Big Data Analytics Foundation
Learn the fundamentals of the hottest framework in Big Data (i.e. Hadoop) and Data Analytics through Python & R (the two most popular tools in Data Science) through this combo course.
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: 6th January
- Class Timing: WE:Sat,Sun(11 am - 01 pm), WD:Tue,Thurs ( 9 pm - 11 pm ), Fast track batch = Weekend (WE) + Weekday (WD).
- Mode: Online
- Certification of Completion: Yes
- Certification: Yes, Subject to clearing exam
Big Data Analytics Foundation 0/2
- 1. Hadoop
- 2. Data analytics with Python & R*
- 1. Introduction to Big Data
- 2. Python Essentials -1
- 3. Python Essentials -2
- 4. Intro to Hadoop
- 5. Hadoop Architecture & Ecosystem
- 6. Hadoop Distributed File System (HDFS)
- 7. Introduction to MapReduce
- 8. MapReduce Programming (Python)
- 9. Apache Pig
- 10. Apache Pig Hands – on
- 11. Apache Hive
- 12. Apache Hive Hands – on
Data analytics with Python & R* 0/11
- 1. Data Science Intro, Fundamentals, Use Cases
- 2. Python Basics: Basic Syntax, Data Structures
- 3. Python Basics: Loops, If-elif statements, Functions, Exception Handling
- 4. Statistics 1: Normal and Binomial Distribution, Random Variable, Pictorial Representations
- 5. Statistics 1: Measures of central tendency, Population, Sample, Probability Distribution
- 6. Python Advanced: Numpy, Pandas
- 7. Python Advanced: Data Manipulation, Matplotlib
- 8. Exploratory Data Analysis & Pre-recorded: R programming, EDA using R
- 9. Exploratory Data Analysis: Data Visualisation
- 10. Exploratory Data Analysis: Case Study
- 11. Recorded: R programming, EDA using R
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.