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1
Data Driven Decision Making (00:00)
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Sesi 1 - DDDM
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2
Data Exploration with Python Pandas (00:00)
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(optional) Review Python
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Sesi 2 - Introduction to Pandas
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Sesi 3 - File Pendukung
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Sesi 3 - Data Cleaning with Pandas
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3
Data Visualization (00:00)
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Sesi 4 - Basic Visualization
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4
Statistical Analysis (00:00)
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Sesi 5 - Descriptive Statistics
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Sesi 6 - Inferential Statistics: Distributions, Confidence Interval, Hypothesis Testing
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Sesi 6 - Inferential Statistics: Resampling, ANOVA
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5
Machine Learning Models (00:00)
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(optional) Introduction to Machine Learning
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Sesi 7 - Regression: Linear and Polynomial Regression
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Sesi 7 - Classification: Logistic Regression
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(tips) Machine Learning Models: Overview
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Sesi 8 - Classification: KNN
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Sesi 8 - Classification: Naive Bayes, Decision Tree, Random Forest, SVG
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6
Final Project (00:00)
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Sesi 9 - Make Your Own Model!
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