# Machine Learning and Data Science Using Python

## Short Description

Begin your ML and DS Journey

## Description

Module-1â€‹

Welcome to the Pre-Program Preparatory Content

Session-1:â€‹

1) Introductionâ€‹

2) Preparatory Content Learning Experience

MODULE-2â€‹

INTRODUCTION TO PYTHON

Session-1:â€‹

Understanding Digital Disruption Course structureâ€‹

1) Introductionâ€‹

2) Understanding Primary Actionsâ€‹

3) Understanding es & Important Pointers

Session-2:â€‹

Introduction to pythonâ€‹

1) Getting Started â€” Installationâ€‹

2) Introduction to Jupyter Notebookâ€‹

The Basics Data Structures in Python

3) Listsâ€‹

4) Tuplesâ€‹

5) Dictionariesâ€‹

6) Sets

Session-3:â€‹

Control Structures and Functionsâ€‹

1) Introductionâ€‹

2) If-Elif-Elseâ€‹

3) Loopsâ€‹

4) Comprehensionsâ€‹

5) Functionsâ€‹

6) Map, Filter, and Reduceâ€‹

7) Summary

Session-4:â€‹

Practice Questionsâ€‹

1) Practice Questions Iâ€‹

2) Practice Questions II

Module-3â€‹

Python for Data Science

Session-1:â€‹

Introduction to NumPyâ€‹

1) Introductionâ€‹

2) NumPy Basicsâ€‹

3) Creating NumPy Arraysâ€‹

4) Structure and Content of Arraysâ€‹

5) Subset, Slice, Index and Iterate through Arraysâ€‹

6) Multidimensional Arraysâ€‹

7) Computation Times in NumPy and Standard Python Listsâ€‹

8) Summary

Session-2:â€‹

Operations on NumPy Arraysâ€‹

1) Introductionâ€‹

2) Basic Operationsâ€‹

3) Operations on Arraysâ€‹

4) Basic Linear Algebra Operationsâ€‹

5) Summary

Session-3:â€‹

Introduction to Pandasâ€‹

1) Introductionâ€‹

2) Pandas Basicsâ€‹

3) Indexing and Selecting Dataâ€‹

4) Merge and Appendâ€‹

5) Grouping and Summarizing Data framesâ€‹

6) Lambda function & Pivot tablesâ€‹

7) Summary

Session-4:â€‹

Getting and Cleaning Dataâ€‹

1) Introduction

2) Reading Delimited and Relational Databasesâ€‹

4) Getting Data from APIsâ€‹

5) Reading Data from PDF Filesâ€‹

6) Cleaning Datasetsâ€‹

7) Summary

Session-5:â€‹

Practice Questionsâ€‹

1) NumPy Practice Questionsâ€‹

2) Pandas Practice Questionsâ€‹

3) Pandas Practice Questions Solution

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