Professional Diploma in Big Data & Data Analytics

Eligibility: BE, B.Tech, ME, M.Tech, MCA, BCA, MSc, BSc
Duration: 2 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
  • Database Concepts
  • Big Data and Hadoop
  • Data Analytics using Python
  • Cloud Computing
  • Programming in C and Data Structure (Optional)

Python Programming - 10 days

Python is an open-source, easy to learn, powerful programming language. It has efficient high-level data structures and a simple but effective approach to object-oriented programming. Python's elegant syntax and dynamic typing, together with its interpreted nature, make it an ideal language for scripting and rapid application development in many areas on most platforms. A leading global survey firm has found that the number of people interested in learning Python is rising.

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

Database : SQL Fundamentals - 5 days

  • Introduction to Database Concepts
  • Using DDL statement to Create and Manage Tables
  • Reporting Aggregated data using Group Functions
  • Displaying data from Multiple tables using Joins
  • Retrieving Data with SQL SELECT Statement
  • Using Single-Row functions to Customize Output
  • Using Sub queries to Solve Queries
  • Manipulating Data : Insert, Update, Delete
  • Restricting and Sorting Data
  • Set Operators

Big Data & Hadoop - 15 days

In this course you will learn the big data concepts and terminology, and how big data isn't just about the size of data. Apache Hadoop is one of the hottest technologies that paves the ground for analyzing big data. Learn more about what Hadoop is and its components, such as MapReduce and HDFS. Come on this journey to play with large data sets and see Hadoop’s method of distributed processing.

  • 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

Data Analysis and Visualization in Python - 6 days

Data visualization is the graphical representation of data in order to interactively and efficiently convey insights to clients, customers, and stakeholders in general. It is a way to summarize your findings and display it in a form that facilitates interpretation and can help in identifying patterns or trends. In this Data Visualization with Python course, you'll learn how to create interesting graphics and charts and customize them to make them more effective and more pleasing to your audience.

  • 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 - 7 days

  • Fundamental of Cloud
  • Virtualization concepts
  • Cloud Platform in Industries
  • Overview on Amazon Storage Services
  • Cloud Service Models : IaaS, PaaS, SaaS
  • Limitation and challenges of cloud Environments
  • Cloud Applications
  • Cloud Deployment Models
  • Attacks in Public clouds
  • Case Study : AWS

Optional Module: Programming in C and Advance C - 18 days

  • Introduction to C
  • Preprocessor Directives
  • Pointers
  • File I/O : Sequential and Random Access
  • Formatted I/O
  • Decision control statements & Loops
  • Storage classes(Internal Linkage & External Linkage)
  • Dynamic Memory
  • Function Pointers
  • Command Line Arguments
  • Modular programming using functions
  • Arrays and Strings User Defined Data Types
  • User Defined Data Types
  • Variable number of arguments

Big Data & Data Analytics Project Synopsis

  • Stock Market Data Analysis
  • Word frequency in Novel
  • Risk and Returns: The sharpe ratio

Embedded Systems Design Training Calendar

Program Name Start Date Duration
Professional Diploma in Big Data & Data Analytics October- 3rd, 10th, 17th , 24th & 31st - 2018 2 months

Who can take up the Professional Diploma in Big Data & Data Analytics Course?

The data science role requires the perfect amalgam of experience, data science knowledge, and using the correct tools and technologies. It is a good career choice for both new and experienced professionals. Aspiring professionals of any educational background with an analytical frame of mind are most suited to pursue the Program.

What is Professional Diploma in Big Data & Data Analytics at Cranes Varsity?

Professional Diploma in Big Data & Data Analytics has been structured and framed based on the industry feedback and their expectations. It emphasizes more on Hands-on knowledge on respective modules enhancing the skills and in depth domain knowledge which makes the student industry ready. It covers Programming in Python with focus on Data Analytics and working with Big Data using Hadoop.

Is it worth to learn Big Data Systems?

There is a huge demand for people with skills to manage, analyze and help organizations use Big Data effectively. Big Data professionals are among the highest paid in the IT industry.

What are the analytics tools covered in Python?

Numpy, Pandas and Matplotlib.

In which domain of Big Data Analytics can I get a Job?

BFSI, Retail, Manufacturing, Healthcare.