Machine Learning and Artificial Intelligence in Power BI
- Offered byUDEMY
Machine Learning and Artificial Intelligence in Power BI at UDEMY Overview
Duration | 5 hours |
Total fee | ₹449 |
Mode of learning | Online |
Credential | Certificate |
Machine Learning and Artificial Intelligence in Power BI at UDEMY Highlights
- 30-Day Money-Back Guarantee
- Certificate of completion
- Full lifetime access
- Learn from 1 downloadable resource and 1 article
Machine Learning and Artificial Intelligence in Power BI at UDEMY Course details
- Machine Learning in Power Bi
- Artificial intelligence in Power BI
- Advanced analytics
- Data analytics
- If you're looking for a hands-on, comprehensive, and advanced course to learn Machine Learning and Artificial Intelligence in Power BI, you've come to the right place. Power BI has become one of the best Business Intelligence tools and one of the most widespread data visualization tool among data professionals. In addition, with the integration of Python and Machine Learning models, it can be used for advanced and predictive analytics. In this course, we will teach you to use Power BI artificial intelligence features and to integrate Python Machine Learning models in Power BI. You will also learn the fundamentals of Machine Learning and how to develop models, with autoML and low code machine learning. To do this, we'll guide you through Power BI functionalities, sharing clear explanations and helpful proffesional tips. We will follow a constant and systematic progression, dividing the course into those KEY OBJECTIVES: Power BI fundamentals. Here we are going to learn the fundamentals of Power BI: connecting a data source, the program interface, adding filters, and more. Artificial intelligence charts like Q&A, key influencing factors or decomposition trees. Advanced analytics Machine Learning Fundamentals Python installation and synchronization with Power BI AutoML Fundamentals with Python and Pycaret Integration of models in Power BI Regression models with Python in Power BI Classification models with Python in Power BI Clustering models with Python in Power BI By the end of the project, you will not only have applied advanced analytics and machine learning techniques from scratch in Power BI dashboards, but also you will have gained the knowledge and confidence to apply those concepts to your own projects. For those who want to learn quickly with hands-on projects, join today and get immediate and lifetime access to the following: Advanced Data Analytics in Power BI eBook in PDFDownloadable Power BI project files practical exercises and quizzesPower BI resources like: Cheatsheets and summaries1-on-1 expert supportCourse questions and answers forumSee you there!
Machine Learning and Artificial Intelligence in Power BI at UDEMY Curriculum
Introduction to this course
How to get the most out of the course
Course Material
Introduction to Power BI
Introduction to Power Bi
Download and present Power BI Desktop
Data Import
Tools to analyze data quality
Data pre-processing functions
Artificial intelligence graphics
Visual Q&A
Configuring the Q&A visual
Solution Exercise 1
Key Influencers
Major Chart Segments Key Influencers
Correlation vs Causation
Solution Exercise 2
Exercise 3 Hierarchical scheme
Solution Exercise 3
Predictions with time series
Solution Exercise 4
Detection of anomalies in time series
Solution Exercise 5
Install Python and sync with Power BI
Install Python and synchronization with Power BI
Installing Pycaret
Jupyter Notebook Fundamentals
Advanced analytics
How to run python scripts
Seaborn Basics
Selecting the correct chart type
Applied project_Data preprocessing with Python
Applied project_Analysis of numerical variables with Seaborn
Machine Learning Fundamentals
Introduction to AI
Types of Machine Learning Models
Phases of training Machine Learning models
Main Machine Learning algorithms
Deploy models in Power BI
Deploy models in Power BI
Machine Learning models with Scikit-learn
Entrenando un modelo de regresión con Sklearn en Power BI
Evaluation and obtaining of metrics of the Sklearn regression model
AutoML Fundamentals with Python and Pycaret
Introduction to autoML
Training and optimization of models with Pycaret
Model evaluation and deployment with Pycaret
Regression models with Python in Power BI
Fundamentals of regression models with Pycaret in Power BI
Applied project_Development of a regression model of XGBoost
Applied project_Integration of the XGBoost model in Power BI
Applied project_Adding model evaluation charts to PowerBI
Exercise 1. Regression models in Power BI
Solution Exercise 1
Classification models with Python in Power BI
Fundamentals of classification models with Pycaret in Power BI
Evaluation metrics of classification models
Applied project_Development of a classification model in Power BI
Applied project_Model load and prediction in Power BI
Applied project_Applying advanced pre-processing to the data
Applied project_Evaluation of the classification model in Power BI
Exercise 2. Classification models in Power BI
Solution_Exercise 2
Clustering models with Python in Power BI
Fundamentals of Clustering Models with Pycaret in Power BI
Clustering model evaluation metrics
Applied project_Development of a clustering model in Power BI
Applied project_Development of the model in Jupyter and integration in Power BI
Exercise 3. Clustering models in Power BI
Solution Exercise 3
Machine Learning and Artificial Intelligence in Power BI at UDEMY Faculty details
Machine Learning and Artificial Intelligence in Power BI at UDEMY Entry Requirements
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- Not mentioned
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