Master of Science Data Science

Master of Science (Data Science)

This programme will equip students with data science knowledge highly relevant in intelligence era. This programme aims to provide a comprehensive framework for understanding data science life cycle, statistical foundations, technologies and applications.

Duration (in months) :- 24 (Online)

INTAKE :- 500

RESERVATION :- Not Applicable

Eligibility :- Graduate from any recognised University/ Institution of National Importance with a minimum of 50% marks or equivalent grade (45% marks or equivalent grade for Scheduled Caste / Scheduled Tribes).

SELECTION PROCEDURE :- Based on fulfillment of egilibity norms and submission of documents.

Medium of Instruction :- English.

Programme Pattern :- Semester

Course and Specialization :- As per Annexure A.

Fees	Academic Fee p.a	Institute Deposit	Total
Indian Students	INR 70,000	-	INR 70,000
International Students	INR 70,000	-	INR 70,000

Assessment :- All courses will have 30% internal component and 70%component as external [University] examination.

Standard of Passing :- The assessment of the student for each examination is done, based on relative performance. Maximum Grade Point (GP) is 10 corresponding to O (outstanding). For all courses, a student is required to pass both internal and external examination separately with a minimum Grade Point of 4 corresponding to Grade P. Students securing less than 40% absolute marks in each head of passing will be declared FAIL. The University awards a degree to the student who has achieved a minimum CGPA of 4 out of maximum of 10 CGPA for the programme.

Award of Degree/DIPLOMA CERTIFICATE :- Master of Science (Data Science) will be awarded at the end of semester IV examination by taking into consideration the performance of all semester examinations after obtaining minimum 4.00 CGPA out of 10 CGPA.

Classification of Credits :-

Semester	Generic Core	Generic Elective	Total
1	19	0	19
1	20	0	20
1	13	6	19
1	16	6	22
Total	68	12	80

Sample Degree Certificate :-

Annexure A :-

Course Title	Credit	Internal Marks	External Marks	Total Marks
Generic Core Courses
Statistical computing	4	30	70	100
Research Methodology	2	30	70	100
Data Analysis Using Python	2	30	70	100
NOSQL Databases	3	30	70	100
Data Warehousing	3	30	70	100
Data Management	3	30	70	100
Mathematics Foundations	2	30	70	100
Total	19	210	490	700

Course Title	Credit	Internal Marks	External Marks	Total Marks
Generic Core Courses
Multivariate statistics-1	3	30	70	100
Statistical Inference	4	30	70	100
Machine Learning Algorithms	4	30	70	100
Text Analytics	3	30	70	100
Operations Research and Optimization Techniques	2	30	70	100
Data protection and Privacy	2	30	70	100
Data Mining	2	30	70	100
Total	20	210	490	700

Course Title	Credit	Internal Marks	External Marks	Total Marks
Generic Core Courses
Multivariate statistical Analysis-2	4	30	70	100
Artificial Neural Network and Deep Learning	3	30	70	100
Data Analysis and Visualization	3	30	70	100
Big data analytics	3	30	70	100
Total	13	120	280	400
Generic Elective
Fuzzy Logic	3	30	70	100
Natural Language Processing	3	30	70	100
Cognitive computing	3	30	70	100
Total	6	90	210	300

Course Title	Credit	Internal Marks	External Marks	Total Marks
Generic Core Courses
Time Series Analysis	3	30	70	100
Data Analytics with Excel	1	20	30	50
Project	12	180	420	600
Total	16	275	525	800
Generic Core Courses
Reinforcement learning	3	30	70	100
Social media and web analytics	3	30	70	100
Computer vision	3	30	70	100
Analytics applications	3	30	70	100
Total	6	120	280	400

Semester	Internal Credits	External Credits	Total Credits	Total Marks
Semester 1	0	19	19	950
Semester 2	0	20	20	1000
Semester 3	0	19	19	950
Semester 4	1	21	22	1100
Total	1	79	80	4000

Programme Highlights

Master of Science (Data Science)

Symbiosis online Degree Programme equally credible as offline

100% Online Programmes- No campus visit required

Online assessments as per UGC Guidelines

24*7 Access to Learning Management System

Curriculum developed by experts from top 10 Symbiosis Institutes in India

Access to recorded sessions- learn at your own pace

Live Teacher - student lectures & interactions

Peer-to-peer doubt sharing & solving sessions

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