Monday, January 25, 2021

The Data Science Course 2020 Complete Data Science Bootcamp Training

Course Detail:

Part 1 Introduction

The Field of Data Science - The Various Data Science Discipline

The Field of Data Science - Connecting the Data Science Disciplines

The Field of Data Science - The Benefits of Each Disciplines

The Field of Data Science - Popular Data Science Techniques

The Field of Data Science - Popular Data Science Tools

The Field of Data Science - Careers in Data Science

The Field of Data Science - Debunking Common Misconceptions

Part 2 Probability

Probability - Combinatorics

Probability - Bayesian Inference

Probability - Distributions

Probability - Probability in Other Fields

Part 3 Statistics

Statistics - Descriptive Statistics

Statistics - Practical Example Descriptive Statistics

Statistics - Inferential Statistics Fundamentals

Statistics - Inferential Statistics Confidence Intervals

Statistics - Practical Example Inferential Statistics

Statistics - Hypothesis Testing

Statistics - Practical Example Hypothesis Testing

Part 4 Introduction to Python

Python - Variables and Data Types

Python - Basic Python Syntax

Python - Other Python Operators

Python - Conditional Statements

Python - Python Functions

Python - Sequences

Python - Iterations

Part 5 Advanced Statistical Methods in Python

Advanced Statistical Methods - Linear regression with StasModels

Advanced Statistical Methods - Multiple Linear Regression with StatsModels

Advanced Statistical Methods - Linear Regression with sklearn

Advanced Statistical Methods - Practical Example Linear Regression

Advanced Statistical Methods - Logistic Regression

Advanced Statistical Methods - Cluster Analysis

Advanced Statistical Methods - K-Means Clustering

Advanced Statistical Methods - Other Types of Clustering

Part 6 Mathematics

Part 7 Deep Learning

Deep Learning - Introduction to Neural Networks

Deep Learning - How to Build a Neural Network from Scratch with NumPy

Deep Learning - TensorFlow 2.0 Introduction

Deep Learning - Digging Deeper into NNs Introducing Deep Neural Networks

Deep Learning - Overfitting

Deep Learning - Initialization

Deep Learning - Digging into Gradient Descent and Learning Rate Schedules

Deep Learning - Preprocessing

Deep Learning - Business Case Example

Deep Learning - Conclusion

Appendix Deep Learning - TensorFlow 1 Introduction

Appendix Deep Learning - TensorFlow 1 Classifying on the MNIST Dataset

Appendix Deep Learning - TensorFlow 1 Business Case

Software Integration

Case Study - What's Next in the Course

Case Study - Preprocessing the 'Absenteeism Data'

Case Study - Applying Machine Learning to Create the 'absenteeism module'