À propos de ce cours

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Approx. 10 heures pour terminer
Anglais
Sous-titres : Anglais, Coréen

Compétences que vous acquerrez

Regression AnalysisData CleansingPredictive ModellingExploratory Data Analysis
Certificat partageable
Obtenez un Certificat lorsque vous terminez
100 % en ligne
Commencez dès maintenant et apprenez aux horaires qui vous conviennent.
Dates limites flexibles
Réinitialisez les dates limites selon votre disponibilité.
Approx. 10 heures pour terminer
Anglais
Sous-titres : Anglais, Coréen

Enseignant

Offert par

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Université du Colorado à Boulder

Programme du cours : ce que vous apprendrez dans ce cours

Évaluation du contenuThumbs Up58%(1,084 notes)Info
Semaine
1

Semaine 1

4 heures pour terminer

Exploratory Data Analysis and Visualizations

4 heures pour terminer
8 vidéos (Total 38 min), 1 lecture, 3 quiz
8 vidéos
0. Introduction to the Module. Why Exploratory Data Analysis is Important3 min
1. Data Cleanup and Transformation4 min
2. Dealing With Missing Values6 min
3. Dealing with Outliers3 min
4. Adding and Removing Variables4 min
5. Common Graphs7 min
6. What is Good Data Visualization?4 min
1 lecture
Register for Analytic Solver Platform for Education (ASPE)10 min
2 exercices pour s'entraîner
Week 1 Quiz48 min
Week 1 Application Assignment 1 (optional): Data Cleanup6 min
Semaine
2

Semaine 2

2 heures pour terminer

Predicting a Continuous Variable

2 heures pour terminer
8 vidéos (Total 41 min)
8 vidéos
1. Introduction to Linear Regression8 min
2. Assessing Predictive Accuracy Using Cross-Validation5 min
3. Multiple Regression4 min
4. Improving Model Fit3 min
5. Model Selection3 min
6. Challenges of Predictive Modeling5 min
7. How to Build a Model using XLMiner8 min
2 exercices pour s'entraîner
Week 2 Quiz18 min
Week 2 Application Assignment40 min
Semaine
3

Semaine 3

1 heure pour terminer

Predicting a Binary Outcome

1 heure pour terminer
8 vidéos (Total 33 min)
8 vidéos
1. Introduction to Logistic Regression4 min
2. Building Logistic Regression Model6 min
3. Multiple Logistic Regression3 min
4. Cross Validation and Confusion Matrix5 min
5. Cost Sensitive Classification2 min
6. Comparing Models Independent of Costs and Cutoffs3 min
7. Building Logistic Regression Models using XLMiner6 min
2 exercices pour s'entraîner
Week 3 Quiz14 min
Week 3 Application Assignment26 min
Semaine
4

Semaine 4

4 heures pour terminer

Trees and Other Predictive Models

4 heures pour terminer
8 vidéos (Total 32 min)
8 vidéos
1. Introduction to Trees2 min
2. Classification Trees5 min
3. Regression Trees2 min
4. Bagging, Boosting, Random Forest4 min
5. Building Trees with XLMiner5 min
6. Neural Networks5 min
7. Building Neural Networks using XLMiner4 min
3 exercices pour s'entraîner
Week 4 Quiz12 min
Week 4 Application Assignment10 min
Final Course Assignment Quiz40 min

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