Machine Learning and Artificial Intelligence in Power BI

سرفصل های دوره

Learn how to integrate Machine Learning and AI in Power BI with hands-on projects and professional Power BI instructors

1. Introduction to this course

1.1 Material.7z

1. Course Material.html

2. Introduccion a Power BI

1. Introduccion a Power Bi

2. Descarga y presentacion de Power BI Desktop

3. Importacion de datos

4. Herramientas para analizar la calidad del dato

5. Funciones de pre-procesamiento de datos

3. Artificial intelligence graphics

1. Visual Q&A

2. Configuring the Q&A visual

3. Solution Exercise 1

4. Key Influencers

5. Major Chart Segments Key Influencers

6. Correlation vs Causation

7. Solution Exercise 2

8. Exercise 3 Hierarchical scheme

9. Solution Exercise 3

10. Predictions with time series

11. Solution Exercise 4

12. Detection of anomalies in time series

13. Solution Exercise 5

4. Install Python and sync with Power BI

1. Install Python and synchronization with Power BI

2. Installing Pycaret

3. Jupyter Notebook Fundamentals

5. Advanced analytics

1. How to run python scripts

2. Seaborn Basics

3. Selecting the correct chart type

4. Applied project Data preprocessing with Python

5. Applied project Analysis of numerical variables with Seaborn

6. Machine Learning Fundamentals

1. Introduction to AI

2. Types of Machine Learning Models

3. Phases of training Machine Learning models

4. Main Machine Learning algorithms

7. Deploy models in Power BI

1. Deploy models in Power BI

8. Machine Learning models with Scikit-learn

1. Entrenando un modelo de regresion con Sklearn en Power BI

2. Evaluation and obtaining of metrics of the Sklearn regression model

9. AutoML Fundamentals with Python and Pycaret

1. Introduction to autoML

2. Training and optimization of models with Pycaret

3. Model evaluation and deployment with Pycaret

10. Regression models with Python in Power BI

1. Fundamentals of regression models with Pycaret in Power BI

2. Applied project Development of a regression model of XGBoost

3. Applied project Integration of the XGBoost model in Power BI

4. Applied project Adding model evaluation charts to PowerBI

5. Exercise 1. Regression models in Power BI

6. Solution Exercise 1

11. Classification models with Python in Power BI

1. Fundamentals of classification models with Pycaret in Power BI

2. Evaluation metrics of classification models

3. Applied project Development of a classification model in Power BI

4. Applied project Model load and prediction in Power BI

5. Applied project Applying advanced pre-processing to the data

6. Applied project Evaluation of the classification model in Power BI

7. Exercise 2. Classification models in Power BI

8. Solution Exercise 2

12. Clustering models with Python in Power BI

1. Fundamentals of Clustering Models with Pycaret in Power BI

2. Clustering model evaluation metrics

3. Applied project Development of a clustering model in Power BI

4. Applied project Development of the model in Jupyter and integration in Power BI

5. Exercise 3. Clustering models in Power BI

6. Solution Exercise 3

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تولید کننده: Udemy-Training