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PG Diploma in Data Science (Full-time)

11 month program, with 9-month residential training, followed by 2-month internship (non-residential)


Hands-on learning on R, Excel, Tableau, Hadoop, Pig, Hive, Apache, Spark, Storm, etc.

Ask us everything about the program!

Your Journey to become a successful Data Scientist begins today!

PG Diploma from Manipal Academy of Higher Education

By requesting info you agree to be contacted by Manipal ProLearn

COURSE HIGHLIGHTS

100% Placement Assistance with leading organisation on successful completion of the course

Placement Assistance

Receive 40 credits, recognized by Global Universities for Higher Education

Global Recognition 

Industry-relevant course curriculum, with applications in multiple domains taught by highly experienced Subject Matter Experts (SMEs)  from academia, IT & Data Science industry

Comprehensive Curriculum

Launch your career in data science by mastering Data Management & Visualization, Statistics, Machine Learning and Big Data

Become a Data Scientist

Industry Electives in different domains like Banking Analytics / Marketing Analytics

Choice of Electives

Loans available from Bank of Baroda, Axis Bank and Avanse Financial Services

Loan Available 

PLACEMENT STATS (2017-2018)

Get up to 143% hike in salary after this course

Highest Salary 

(Full-Time)

Average Salary

OUR RECRUITERS

* List is partial.

WHO SHOULD ATTEND

Engineering or Non-Engineering aspirants wanting to become a Data Scientist

Any Data Analyst or Software Developer aspiring to be a Data Scientist


Managers from Analytical background and those who are leading a team of Analysts

Any professional from Business Analytics/ Business Intelligence background

Professionals wanting to build machine learning models, using distributed storage and distributed processing


TESTIMONIALS

Hear it directly from the learners on what they have to say about our program

“I am working as Technical Program Manager for 

PayPal Credit. PGDDS course from Manipal Global 

Academy is not only helping me to understand how 

credits to merchants and consumers are getting 

rejected/approved but also the algorithm behind them.”



Vijayalakshmi Kapoor


“Manipal helped us change our career paths by bringing so many companies for campus recruitment. This course has given us a wide variety subject exposure which will definitely help each one of us in our career.”


Meghashree Shridhar


“This course has given us the platform to start a career in Data Science/Machine Learning. It has given me a baseline where to start with.”


Sushanth Raj


Rohit Singh


“The program is designed with keeping in mind interest of both freshers and working professional. The right balance of theory, practical and hackathons makes the students industry ready.” 


“I thank myself that I chose this program. Well balanced theory and applications, highly skilled faculties and a diverse set of students are what I appreciate most.”


Anurag Sindhu


“A nitro boost, would be an apt rendition for what this PGD in Data Science Program has been to my career skill sets, be it Analytical or presentation or extracting patterns/insights, consequently acting as a springboard for my career prospects.” 


Vishu Kasivelu


ELIGIBILITY CRITERIA

Freshers without prior experience and Working professionals on a sabbatical from their work can join the program.

Applicants should have the following minimum Academic qualifications:


1. B.E/B.Tech/BCA/B-Pharm graduates and/or ME/M.Tech/MCA/M-Pharm or Science Graduates (BSc. & MSc.) in Maths/Stats/Operations Research/ Physics/Economics/Computer Science/Information Technology or Commerce Graduates in Maths/Stats/Economics/Computer Science/ Information Technology. 


2. Min 50% marks or equivalent in the qualifying examinations.


Applicants will be required to attempt and pass the Online Pre-Admission Test with sections on verbal, quantitative and analytical test.

If admitted, you will be required to attend classes (face to face) in  Bangalore during weekdays (Monday - Friday) and select Saturdays. 

Course fee

7,43,400    

BATCH SCHEDULE

Mode

Batch Start Date

Timings

Full-Time

Batches start on 24th September 2018

Weekdays

Application 

Process

  i. Online Application can be purchased by paying Rs. 2000

(GST included)

MANIPAL ADVANTAGE

Supplementary Online Training Program provided – “Python with Data Science”

Limited Batch Size for Quality Interaction during lectures

Supplementary

Restricted Batch Size

Instructor led classroom sessions on weekdays complimented by seamless

assignments & case studies during after class hours

Learning Mode 

Choose your elective based on domain/industry interest - Banking / Marketing Analytics

Elective

Preparatory Courses on “Java Programming” and “Advanced Excel”

Preparatory Courses

LEARNING OUTCOMES

1

Perform data analysis, modelling, predictive analysis, and story-telling through data visualization which is crucial to business decision-making.

2

Understand and use Big Data technologies as enablers to deploy enterprise information management and solve business problems

3

Apply the methods, tools and techniques to real-world problems by leveraging technologies such as R, Excel, SQL, NoSQL, Tableau, Hadoop, Pig, Hive, Apache Spark and Storm, and other open source and proprietary products as well

4

5

Communicate analytics problems, methods, and findings effectively orally, visually, and in writing

Help Companies make critical decisions through analysis, modelling, visualization, etc.

TERM 01

PROGRAMMING FOR DATA SCIENCE

DATABASE MANAGEMENT SYSTEMS

STATISTICAL TECHNIQUES FOR DATA SCIENCE

EXPLORATORY DATA ANALYSIS

COURSE CURRICULUM

BIG DATA TECHNOLOGIES

DATA VISUALISATION

TERM 02

MACHINE LEARNING

ELECTIVE 1: PRINCIPLES OF FINANCE or MARKETING

TRANSITION TO CORPORATE-BEHAVIOURAL DEVELOPMENT PROGRAM

ADVANCED BIG DATA TECHNOLOGIES

TERM 03

ADVANCED MACHINE LEARNING

ELECTIVE 2: BANKING /MARKETING ANALYTICS

ELECTIVE 3: UNSTRUCTURED DATA ANALYSIS / LINEAR PROGRAMMING AND OPTIMISATION

INTERNSHIP/PROJECT WORK

Influence of international news headlines over stock trends: a sentiment analysis

The project is about analysing how the sentiments of non-quantifiable data, like International news articles about a company, influences the future stock trend.

