CSE

CCS346: Exploratory Data Analysis syllabus for CSE 2021 regulation (Professional Elective-I)

Exploratory Data Analysis detailed syllabus for Computer Science & Engineering (CSE) for 2021 regulation curriculum has been taken from the Anna Universities official website and presented for the CSE students. For course code, course name, number of credits for a course and other scheme related information, do visit full semester subjects post given below.

For Computer Science & Engineering 5th Sem scheme and its subjects, do visit CSE 5th Sem 2021 regulation scheme. For Professional Elective-I scheme and its subjects refer to CSE Professional Elective-I syllabus scheme. The detailed syllabus of exploratory data analysis is as follows.

Exploratory Data Analysis

Course Objectives:

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Unit I

EXPLORATORY DATA ANALYSIS 6 EDA fundamentals – Understanding data science – Significance of EDA – Making sense of data -Comparing EDA with classical and Bayesian analysis – Software tools for EDA – Visual Aids for EDA- Data transformation techniques-merging database, reshaping and pivoting, Transformation techniques.

Unit II

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Unit III

UNIVARIATE ANALYSIS 6 Introduction to Single variable: Distribution Variables – Numerical Summaries of Level and Spread -Scaling and Standardizing – Inequality.

Unit IV

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Unit V

MULTIVARIATE AND TIME SERIES ANALYSIS 6 Introducing a Third Variable – Causal Explanations – Three-Variable Contingency Tables and Beyond – Fundamentals of TSA – Characteristics of time series data – Data Cleaning – Time-based indexing – Visualizing – Grouping – Resampling.

Practical Exercises:

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Course Outcomes:

At the end of this course, the students will be able to:

  1. Understand the fundamentals of exploratory data analysis.
  2. Implement the data visualization using Matplotlib.
  3. Perform univariate data exploration and analysis.
  4. Apply bivariate data exploration and analysis.
  5. Use Data exploration and visualization techniques for multivariate and time series data.

Text Books:

  1. Suresh Kumar Mukhiya, Usman Ahmed, Hands-On Exploratory Data Analysis with Python, Packt Publishing, 2020. (Unit 1)
  2. Jake Vander Plas, “Python Data Science Handbook: Essential Tools for Working with Data”, First Edition, O Reilly, 2017. (Unit 2)
  3. Catherine Marsh, Jane Elliott, Exploring Data: An Introduction to Data Analysis for Social Scientists, Wiley Publications, 2nd Edition, 2008. (Unit 3,4,5)

Reference Books:

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For detailed syllabus of all the other subjects of Computer Science & Engineering 5th Sem, visit CSE 5th Sem subject syllabuses for 2021 regulation.

For all Computer Science & Engineering results, visit Anna University CSE all semester results direct link.

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