🎓 Data Analysis and Model Training Course by Global AI Hub
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What is
Data
? -
Multimedia
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Structured and Unstructured Data
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Data Types
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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)
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Statistics
- Descriptive Statistics Concepts
- The Concept of Skewness
- Correlation and Correlation Matrix
- The Simpsons Paradox
- Anscombe Quartet
- Data Distribution and Hypothesis Testing
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Data Distribution
- Data and Distribution
- Gaussian(Normal) Distribution
- t-Distribution
- Degrees of Freedom
- Bernoulli's Distribution
- Exponential Distribution
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Application
- Pandas Revision
- Introduction to Data Preprocessing with Pandas
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Hypothesis Tests
- Basic Hypothesis testing
- P value
- T test
- Z test
- Chi-square (Chi-Square) Test
- Errors in Hypothesis Testing
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Data Cleaning
- The 68-95-99.7 Rule and 3 Sigma
- Outlier, Missing and Duplicate Data and their Detection
- Z-Score
- Handling missing values
- Null vs NaN
- Pandas Functions for missing values
- Dimensionality Reduction
- PCA (Principal Component Analysis)
- Collinearity (Multiple Linear Connection
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Data Transformation
- Data Conversion Techniques
- round
- Scaling
- Label Encoding
- One Hot Encoding
- Stack
- melt
- Shorts
- Feature Engineering
- Data Conversion Techniques
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Data Augmentation
- Aggregation Functions
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Application
- Data Visualization with Seaborn
- Data Preprocessing with Pandas
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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
- End-to-End Machine Learning Project Steps
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Application
- Training An End-to-End ML Model with a Real Dataset
The course completion is certified.