Syllabus - Data Analytics & Visualization (CD702 (A))

CSE

Data Analytics & Visualization (CD702 (A))

VII-Semester

Unit 1

Data Definitions and Analysis Techniques

Elements, Variables, and Data categorization Levels of Measurement Data management and indexing Introduction to Statistical Concepts: Sampling Distributions, Resampling, Statistical Inference and Descriptive Statistics, Measures of central tendency, Measures of location of dispersions

Unit 2

Advance Data analysis techniques

Statistical hypothesis generation and testing, Chi-Square test, t-Test, Analysis of variance, Correlation analysis, Maximum likelihood test, Regression Modelling, Multivariate Analysis, Bayesian Modelling, Inference and Bayesian Network, Regression analysis

Unit 3

Data Wrangling

Intro to Data Wrangling, Gathering Data, Assessing Data, Cleaning Data. Data Visualization in Data Analysis: Design of Visualizations, Univariate Exploration of Data, Bivariate Exploration of Data, Multivariate Exploration of Data, Explanatory Visualizations.

Unit 4

Data Ecosystem

Overview of the Data Analyst Ecosystem, Types of Data, Understanding Different Types of File Formats, Sources of Data, Overview of Data Repositories, NoSQL, Data Marts, Data Lakes, ETL, and Data Pipelines, Foundations of Big Data, Big Data processing tools such as Hadoop, Hadoop Distributed File System (HDFS), Hive, and Spark

Unit 5

Data Visualization tools

Python visualization libraries (matplotlib, pandas, seaborn, ggplot, plotly), Introduction to PowerBI tools, Examples of inspiring (industry) projects- Exercise: create your own visualization of a complex dataset.

Practicals

Reference Books

  • Joel Grus, Data Science from Scratch, Shroff Publisher Publisher /O’Reilly Publisher Media

  • Annalyn Ng, Kenneth Soo, Numsense! Data Science for the Layman, Shroff Publisher Publisher

  • Cathy O’Neil and Rachel Schutt. Doing Data Science, Straight Talk from The Frontline. O’Reilly Publisher Media.

  • Jure Leskovek, Anand Rajaraman and Jeffrey Ullman. Mining of Massive Datasets. v2.1, Cambridge University Press.

  • Jake VanderPlas, Python Data Science Handbook, Shroff Publisher Publisher /O’Reilly Publisher Media

  • Philipp Janert, Data Analysis with Open Source Tools, Shroff Publisher Publisher /O’Reilly Publisher Media.