Importance of Math and Stats in Data Science Career

In this video, let's understand how learning Math/Stats can help you in your data science career.

Contents

1. Course Overview

Importance of Math and Stats in Data Science Career

How Is This Course Different from Other Courses on the Internet?

What Support Do You Provide If I Have Questions?

Who Should Take This Course?

Pre-requisites

System Requirements

Course Overview

2. Enhance your Learning Experience

Join Discord

Video Resolution

3. Data & Visualization Basics

Types of Data

Pie Chart and Bar Chart

Quiz

Histograms and Line Chart

Quiz

Scatter and Bubble Plot

Quiz

Univariate vs. Bivariate vs. Multivariate Analysis

4. Pandas, Matplotlib and Seaborn Basics

Pandas Introduction and Installation

Dataframe Basics

Read, Write Excel and CSV Files

Handle NA Values - Part 1

Handle NA Values - Part 2

Group By

Concat and Merge

Matplotlib and Seaborn Basics

5. Measures Of Central Tendency and Dispersion

Descriptive vs. Inferential Statistics

Measures of Central Tendency: Mean, Median, Mode

Percentile

Analysis: Shoe Sales (Using Mean, Median, Percentile)

Quiz

Exercise

Measures of Dispersion: Range, IQR

Box or Whisker Plot

Outlier Treatment Using IQR and Box Plot

Quiz

Exercise

Measures of Dispersion: Variance and Standard Deviation

Analysis: Stock Returns Volatility (Using Variance and Std Dev)

Correlation

Correlation vs Causation

Quiz

Exercise

6. Probability Theory

Probability Basics

Quiz

Addition and Multiplication Rule

Quiz

Conditional Probability and Bayes Theorem

Quiz

7. Distributions

What Is a Distribution?

Skewness

Normal Distribution

Detect Outliers Using Normal Distribution

Quiz

Exercise

Z Score

Standard Normal Distribution (SND)

I Need a Favour

Quiz

Exercise

8. AtliQo Bank Project

Chapter Overview

Bashneer Grower’s Bank Venture

AtliQo Credit Card Launch: Problem Statement

Project Kick-off Meeting

Project Management Using Kanban

Tasks Breakdown and JIRA Board Setup

Meeting: Tony, Peter, Natasha

9. Phase 1: Find Target Market

Data Validation Of Acquired Data

Data Understanding, MySQL Setup

Data Import in Jupyter Notebook

Data Cleaning: Handle NULL Values (Annual Income)