**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

Python - Advanced Python Tools

**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'

Case Study - Loading the 'absenteeism module'

Case Study - Analyzing the Predicted Outputs in Tableau

Bonus lecture

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