PG DIPLOMA IN DATA SCIENCE
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Highest Salary package:
Take the first step to become a data scientist!
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100% Placement Assistance with leading organisation on successful completion of the course
Master Data Management and Visualization, statistics, Machine Learning, Neural networks, AI, Deep Learning, Big Data technology, Unstructured data analysis
Receive 40 credits, recognized by Global Universities for Higher Education
Domain Specific electives on Marketing and Banking
Analytics, Unstructured Data
Analysis, Robotic Process
Automation and Linear Programming
Industry-relevant course curriculum, with applications in multiple domains taught by highly experienced Subject Matter Experts (SMEs) from academia, IT & Data Science industry
Loans available from
Avanse and TachyLoans
PLACEMENT STATS (2017-2018)
Get up to 143% hike in salary after this course
and many more…
WHO SHOULD ATTEND
Engineering or Non-Engineering aspirants wanting to become a Data Scientist
Any professional from Business Analytics/ Business Intelligence background
Managers from Analytics background and those who are leading a team of Analysts
Any Data Analyst or Software Developer aspiring to be a Data Scientist
Professionals wanting to build machine learning models, using distributed storage and distributed processing
Fresher and professionals with minimum 2 years work experience 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 qualify 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.
Batch Start Date
Batches start on 24th September 2018
i. Online Application can be purchased by paying Rs. 1000
PROGRAMMING FOR DATA SCIENCE (USING R AND PYTHON)
EXPLORATORY DATA ANALYSIS
DATA SCRAPPING AND WRANGLING
STATISTICAL TECHNIQUES FOR DATA SCIENCE
ELECTIVE 1: PRINCIPLES OF MARKETING or FINANCE
BIG DATA TECHNOLOGIES
ADVANCED BIG DATA TECHNOLOGIES
TRANSITION TO CORPORATE-BEHAVIOURAL DEVELOPMENT PROGRAM
ELECTIVE 2: BANKING or MARKETING ANALYTICS
ELECTIVE 3: UNSTRUCTURED DATA ANALYSIS/ LINEAR PROGRAMMING AND OPTIMIZATION/ ROBOTIC PROCESS AUTOMATION
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
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.
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.
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.
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 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 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.
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.
Limited Batch Size
Limited Batch Size for Quality Interaction during lectures
Instructor led classroom sessions on weekdays complimented by seamless
assignments & case studies during after class hours
Choose your elective based on domain/industry interest - Banking / Marketing Analytics, Unstructured Data Analysis, Robotic Process Automation and Linear Programming.
Preparatory Courses on “Java Programming” and “Advanced Excel”
Perform data analysis, modelling, predictive analysis, and story-telling through data visualization which is crucial to business decision-making.
Understand and use Big Data technologies as enablers to deploy enterprise information management and solve business problems.
Apply the methods, tools and techniques to real-world problems by leveraging technologies such as Python, R, Excel, SQL, NoSQL, Tableau, Hadoop, Pig, Hive, Apache Spark and Storm, and other open source and proprietary products as well.
Communicate analytics problems, methods, and findings effectively orally, visually, and in writing.
Help learners make critical decisions through analysis, modelling, visualization to make informed business decisions.
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.”
“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.”
“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.”
“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.”
“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.”