Short Description
Begin your ML and DS Journey
Description
Module-1
Welcome to the Pre-Program Preparatory Content
Session-1:
1) Introduction
2) Preparatory Content Learning Experience
MODULE-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 Python
3) 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 NumPy
1) Introduction
2) NumPy Basics
3) Creating NumPy Arrays
4) Structure and Content of Arrays
5) Subset, Slice, Index and Iterate through Arrays
6) Multidimensional Arrays
7) Computation Times in NumPy and Standard Python Lists
8) Summary
Session-2:
Operations on NumPy 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) Introduction
2) Reading Delimited and Relational Databases
3) Reading Data from Websites
4) Getting Data from APIs
5) Reading Data from PDF Files
6) Cleaning Datasets
7) Summary
Session-5:
Practice Questions
1) NumPy Practice Questions
2) Pandas Practice Questions
3) Pandas Practice Questions Solution
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