Machine Learning and Data Science Using Python - Part 1

Module-1​Welcome to the Pre-Program Preparatory Content Session-1:​1) Introduction​2) Preparatory Content Learning ExperienceMODULE-2​INTRODUCTION TO PYTHON Session-1:​Understanding Digital Disruption Course structure​1) Introduction​2) Understanding Primary Actions​3) Understanding es & Important Pointers Session-2:​Introduction to python​1) Getting Started — Installation​2) Introduction to Jupyter Notebook​The Basics Data Structures in Python3) Lists​4) Tuples​5) Dictionaries​6) Sets Session-3:​Control Structures and Functions​1) Introduction​2) If-Elif-Else​3) Loops​4) Comprehensions​5) Functions​6) Map, Filter, and Reduce​7) Summary Session-4:​Practice Questions​1) Practice Questions I​2) Practice Questions II Module-3​Python for Data Science Session-1:​Introduction to Num Py​1) Introduction​2) Num Py Basics​3) Creating Num Py Arrays​4) Structure and Content of Arrays​5) Subset, Slice, Index and Iterate through Arrays​6) Multidimensional Arrays​7) Computation Times in Num Py and Standard Python Lists​8) Summary Session-2:​Operations on Num Py Arrays​1) Introduction​2) Basic Operations​3) Operations on Arrays​4) Basic Linear Algebra Operations​5) Summary Session-3:​Introduction to Pandas​1) Introduction​2) Pandas Basics​3) Indexing and Selecting Data​4) Merge and Append​5) Grouping and Summarizing Data frames​6) Lambda function & Pivot tables​7) Summary Session-4:​Getting and Cleaning Data​1) Introduction2) Reading Delimited and Relational Databases​3) Reading Data from Websites​4) Getting Data from AP Is​5) Reading Data from PDF Files​6) Cl