURSE CODE	COURSE NAME	CREDIT	CEC	TERM END	TOTAL
TRIMESTER 3 - CORE COURSES
3PGDMDSA01	Big Data Analytics using Hadoop -II	3	50	50	100
3PGDMDSA02	Machine Learning using Python -1	3	50	50	100
3PGDMDSA03	Data Visualization Techniques Using Power BI	3	50	50	100
3PGDMDSA04	Big Data Analytics using Spark	3	50	50	100
3PGDMDSA05	Cloud Computing	3	50	50	100
3PGDMDSA06	Legal Aspects of IT Business	3	50	50	100
3PGDMDSA07	Corporate Finance	3	50	50	100
3PGDMDSA08	Research Methodology using R	3	50	50	100
3PGDMDSA09	Personal Competence and Capability Building -II	1	50	**	50
	TOTAL CREDITS	25		TOTAL MARKS	850

COURSE CODE	COURSE NAME	CREDIT	CEC	TERM END	TOTAL
TRIMESTER 4 - CORE COURSES
4PGDMDSA01	Corporate Interface through Summer Internship	6	50	50	200
4PGDMDSA02	Machine Learning Using Python -II	3	50	50	100
4PGDMDSA03	Data visualization Techniques using Tableau	3	50	50	100
4PGDMDSA04	NoSQL Databases	3	50	**	50
4PGDMDSA05	Neural Network Science	3	50	50	100
4PGDMDSA06	Operations Research	3	50	50	100
4PGDMDSA07	Entrepreneurship	2	50	50	100
4PGDMDSA08	Digital & Social Media Analytics	2	50	**	50
	TOTAL CREDITS	25	TERM-END	TOTAL MARKS	850

COURSE CODE	COURSE NAME	CREDIT	CEC	TERM END	TOTAL
TRIMESTER 5 - CORE COURSES
5PGDMDSA01	Strategic Management	6	50	50	100
5PGDMDSA02	Natural Language Processing & Text Mining	3	50	50	100
5PGDMDSA03	Advanced Neural Network Science	3	50	50	100
5PGDMDSA04	Ethics and Data Governance for Data Science	3	50	50	100
5PGDMDSA05	Project Management using JIRA	3	50	50	100
5PGDMDSA06	AI for Business	3	50	50	100
5PGDMDSA07	Personal Competence and capability Building -III	2	50	**	50
5PGDMDSA08	HACKATHON	2	50	**	50
	TOTAL CREDITS	25		TOTAL MARKS	700

COURSE CODE	COURSE NAME	CREDIT	CEC	TERM END	TOTAL
TRIMESTER 6 - CORE COURSES
6PGDMDSA01	Capstone Project	6	100	100	200
6PGDMDSA02	IPR	3	50	50	100
6PGDMDSA03	Internet of Things	3	50	50	100
	TOTAL CREDITS	12		TOTAL MARKS	400

TRIMESTER 1-

COURSE CODE	COURSE NAME	CREDIT	CEC	TERM END	TOTAL
TRIMESTER 1 - CORE COURSES
1PGDMDSA01	Fundamentals of Programming Using Python	3	50	50	100
1PGDMDSA02	Statistics for Data Science - I	3	50	50	100
1PGDMDSA03	Data Visualization Techniques - I	3	50	50	100
1PGDMDSA04	Relational Database Management Systems	3	50	50	100
1PGDMDSA05	Effective Business Communication	3	50	50	100
1PGDMDSA06	Perspective Management	3	50	50	100
1PGDMDSA07	Managerial Economic	3	50	50	100
1PGDMDSA08	Foundations of Data Science	2	50	50	100
1PGDMDSA09	Shell Scripting for Beginners	2	50	**	50
	TOTAL CREDITS	25	TERM-END	TOTAL MARKS	850

