Syllabus Foundations of Data Science using Python - (IT25201) Python Language Basics and Data Structures : Python Language Basics - Scalar Types - Control Flow. Data Structures and Sequences : Tuple - List - Built-in Sequence Functions - dict - set - List, Set, and Dict Comprehensions. Functions : Namespaces, Scope and Local Functions - Returning Multiple Values - Functions Are Objects - Files and the Operating System. (Chapter - 1) Practical : 1. Programs using Data Frames. 2. Programs using functions and files. Numpy Basics : The NumPy ndarray : A Multidimensional Array Object - Universal Functions : Fast Element - Wise Array Functions - Array - Oriented Programming with Arrays - File Input and Output with Arrays - Linear Algebra - Pseudorandom Number Generation. (Chapter - 2) Practical : 1. Programs using numpy. 2. Programs to solve linear algebra problems with numpy functions. Pandas Basics : Introduction to pandas Data Structures - Loading and Understanding Data - Data aggregation for computing Descriptive Statistics - Data Cleaning and Preprocessing. (Chapter - 3) Practical : 1. Programs using numpy. 2. Solving linear algebra problems. Data Loading, Storage, and File Formats : Reading and Writing Data in Text Format - Binary Data Formats - Interacting with Web APIs - Interacting with Databases. (Chapter - 4) Practical : 1. Data and Databases. 2. Web APIs. Data Exploration : Data Transformation - String Manipulation. Data Wrangling : Hierarchical Indexing - Combining and Merging Datasets - Reshaping and Pivoting. (Chapter - 5) Practical : 1. String manipulations. 2. Data wrangling. Data Wrangling : Data Aggregation and Group Operations : GroupBy Mechanics - Data Aggregation - Apply : General split-apply-combine - Pivot Tables and Cross - Tabulation - Date and Time Data Types. (Chapter - 6) Practical : 1. Data aggregation operations. 2. Handle time series data. Data Visualization : Introduction to Data Visualization - Visualizing categorical data, visualizing time series data, Visualizing multiple variables - Visualizing Distribution & Relationships - Multivariate and Time Series Visualization exploration. (Chapter - 7) Practical : 1. Visualization of Different kinds of Data. 2. Distribution Analysis.
