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
Also check: css course