Big Data Practitioners 

1. Gün

Part 1 : Introduction

The Field of Data Science – The Various Data Science Disciplines
The Field of Data Science – Connecting the Data Science Disciplines
The Field of Data Science – The Benefits of Each Discipline
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: Mathematics

Matrices & Vectors & Tensors

2. Gün

Part 5: 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

3. Gün

Part 6 : Deep Learning – Introduction to Neural Networks
Deep Learning – How to Build a Neural Network from Scratch with NumPy

Part 7 : Data Science With BigData

Hadoop components and architecture
Hadoop configuration, administration, and management
How to use common Hadoop tools