Foundations of Data Science detailed syllabus for Artificial Intelligence & Machine Learning (AI&ML) for 2021 regulation curriculum has been taken from the Anna University official website and presented for the AI&ML 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 Artificial Intelligence & Machine Learning 3rd Sem scheme and its subjects, do visit AI&ML 3rd Sem 2021 regulation scheme. The detailed syllabus of foundations of data science is as follows.
Course Objectives:
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Unit I
INTRODUCTION 9 Data Science: Benefits and uses – facets of data – Data Science Process: Overview – Defining research goals – Retrieving data – Data preparation – Exploratory Data analysis – build the modelpresenting findings and building applications – Data Mining – Data Warehousing – Basic Statistical descriptions of Data
Unit II
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Unit III
DESCRIBING RELATIONSHIPS 9 Correlation -Scatter plots -correlation coefficient for quantitative data -computational formula for correlation coefficient – Regression -regression line -least squares regression line – Standard error of estimate – interpretation of r2 -multiple regression equations -regression towards the mean
Unit IV
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Unit V
DATA VISUALIZATION 9 Importing Matplotlib – Line plots – Scatter plots – visualizing errors – density and contour plots -Histograms – legends – colors – subplots – text and annotation – customization – three dimensional plotting – Geographic Data with Basemap – Visualization with Seaborn.
Course Outcomes:
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Reference Books:
- Allen B. Downey, Think Stats: Exploratory Data Analysis in Python, Green Tea Press,2014.
For detailed syllabus of all other subjects of Artificial Intelligence & Machine Learning, 2021 regulation curriculum do visit AI&ML 3rd Sem subject syllabuses for 2021 regulation.
For all Artificial Intelligence & Machine Learning results, visit Anna University AI&ML all semester results direct link.