Some of the Industry Projects completed by our students

Conversational Chatbots


The project is about building a conversational chat bot based on the dataset of the website information and queries raised by the customers.

Analysis of Stock Market Data and prediction of Stock Prices

Using the historical data of stocks, an analysis will be done using techniques like EDA and Data Visualization. Further, Machine Learning and Deep Learning will be used alongside Statistical methods like ARIMA. RShiny will be used to build a user friendly web application for the same. Unstructured Data Analysis will be used on Web Scrapping of Stock market news and economic news.

DonorsChoose.org Application Screening

To predict whether or not a DonorsChoose.org project proposal submitted by a teacher will be approved, using the text of project descriptions (Text analytics) as well as additional metadata about the project, teacher, and school. DonorsChoose.org can then use this information to identify projects most likely to need further review before approval.

Handwritten Digit Recognition


The objective of the project is to recognise and design an application system for Handwritten digits. The input to the system would be a pure digit’s image and output would be recognized digits.

Safe driver prediction using machine learning algorithms


Building a predictive model to predict the probability that a driver will initiate an auto insurance in future.

Data Mining Approach For Studying about Sales of different Products and Studying behaviour of different customers for predicting future sales.

Analyzing Past Shopping Records for getting insights about sales of different products, behaviour of different customers, finding Association Rules for different products and predicting forecast for sales of different products.

FACULTY

Dr Gangaboraiah

Dr Gangaboraiah has held several positions  at the Department of Community Medicine.As a Visiting Professor, he has taught Research Methodology and Statistics in various Educational institutions across the country. 


Mr Mallikarjuna Doddamane

Mr Mallikarjuna Doddamane has been in the education sector for 15 years across engineering and management areas. His is very passionate about Statistical Techniques and teaches the same at Manipal ProLearn.

Dr Ramesh Babu

Dr Ramesh Babu has two decades of professional experience in various positions in Technology, Management, Consulting and Leadership in the IT industry. His functional areas include driving enterprise-wide capacity and

capabilities programs.

Mr Mohan Kumar Silaparasetty

Mr Mohan Kumar Silaparasetty has been in the IT industry for more than 25 years. After graduating from IIT - Kharagpur, Mohan worked for SAP and IBM in a variety of leadership roles before embarking on his entrepreneurial journey. 

Mr Nagabhushan M

Mr Nagabhushan M has over 13 years of business experience, of which 7+ years were in the role of SME and educator. In the Big Data Ecosystem his focus areas include Hadoop, YARN, MapReduce, HDFS, HBase, Zookeeper, Hive, Pig, Sqoop, Cassandra, Oozie, Flume, Ambari, MAPR Hadoop, Hortonworks Hadoop and Cloudera Hadoop.

Mr Kathirmani Sukumar

Mr Kathirmani Sukumar has 8 years experience in data analytics. Kathirmani is specialized in data visualization , exploratory data analysis, and text analytics. He has also developed various data science applications using Python. He has worked with Gramener Technologies as a senior data scientist and then has now co-founded Quelit Innovations.

Mr R.N. Prasad

Mr R.N. Prasad is a Senior Analytics Consultant helping companies to design and implement innovative decision support and Corporate Performance Management (CPM) Systems. He is associated with Manipal Global Academy of IT and Data Science for over 3 years to design, develop and deliver education programs for big data, analytics, data architecture and product management areas.


Mr Raghavendra N.


Mr Raghavendra N. has 9 years of experience in Industrial IT(Oracle, Open Source) Competency Development &Technical Consulting and Assessment Operations with agile learning methodologies. He has sound knowledge and training experience in Data structures and Database programming, Oracle Database administration UNIX, Java, C, C++ and Hadoop fundamentals. 


Mr Amit Choudhary

Mr Amit Choudhary has 9 years 8 months of work experience in Manipal Global Education Service Pvt. Ltd. He has worked on various government projects like EGMM, UPSD, UDD etc where analytics was a part of project.

Mr Pankaj Rai

Mr Pankaj Rai is the Head of Strategic Planning at Wells Fargo’s GIC where he is responsible for creating a culture of 3Es (effectiveness, efficiency & experience) in the shared services operations spread out across India and Philippines. 

INDUSTRY MENTORS

Mr Renuka Prasad

Mr Renuka Prasad is the General Manager and Head of Recruitment For Analytics at WNS Global Services.

Dr Suman Katragadda

Mr Suman Katragadda is an analytics thought leader with deep expertise in healthcare payers and providers. He is one of the founding members of health care analytics practice at PwC, US that has consistently been ranked as No.1 for more than three years. 

Mr Sudhir S

Mr Sudhir S is currently working as a Principal Consultant at Fractal Analytics. His previous work experienceincludes eminent positions at Cognizant, Genpact and GE. His core areas of expertise include Business Analytics, Business Intelligence, Predictive modelling and analytics. 

Dr Venu Gopal Jarugumalli

Dr Venu is a seasoned analytics professional from an Economics background. He has spent over 12 years in analytics product development & implementation, client consulting and project delivery. Dr. Venu is a PhD from ISEC in International Business Strategy.

Mr Gaurav Sundararaman

Mr Gaurav works as a Senior Stats Analyst with ESPN. He’s been in the sports analytics domain for close to  6 years. He has previously worked with the Indian cricket team and with IPL franchises. Gaurav has presented a paper at MIT Sloan sports analytics 

conference at Boston.

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