Module 1 : Introduction
What is Data Science
Application of Statistics and Programming in Data Science
Importance of Data in Al, Data Science and Data Analytics
Module 2 : Statistics
Introduction to Data Types
Basic Statistics
Probability
Inferential Statistics
Module 3 : Python
Python Introduction
Data Types and Data Structure Variables
Functions
Control Flow
Exception handling
Classes
Module 4: DA with Python
Useful Data Science libraries
Import Datasets and Modules
Numpy Arrays
Pandas
Data Visualization
Module 5 : Predictive Analysis
Introduction to PA & ML
Linear Regression
Logistic Regression
Cluster Analysis
Time Series for forecasting
Module 6 : Machine Learning
Decision Tree
Ensemble Methods in Tree Based Models
Support Vector Machines(SVM)
K-nearest Neighbor (KNN)
Module 7 : Natural Language Processing(NLP)
Natural Language Processing (NLP)
Extracting the data using NLP
Text Preprocessing for application
Text Indexing for Analysis
Feature Engineering for word cloud
Advanced NLP and ML for NLP
Implementing Industrial Applications
Natural Processing Language and Deep Learning for NLP