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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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    شناسه: 7921
    حجم: 1590 مگابایت
    مدت زمان: 264 دقیقه
    تاریخ انتشار: 20 اسفند 1401
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