2024 Master class on Data Science using Python A-Z for ML

Course Curriculum

Chapter 1: BONUS : Python Crash Course

Lecture 1: Variables in Python

Lecture 2: Conditionals & If statement

Lecture 3: Example for If statement

Lecture 4: If else statement

Lecture 5: Example of If else statement

Lecture 6: Nested If statement

Lecture 7: Example for Nested If statement

Lecture 8: Elif statement

Lecture 9: Example for Elif statement

Lecture 10: While loop

Lecture 11: Example of while loop

Lecture 12: For Loop

Lecture 13: Example of For Loop

Lecture 14: Break & Continue Statement

Lecture 15: Introduction to containers

Lecture 16: Creating and accessing lists in Python

Lecture 17: List indexing and slicing

Lecture 18: Working with List methods

Lecture 19: Working with operators on lists

Lecture 20: List Comprehension

Lecture 21: Tuple : definition

Lecture 22: Tuples

Lecture 23: Tuple Indexing & Slicing

Lecture 24: Manipulating Tuples

Lecture 25: Unpacking Tuples

Lecture 26: Sets

Lecture 27: Dictionaries

Lecture 28: Basics of dictionary

Lecture 29: Accessing dictionary

Lecture 30: len, str & type functions in dictionary

Lecture 31: Functions in python

Lecture 32: Example program1 on Functions

Lecture 33: Example program2 on functions

Chapter 2: Data Handling using Numpy

Lecture 1: Introduction to modules in python

Lecture 2: Creating & Displaying 1D array

Lecture 3: Understanding 1D array Index

Lecture 4: Creating Array of 0's and Array of 1's

Lecture 5: Sorting elements in 1D array

Lecture 6: Slicing a 1D array

Lecture 7: Mathematical Operations on Array

Lecture 8: Searching an element in a Array

Lecture 9: Filtering an array

Lecture 10: Checking whether given array is empty or not ?

Lecture 11: Creating & Displaying 2D array

Lecture 12: ndim Attribute

Lecture 13: Size Attribute

Lecture 14: Shape and reshape of array

Lecture 15: Creating an Identity Matrix

Lecture 16: arange()

Lecture 17: linspace()

Lecture 18: Random array

Lecture 19: Random matrix

Lecture 20: Creating a diagonal matrix

Lecture 21: Flatten a Matrix

Lecture 22: Computing Trace of a Matrix

Lecture 23: Finding Transpose of a Matrix

Lecture 24: Negative indexing to access elements in a 2D array

Chapter 3: Data Handling using Pandas

Lecture 1: Introduction to Pandas

Lecture 2: Working with series in Pandas

Lecture 3: Combining series with Numpy

Lecture 4: Finding number of elements in a series

Lecture 5: Computing mean, max and min in a series

Lecture 6: Sorting a Series

Lecture 7: Displaying Unique values in a Series

Lecture 8: Summary of series statistics

Lecture 9: Creating DataFrame From Series

Lecture 10: Creating DataFrame from List of Dictionaries

Lecture 11: Data Frame access using row-wise and column-wise.

Lecture 12: Add, Rename and Delete Columns in a Data Frame

Lecture 13: Deleting rows and cols using drop()

Lecture 14: Boolean Indexing in DataFrames

Lecture 15: Concatenating DataFrames

Chapter 4: Data Visualization using Matplotlib in Python

Lecture 1: Introduction to Matplotlib

Lecture 2: Creating Line Graph

Lecture 3: Creating Bar Graph

Lecture 4: Creating Scatter Graph

Lecture 5: Creating Histogram Graph

Lecture 6: Creating Pie Chart

Lecture 7: Creating 3D Plot

Lecture 8: Creating 3D Line graph

Chapter 5: Data Visualization using Seaborn in Python

Lecture 1: Understanding a sample Dataset (Downloadable)

Lecture 2: Introduction to Seaborn

Lecture 3: Swarm Plot

Lecture 4: Violin Plot

Lecture 5: Facet Grids

Lecture 6: Heatmap

Chapter 6: Problem Solving Assignments

Chapter 7: Projects

Chapter 8: Bonus Lecture