COURSE NAME
Machine Learning & Deep Learning Course
1. Machine Learning Course 
Python Basics
Conditionals, Loops and Functions
Lists and Dictionaries
2D Lists and Numpy
Pandas
Plotting Graphs
Introduction to ML
Linear Regression
MultiVariable Regression and Gradient Descent
Logistic Regression
Classification Measures
Decision Trees - 1
Decision Trees - 2
Feature Scaling
Random Forests
Naive Bayes
Project: Text Classification
KNN
SVM
PCA
PCA - 2
NLP - 1
NLP - 2
Git
Neural Networks - 1
Neural Networks - 2
Tensor Flow
Keras
CNN - 1
CNN - 2
RNN
LSTM
Unsupervised Learning - 1
Unsupervised Learning - 2
Git
Topics
Example With Linear Decision Boundary
Finding Non Linear Decision Boundaries
Neural Network Terminology
No. of Parameters in Neural Network
Forward and Backward Propagation
Cost Function
How to handle Multiclass classification
