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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Frequently Asked Questions
Find answers to common questions about the Exploratory Data Analysis course.
The Exploratory Data Analysis course introduces learners to the techniques used to understand, summarise and visualise datasets before advanced modelling begins. It focuses on identifying patterns, distributions, relationships and useful insights within real-world data.
The course is suitable for BE and BTech students from different streams, non-engineering students with a STEM background, and working professionals who want to move into analytics or data science roles.
You will learn measures of central tendency and dispersion, data distributions, histograms, box plots, scatterplots, correlation and techniques for examining relationships between variables. The course also introduces principal component analysis and dimensionality reduction.
No prior statistics coursework is assumed. The course is designed to provide a working foundation in data exploration. Basic comfort with quantitative reasoning can help learners progress through the concepts more easily.
The course covers mean, median and mode, variance, standard deviation, correlation, histograms, box plots, scatterplots and dimensionality reduction. These techniques help learners summarise datasets and identify meaningful relationships and patterns.
Yes. Data visualization is an important part of exploratory data analysis. Learners work with visual techniques such as histograms, box plots and scatterplots to examine distributions, identify unusual values and understand relationships between variables.
Yes. The course introduces the intuition behind Principal Component Analysis and dimensionality reduction. Learners gain an understanding of how these techniques can help simplify complex datasets while retaining useful information.
Yes. The Exploratory Data Analysis course is delivered in a self-paced online format, allowing learners to complete the learning material according to the structure of the programme and their own schedule.
The Exploratory Data Analysis course has a duration of approximately 5 hours. It is listed at NSQF Level 5 and provides a focused foundation in data exploration before learners move into more advanced analytics or modelling.
Learners receive a joint certificate of participation on completing the course. Learners who successfully clear the SSC NASSCOM assessment can earn the industry-recognised NASSCOM certification aligned with National Occupational Standards.