Big Data Specialization
Big data Specialization is ideal for someone who wants to learn both Hadoop and Spark-the two most used technologies in Big Data today.
- Basic understanding of programming
- Inclination to work in the technical domain
You can register for one of our free events to interact with our faculty or also attend a trial class.
Industry immersion sessions enable students to interact with Big Data Analytics practitioners from top companies like Twitter, Facebook, Vodafone, Barclays, PwC, Zomato, etc. to make them understand how their organizations use Big Data & Data Science.
Click here to view one such session taken by Sandeep Tompala- Senior Manager- Data Consulting, Vodafone.
- Next Batch Start Date: 29th September
- Class Timing: Sat,Sun 11 am - 01 pm
- Mode: Online
- Certification of Completion: Yes
- Certification: Yes, Subject to clearing exam
Either of the two core modules mentioned below 0/3
- 1. Hadoop
- 2. Spark
- 3. Big Data Integration & Processing
Hadoop (6 weeks) 0/10
- 1. Module 1: Introduction to Big Data
- 2. Module 2: Python Essentials – I
- 3. Module 3: Python Essentials – II
- 4. Module 4: Introduction to Hadoop
- 5. Module 5: Hadoop Architecture & Ecosystem
- 6. Module 6: Hadoop Distributed File System(HDFS)
- 7. Module 8: MapReduce Programming with Python
- 8. Module 9: Apache Pig
- 9. Module 10: Apache Pig Hands – on
- 10. Module 11: Apache Hive
Spark(5 weeks) 0/10
- 1. Module 1: Programming with Scala-I
- 2. Module 2: Programming with Scala-II
- 3. Module 3: Introduction to Apache Spark architecture
- 4. Module 4: RDD, transformations and actions
- 5. Module 5: Spark Programming
- 6. Module 6: Spark SQL
- 7. Module 7: Spark Streaming – I
- 8. Module 8: Spark Streaming – II
- 9. Module 9 Machine Learning with Spark MLlib
- 10. Module 10: Live Practice session
All classes take place over the weekends in the mornings. There’ll be one class of 2 to 2.5 hours on Saturdays and Sundays each. This means that you can now acquire in-demand skills without compromising on your schedule.