




"It is a one-stop solution for professionals looking to upskill in Big Data. If you are looking to step up the ladder, then this is the right choice for you!"

Complete all courses successfully and receive Post-Graduate certificate. Become a part of the Big Data community with the PG Alumni status from BITS Pilani
Real time Aadhar verification, Amazon's User Recommendations, Facebook's newsfeed suggestions- all are possible due to Big Data!
Be it Manufacturing to E-commerce to Public Sector to Healthcare to Agriculture- Big Data is applicable everywhere! And its use cases are growing rapidly!
Thousands of job openings from top companies with 30-60% salary hikes for skilled Big Data professionals
Each course in this program is taught by top academicians from BITS and leading industry experts in big data from companies such as Accenture, Impetus, LatentView, JP Morgan, Slassy etc.
The curriculum has been developed by BITS faculty and leading Big Data companies. Most courses have an independent industry-sourced project that will be deployed by you on AWS Cloud. This syllabus will teach you end to end skills - a thorough understanding of fundamental concepts and thinking beyond tools!
Preparatory Sessions
The pre-program preparatory sessions will help augment & brush up your skills in fundamanetal computer science concepts. Prior experience with Java & SQL is strongly recommended to excel in the program.
Topics Covered:
Prep Sessions will be available to students upon enrolment.
To learn more about why should you be taking prep sessions, click here
Foundations of Big Data Systems
Duration : 8 weeks
In this course you will be given an introduction to Big Data and its common industry applications. You will also develop important foundations in data structures and algorithms that form the basis of the Big Data Systems used in the industry.
Topics Covered:
Course Outcomes:
You will be able to select and implement appropriate data structures to solve big data problems and also write Map and Reduce codes for distributed processing of data.
Programming Language Used: Java
Platforms for Big Data
Duration: 8 weeks
In this course, you will be exposed to the different platforms used for processing Big Data. Additionally, you will also learn how to set up a virtual machine for processing Big Data on your own computer as well as on the cloud.
Topics Covered:
Course Outcomes:
You will be able to perform batch processing operations on Big data on your own computer as well as on an Amazon EC2 instance. You will be able to retrieve and store data in HDFS using MapReduce & Apache Pig
Tools & Technologies Used: Hadoop, Apache Pig, Apache Spark & Dynamo DB
Processing Big Data - ETL & Batch Processing
Duration : 7 weeks
Learn about collecting and processing structured and unstructured data by performing ETL operations. Use workflow manager tools to learn automation of task flows
Topics Covered:
Course Outcomes:
You will learn to choose and use tools to ingest structured and unstructured data into big data processing systems and use Hive to perform data transformations. You will use OOZIE for managing your workflow.
Tools & Technologies Used: Sqoop, Apache Flume, Apache Hive and HBase.
Processing of Real Time Data & Streaming Data
Duration : 4 weeks
Ever wondered how you receive a notification based on your location? The answer lies in exploiting Real Time & Streaming Data. This course will expose you to the exciting world of processing real time data.
Topics Covered:
Course Outcomes:
You will be able to build real time data processing systems using Apache Storm and Apache Spark
Tools & Technologies Used: Apache Storm, Apache Flume, Apache Spark
Big Data Analytics
Duration : 5 weeks
In this course you will be introduced to the field of Big Data Analytics and you will learn about the libraries in Apache Spark used to perform Regression, Classification, Clustering on Big Data.
Topics Covered:
Course Outcomes:
Tools & Technologies used:
Spark (MLLib) and Scala*
* signifies optional/additional learning material for interested students
Program Fee
Course Duration
Mar'19 - Feb'2011 monthsWe recommend
10 hoursper week
Successfully launched
5 batches