Eligibility
Working professional with at least two years of work experience, having mathematical, computer science or technical background.
Candidates with an MBA (or equivalent Management qualification) will be eligible based on their graduation streams.
Those earned 50% or above in (or is awaiting results of) one of the following - any of the Engineering Degrees (B.E., B.Tech., M.E. or M.Tech.); or BCA/MCA; or Bachelors or Masters in Maths, Physics, Statistics, Economics, or Operational Research.
Candidates from other streams (Chemistry, Biology, Commerce, Arts, Media, and BBA) who have scored 50% or above, will have to take an online Technical Aptitude assessment.
All candidates will have to undertake an English Proficiency test, irrespective of the graduation streams.
Course Outcome
Concepts of Data Science
Learn about Big Data and Machine Learning from the foundation to advanced level.
Program Structure
The first 3 terms have a mix of theory and labs while the last term is a project term. The last term will be a stipend-based internship or project of 2 months.
Big Data Technologies
Become an expert in Big Data Technologies, the most popular and growing technology in the world.
Better Career Path
Find job opportunities as Data Scientists, Data Analysts, Data Engineer, Data Developer etc.
Loans Available
Loans available from Axis Bank, Credila and Avanse Financial Services.
Soft Skills
Soft skills training is also imparted to help you to transition to corporate and accelerate career growth.
Curriculum
Introduction to Software and Operating Systems (OS)
Introduction to programming
Control Structures:
Functions and Algorithms
Complexity
File operations
Introduction to Database Management Systems
Conceptual Database Design
Logical Database Design
Database Design
Database Implementation
Introduction to Statistics
Probability
Sampling and Sampling Distributions
Testing of Hypothesis
Simple Correlation
Introduction to Data Science
Introduction to Data Analysis
Descriptive Analysis
Data cleansing and transformation
Statistical methods applications for dimension reduction
Statistical methods applications for clustering
Introduction to Machine Learning and Data Science
Regression
Classification
Clustering
Recommendation systems
Understanding of measures and their applications
Customer Analytics
Why Data Visualisation?
Story telling through data
Visualization & Communicating using Data Visualisation
Dashboards and Automation
Visualisation Product
Motivation for Big Data
Getting Started with Hadoop Framework - Introducing Hadoop, Components of Hadoop
Getting Started with Hadoop Framework - Hadoop in the Cloud
Understanding HBase
Analysing Data with Hive
Analysing Data with Pig
Time Series and Forecasting
Artificial Intelligence (AI)
Neural Networks
Understanding Spark
Spark programming
Real-time data stream Analytics (Storm)
Transition to Corporate Culture: 4 Hours
Communication
Spoken Communication
Written Communication
Presentation Skills
Team Work
FAQ
Lorem ipsum dolor sit amet, consectetur adipisicing elit,
sed do eiusmod tempor incididunt ut labore et dolore magna aliqua. Ut enim ad minim veniam,
quis nostrud exercitation ullamco laboris nisi ut aliquip ex ea commodo consequat.
Lorem ipsum dolor sit amet, consectetur adipisicing elit,
sed do eiusmod tempor incididunt ut labore et dolore magna aliqua. Ut enim ad minim veniam,
quis nostrud exercitation ullamco laboris nisi ut aliquip ex ea commodo consequat.
Lorem ipsum dolor sit amet, consectetur adipisicing elit,
sed do eiusmod tempor incididunt ut labore et dolore magna aliqua. Ut enim ad minim veniam,
quis nostrud exercitation ullamco laboris nisi ut aliquip ex ea commodo consequat.