Professional Diploma in Big Data & Data Analytics

Eligibility: BE, B.Tech, ME, M.Tech, MCA, BCA, MSc, BSc
Duration: 2.5 Months

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From advertising to healthcare, almost every industry is now adopting Data Science technology to get an edge over the businesses. Data Science has recorded six times faster growth than the average growth rate of IT industry in the past couple of years. According to the market experts, it would sustain the momentum and continue to outpace other IT sectors by a significant margin in the years to come. If you are looking to make a career in one of the fastest growing IT sectors, there is no better alternative than data science.

Using massive datasets to guide decisions is becoming more and more important for modern businesses. Hadoop and MapReduce are fundamental tools for working with big data. By knowing how to deploy your own Hadoop clusters, you’ll be able to start exploring big data on your own.


  • Programming in Python
  • Data Analytics using Python
  • Cloud Computing
  • Big Data and Hadoop

Python Programming - 12 days

  • Python Introduction
  • Python Lists
  • Exception Handling
  • Flow Control
  • Set, Tuple and Dictionary
  • File Handling
  • Functions
  • List Comprehensions
  • Object Oriented Programming in Python

Data Analysis and Visualization in Python - 10 days

  • Mathematical Computing with Python(NumPy)
  • Importing Data in Python
  • Data Manipulation with Pandas
  • Data Ingestion & Inspection
  • Exploratory Data Analysis
  • Data Visualization using Matplotlib

Cloud Computing - 3 days

  • Fundamental of Cloud
  • Amazon EC2 and EBS
  • Deploying Infrastructure as a Service(IaaS)
  • Migrating to the Cloud
  • AWS Architecture
  • Exploiting Software as a Service(SaaS)
  • Building a Business Case
  • Amazon Storage Services
  • AWS Management Console
  • Delivering Platform as a Service (PaaS)
  • Adopting the Cloud

Web Technologies J2EE - 8 days

  • Introduction to Big Data & Hadoop
  • Hadoop Installation and Configuration
  • Hadoop Streaming
  • Pig Latin statements and programming
  • Introduction of Hive Data-Warehouse
  • DDL & DML with Hive QL
  • Overview of HBase
  • Working of Hadoop
  • HDFS
  • Programming with Rhadoop
  • Pig native functions
  • Hive Architecture
  • Hive functions
  • HBase Architecture and Commands
  • Hadoop Architecture
  • MapReduce
  • Pig commands and control structures
  • Hive QL
  • UDFs
  • CRUD operations