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Post Graduate in data science course provides training to develop Statistical, Computational and Programming Skills. The increasing importance of data analysis in several fields including banking, finance, entertainment, pharmaceutical, environment, economics, engineering and many more motivated us to curate a course for full time working professionals and new graduates to upskill and become eligible for lucrative job prospects.

The program aims at teaching students:

  • Theoretical and practical aspects of statistical concepts like inference, probability, Bayes Theorem, modeling
  • Programming skills like Python and R programming
  • Data visualization tools for real-world scenarios
  • Database management to clean, transform and query data.
  • Implementing machine learning algorithms to design solutions for data-oriented problems

Key highlights

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Gateway to foreign universities

Complete 16 years of education as required by most of the international institutions while getting an excellent foundation in the data science field.

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University of Mumbai

Globally recognised degree from the prestigious 160 years old University of Mumbai. Campus placed at renowned Patkar-Varde college having ‘A+ Grade’ by NAAC.

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Industry approved curriculum

The program has been designed and taught by eminent industry experts to bring education in sync with workplace realities ensuring holistic learning.

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Capstone Projects & Case Studies

Capstone projects drawn from real-world problems allow students to create a product that can be used to practice their skills and showcase to potential employers.

Programming softwares / tools covered

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R Studio Logo
Power BI Logo
Hadoop Logo
Google Analytics Logo

Training Methodology

“Knowledge has to be improved, challenged, and increased constantly, or it vanishes.”

Classroom Learning

Theory

In data science, mathematical skills are as important as programming skills. Subjects like Statistics, Linear algebra and Big data helps to build a profound fundamental to build reliable and efficient models

Practical

You need good programming and analytical skills to become a good data scientist which comes by practicing several tools required to solve big data problems, automate processes and write efficient algorithms.

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Application Based Learning

Application Based Learning For PG Diploma

Case studies

Companies are using analytics to improve their process and the scale of the data they use to do this has increased tremendously over the last few years making it extremely important to learn through real-world case studies.

Industry connects

Professionals from the industry share their experiences though such sessions and talk about how data science continues to gain widespread acclaim & demand across almost every major sector.

Eligibility Criteria

1

Graduate from any stream (Science/Commerce/Arts)

2

Must have a keen interest in Statistics, Programming and Data Analysis.

Course Syllabus

This semester introduces students to statistical analysis and several programming tools, data visualisation to transform and clean the data and database management to create, retrieve, update and manage data.

Paper title

  • Database Management Systems
  • Big Data architecture and ecosystem
  • Statistical Methods
  • Data Visualization – Using Power BI
  • R Programming
  • Python Programming
Semester I
Course Code Course Type Course Title Credits
PUSDSBA 101 Core Subject Database Management Systems 4
PUSDSBA 102 Core Subject Big Data architecture and ecosystem 4
PUSDSBA 103 core Subject Statistical Methods 4
PUSDSBA 104 Core Subject-Practical Data Visualization – Using Power BI 4
PUSDSBA 405 Core Subject R Programming 4
PUSDSBA 406 Core Subject Python Programming 4
Total Credits 24

This semester focuses on Time series forecasting and Machine Learning that automates analytical model building. Students learn to work on big data and advanced SQL to systematically extract information and draw insights.

Paper title

  • Machine Learning and Deep Learning
  • Time Series Analysis and Forecasting
  • NLP and Recommendation Engine
  • Distributed Processing using HADOOP
  • Electives
    • Social Media and Marketing Analytics
    • Financial Analytics
Semester II
Course Code Course Type Course Title Credits
PUSDSBA 201 Core Subject Machine Learning 4
PUSDSBA 202 Core Subject Time Series Analysis 4
PUSDSBA 203 core Subject Advance SQL 4
PUSDSBA 204 Core Subject NLP 4
PUSDSBA 205 Core Subject Project Work 4
PUSDSBA 206 Core Subject Elective 4
Total Credits 24

SDBI offers a Diploma course at Under Graduate level as well to learn data science as an additional skillset.

UG Diploma is a one-year program offered for the students already pursuing their graduation in any field and wants to learn programming software’s, data visualisation and ML techniques. These lectures will be conducted over the weekend and will not clash with their regular college hours. To know more about the syllabus, fees, and key highlights of the program, download brochure. Contact us to know more.

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