Online
Exploratory data analysis
Duration
5 Hours
Level
NSQF Level 5
Delivery
Self-paced online
Assessment
NASSCOM
Certificate
NASSCOM
Overview
Every analytics project starts the same way. Before you can model anything, you have to look at the data and understand what you are actually holding. Exploratory data analysis is that first pass, and it is the step that separates useful analysis from confident nonsense.
This five hour course, part of the AI Ascend program, gives you the working toolkit for summarising and visualising the key parameters in a dataset and drawing defensible inferences from what you find. You will learn how to describe a variable properly, how to see its shape, how to spot the relationships between variables, and how to compress a wide, correlated dataset into something you can actually reason about.
It is short, practical, and sits directly in the workflow of a data scientist. The techniques here are the ones you use on day one of any real project, and they carry forward into everything more advanced you go on to build.
What you will learn
By the end of the course you should be able to:
- Understand and apply measures of central tendency and dispersion
- Explore your data using histograms, box plots and bar plots
- Examine pairs of variables using scatterplots and scatterplot matrices
- Understand the intuition behind principal component analysis and carry it out
- Bring these techniques together into a coherent analytics pipeline for real business scenarios
Prerequisites
The course is designed for learners who want a working foundation in data exploration before moving into modelling. It suits:
- BE and BTech students from any stream
- Non-engineering students from a STEM background
- Working professionals moving into analytics or data science roles
No prior statistics coursework is assumed, though comfort with basic quantitative reasoning will help you move faster.
Skills and tools
Central tendency, mean, median and mode, variance and standard deviation, correlation, box plots, scatterplots, and dimensionality reduction.
Certificate
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