Data Science for Everyone

سرفصل های دوره

Data Science Essentials for Beginners

1 - Introduction

1 -Data Science for Everyone Materials.zip

1 -Why Do We Need Data Literacy

2 -What is Data Science

3 -Data Science Workflow

4 -Data Type

5 -DIKW Pyramid

2 - Analytics for Decision Making

1 -Data-Driven Decision Making

2 -Business Analytics

3 -Machine Learning

3 - Exploratory Data Analysis Part 1

1 -What is EDA

2 -Stevens Typology

3 -Univariate Analysis

4 -Multivariate Analysis

4 - Exploratory Data Analysis Part 2

1 -Probability Basics

2 -Conditional Probability

3 -Bayes Theorem

5 - Data Preprocessing

1 -Data Cleaning

2 -Handling Missing Data

3 -Data Transformation

4 -Data Reduction

6 - Data Visualization

1 -Data Visualization for Univariate Analysis Part 1

2 -Data Visualization for Univariate Analysis Part 2

3 -Data Visualization for Univariate Analysis Part 3

4 -Data Visualization for Bivariate Analysis

5 -Data Visualization for Higher Dimensions

7 - Diagnostic Analytics Part 1

1 -Statistical Hypothesis Testing

2 -Probability Distribution

3 -Law of Large Numbers and Central Limit Theorem

4 -Hypothesis Testing Part 1

5 -Hypothesis Testing Part 2

8 - Diagnostic Analytics Part 2

1 -t-test

2 -Two-sample t-test

3 -Chi-Squared Test

9 - Diagnostic Analytics Part 3

1 -Correlation

2 -Regression

3 -Hypothesis Testing by Correlation and Hypothesis

4 -Multiple Regression Analysis

10 - Predictive Analytics Part 1

1 -Types of Machine Learning

2 -Regression

3 -Performance Metrics of Regression Models Part 1

4 -Performance Metrics of Regression Models Part 2

11 - Predictive Analytics Part 2

1 -What is Classification

2 -Logistic Regression

3 -Decision Tree

4 -Ensemble Learning

5 -Performance Metrics of Classification Models Part 1

6 -Performance Metrics of Classification Models Part 2

12 - Cluster Analysis

1 -What is Clustering

2 -Distance-Based Clustering

3 -K-Means Clustering

4 -Example Customer Segmentation

13 - Deep Learning Part 1

1 -What is Deep Learning

2 -Perceptron

3 -Multilayer Perceptron

4 -Artiricial Neural Network

14 - Deep Learning Part 2

1 -How to Train a Neural Network

2 -Optimization

3 -Regularization Part 1

4 -Reguralization Part 2

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