🎓
Data Analysis and Model Training Course by Global AI Hub
Syllabus:
Day 1

What is
Data
? 
Multimedia

Structured and Unstructured Data

Data Types

Data Visualization
 What is Visualization?
 Tufte's 6 Principle
 Visualization Types
 Line Plot
 Scatter Plot
 Bar Plot
 Histogram
 Pie Charts
 Heatmap
 Box Plot
 Kartil Nedir? Nasıl Hesaplanır?
 Joint Plot
 KDE(Kernel Density Estimate)

Statistics
 Descriptive Statistics Concepts
 The Concept of Skewness
 Correlation and Correlation Matrix
 The Simpsons Paradox
 Anscombe Quartet
 Data Distribution and Hypothesis Testing

Data Distribution
 Data and Distribution
 Gaussian(Normal) Distribution
 tDistribution
 Degrees of Freedom
 Bernoulli's Distribution
 Exponential Distribution

Application
 Pandas Revision
 Introduction to Data Preprocessing with Pandas
Day 2

Hypothesis Tests
 Basic Hypothesis testing
 P value
 T test
 Z test
 Chisquare (ChiSquare) Test
 Errors in Hypothesis Testing

Data Cleaning
 The 689599.7 Rule and 3 Sigma
 Outlier, Missing and Duplicate Data and their Detection
 ZScore
 Handling missing values
 Null vs NaN
 Pandas Functions for missing values
 Dimensionality Reduction
 PCA (Principal Component Analysis)
 Collinearity (Multiple Linear Connection

Data Transformation
 Data Conversion Techniques
 round
 Scaling
 Label Encoding
 One Hot Encoding
 Stack
 melt
 Shorts
 Feature Engineering
 Data Conversion Techniques

Data Augmentation
 Aggregation Functions

Application
 Data Visualization with Seaborn
 Data Preprocessing with Pandas
Day 3

ML Review
 What is Machine Learning?
 Supervised Learning
 Unsupervised Learning
 Errors That May Be Encountered in Model Training
 Tools Used in Data Analysis and Machine Learning
 EndtoEnd Machine Learning Project Steps

Application
 Training An EndtoEnd ML Model with a Real Dataset
Certification
The course completion is certified.