Data structures and algorithms 
Competitive Programming 
Interview Preparation 
Web Development 
Data Science & Machine Learning 
Android Development 
COURSE NAME
Data Science & Machine Learning Complete
1. Data Science & Machine Learning Complete Course 
Introduction To Python
Conditions and Loops
Patterns
More on Loops
Functions
Tuples, Dictionary And Sets
Object Oriented Programming Systems(OOPs)
Pandas
Plotting Graphs
Structured Query Language(SQL) - Basic
Structured Query Language(SQL) - Advance
Indexing And SQLite
Application Programming Interfaces(APIs) - II
Web Scraping - BeautifulSoup
Web Scraping - Selenium
Web Scraping : Advanced Selenium
Statistics
Descriptive Statistics
Introduction to Machine Learning
Linear Regression
MultiVariable Regression And Gradient Descent
Feature Scaling
Logistic Regression
Classification Measures
Decision Trees - I
Decision Trees - II
Random Forests
Naive Bayes
Project: Text Classification
K-Nearest Neighbours(K-NN)
Support Vector Machine(SVM)
Principal Component Analysis(PCA) - I
Principal Component Analysis(PCA) - II
Natural Language Processing(NLP) - I
Natural Language Processing(NLP) - II
Neural Networks - I
Neural Networks - II
Tensor Flow
Keras
Convolutional Neural Network(CNN) - I
Convolutional Neural Network(CNN) - II
Recurrent Neural Network(RNN)
Long Short-Term Memory(LSTM)
Unsupervised Learning - I
Unsupervised Learning - II
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
