Data Science Using Python

Introduction to Data Science

Need of Data Science

Core Components

Data Science Process

Big Data and Its Challenges

Data Science Applications

Introduction to Python

Python Uses

Installation

Operators

Data Structures

Decision Constructs and Looping

Functions

OOPs Concepts

Statistics

Basics of Statistics

Descriptive Statistics

Inferential Statistics

Qualitative vs. Quantitative Analysis

Hypothesis Testing

Python Libraries

Numpy

Pandas

Matplotlib

Introduction to Machine Learning

Introduction

Types

Supervised Learning

Unsupervised Learning

Predictive Analytics

Linear Regression

Logistic Regression

Decision Trees

Random Forest

Bagging and Boosting

Test 1

Project #1 - HR Analytics

Introduction to Neural Networks

Understanding Neural Networks

The Biological Inspiration

Perceptron

Learning & Binary Classification

Backpropagation Learning

Learning Feature Vectors for Words

Object Recognition

Deep Learning Using TensorFlow and Keras

Deep Learning Using TensorFlow and Keras

Introducing Tensorflow

Neural Networks using TensorFlow

Debugging and Monitoring

Convolutional Neural Networks

Keras for Classification and Regression

Setting up Keras

Different Layers in Keras

Creating a Neural Network

Training Models and Monitoring