TRIMESTER 2+

COURSE CODE	COURSE NAME	CREDIT	CEC	TERM END	TOTAL
TRIMESTER 2 - CORE COURSES
2PGDMDSA01	Big Data Analytics using Hadoop -I	3	50	50	100
2PGDMDSA02	Statistics for Data Science - II	3	50	50	100
2PGDMDSA03	Data Visualization Techniques using Python	3	50	50	100
2PGDMDSA04	Data warehousing	3	50	50	100
2PGDMDSA05	Data Mining Techniques	3	50	50	100
2PGDMDSA06	Marketing Principles and Applications	3	50	50	100
2PGDMDSA07	Human Resource Management	3	50	50	100
2PGDMDSA08	Financial reporting &Analytics	3	50	50	100
2PGDMDSA09	Personal Competence and capability Building -II	1	50	**	50
	TOTAL CREDITS	26	TERM-END	TOTAL MARKS	850

TRIMESTER 3+

COURSE CODE	COURSE NAME	CREDIT	CEC	TERM END	TOTAL
TRIMESTER 3 - CORE COURSES
3PGDMDSA01	Big Data Analytics using Hadoop -II	3	50	50	100
3PGDMDSA02	Machine Learning using Python -1	3	50	50	100
3PGDMDSA03	Data Visualization Techniques Using Power BI	3	50	50	100
3PGDMDSA04	Big Data Analytics using Spark	3	50	50	100
3PGDMDSA05	Cloud Computing	3	50	50	100
3PGDMDSA06	Legal Aspects of IT Business	3	50	50	100
3PGDMDSA07	Corporate Finance	3	50	50	100
3PGDMDSA08	Research Methodology using R	3	50	50	100
3PGDMDSA09	Personal Competence and Capability Building -II	1	50	**	50
	TOTAL CREDITS	25		TOTAL MARKS	850

TRIMESTER 4+

COURSE CODE	COURSE NAME	CREDIT	CEC	TERM END	TOTAL
TRIMESTER 4 - CORE COURSES
4PGDMDSA01	Corporate Interface through Summer Internship	3	50	50	200
4PGDMDSA02	Machine Learning Using Python -II	3	50	50	100
4PGDMDSA03	Data visualization Techniques using Tableau	3	50	50	100
4PGDMDSA04	NoSQL Databases	2	50	**	50
4PGDMDSA05	Neural Network Science	3	50	50	100
4PGDMDSA06	Operations Research	3	50	50	100
4PGDMDSA07	Entrepreneurship	2	50	50	100
4PGDMDSA08	Digital & Social Media Analytics	2	50	**	50
	TOTAL CREDITS	25	TERM-END	TOTAL MARKS	850

TRIMESTER 5+

COURSE CODE	COURSE NAME	CREDIT	CEC	TERM END	TOTAL
TRIMESTER 5 - CORE COURSES
5PGDMDSA01	Strategic Management	3	50	50	100
5PGDMDSA02	Natural Language Processing & Text Mining	3	50	50	100
5PGDMDSA03	Advanced Neural Network Science	3	50	50	100
5PGDMDSA04	Ethics and Data Governance for Data Science	3	50	50	100
5PGDMDSA05	Project Management using JIRA	3	50	50	100
5PGDMDSA06	AI for Business	3	50	50	100
5PGDMDSA07	Personal Competence and capability Building -III	2	50	**	50
5PGDMDSA08	HACKATHON	2	50	**	50
	TOTAL CREDITS	25		TOTAL MARKS	700

TRIMESTER 6+

COURSE CODE	COURSE NAME	CREDIT	CEC	TERM END	TOTAL
TRIMESTER 6 - CORE COURSES
6PGDMDSA01	Capstone Project	6	100	100	200
6PGDMDSA02	IPR	3	50	50	100
6PGDMDSA03	Internet of Things	3	50	50	100
	TOTAL CREDITS	12		TOTAL MARKS	400

PGDM Data Science And Business Analytics Programme Structure

PGDM Data Science And Business Analytics Programme Structure

Programme Structure

Programme Summary

Detailed Programme Breakdown

PGDM Data Science & Analytics Course Curriculum Details

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