Fundamentals of Data Science and Analytics detailed syllabus for Artificial Intelligence & Data Science (AI&DS) for 2021 regulation curriculum has been taken from the Anna University official website and presented for the AI&DS 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 & Data Science 4th Sem scheme and its subjects, do visit AI&DS 4th Sem 2021 regulation scheme. The detailed syllabus of fundamentals of data science and analytics is as follows.
Course Objectives:
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Unit I
INTRODUCTION TO DATA SCIENCE 08 Need for data science – benefits and uses – facets of data – data science process – setting the research goal – retrieving data – cleansing, integrating, and transforming data – exploratory data analysis – build the models – presenting and building applications.
Unit II
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Unit III
INFERENTIAL STATISTICS 09 Populations – samples – random sampling – Sampling distribution- standard error of the mean -Hypothesis testing – z-test – z-test procedure -decision rule – calculations – decisions -interpretations – one-tailed and two-tailed tests – Estimation – point estimate – confidence interval -level of confidence – effect of sample size.
Unit IV
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Unit V
PREDICTIVE ANALYTICS 09 Linear least squares – implementation – goodness of fit – testing a linear model – weighted resampling. Regression using StatsModels – multiple regression – nonlinear relationships – logistic regression – estimating parameters – Time series analysis – moving averages – missing values -serial correlation – autocorrelation. Introduction to survival analysis.
Course Outcomes:
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Text Books:
- David Cielen, Arno D. B. Meysman, and Mohamed Ali, Introducing Data Science, Manning Publications, 2016. (first two chapters for Unit I).
- Robert S. Witte and John S. Witte, Statistics, Eleventh Edition, Wiley Publications, 2017.
- Jake VanderPlas, Python Data Science Handbook, OReilly, 2016.
Reference Books:
- Allen B. Downey, Think Stats: Exploratory Data Analysis in Python, Green Tea Press, 2014.
- Sanjeev J. Wagh, Manisha S. Bhende, Anuradha D. Thakare, Fundamentals of Data Science, CRC Press, 2022.
- Chirag Shah, A Hands-On Introduction to Data Science, Cambridge University Press, 2020.
- Vineet Raina, Srinath Krishnamurthy, Building an Effective Data Science Practice: A Framework to Bootstrap and Manage a Successful Data Science Practice, Apress, 2021.
For detailed syllabus of all other subjects of Artificial Intelligence & Data Science, 2021 regulation curriculum do visit AI&DS 4th Sem subject syllabuses for 2021 regulation.
For all Artificial Intelligence & Data Science results, visit Anna University AI&DS all semester results direct link.