6 Month Certificate Programme in Big Data

This 6-month Big Data course will make you a pro in Big Data as you get to deep dive into advanced concepts such as Machine Learning with Spark and Big Data integration & processing while learning and practicing the major Big Data technologies like Hadoop, Spark, Sqoop, Flume, Kafka, Splunk and NoSQL databases such as MongoDB & HBase.
COURSE FEATURES
- 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.
Course Details
- Next Batch Start Date: 14th April
- Class Timing: Weekend: Sat, Sun(11 am - 01 pm), Fast track: Tue, Thurs ( 9 pm - 11 pm ) & Sat, Sun (11 am - 1 pm) IST
- Mode: Online
- Duration: 24 Weeks
- Certification of Completion: Yes
- Certification: Yes, Subject to clearance of exam
- Share:
3 CORE MODULES & 2 ELECTIVE MODULES 0/5
- 1. Hadoop – Core Module
- 2. Spark – Core Module
- 3. Big Data Integration & Processing – Core Module
- 4. MongoDB,Hbase,Sqoop & Flume – Elective Module
- 5. Machine Learning with Spark -Elective Module
6 Month Big Data Certification Program 0/43
- 1. Introduction to Big Data
- 2. Python Essentials – I
- 3. Python Essentials – II
- 4. Introduction to Hadoop
- 5. Hadoop Architecture & Ecosystem
- 6. Hadoop Distributed File System(HDFS)
- 7. Introduction to Map Reduce
- 8. MapReduce Programming with Python
- 9. YARN and MRv2
- 10. Apache Pig
- 11. Apache Hive
- 12. Scala programming -1
- 13. Scala programming -2
- 14. Introduction to Apache Spark (Architecture)
- 15. RDD, Transformations, Actions and Spark Programming
- 16. Spark SQL
- 17. Spark Streaming with Apache Kafka.
- 18. Machine Learning with Spark (MLLib)
- 19. Intro to NoSQL Databases & MongoDB
- 20. MongoDB Deep dive
- 21. Apache Hbase
- 22. Sqoop
- 23. Flume
- 24. Data lakes
- 25. Introduction to Machine learning
- 26. Statistics
- 27. Overview of Machine Learning algorithms
- 28. Spark MLlib datatypes
- 29. Classification
- 30. Linear regression, Logistic regression
- 31. Spark MLlib Decision tree
- 32. Spark MLlib KNN classification
- 33. Spark Clustering
- 34. Data lakes
- 35. Processing big data
- 36. Integration of Hadoop with MongoDB
- 37. Integration of Spark with MongoDB
- 38. Apache Kafka
- 39. Integration of Kafka with Spark
- 40. Splunk and Big data management
- 41. Big data processing using Splunk
- 42. Big data processing pipelines
- 43. 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.