Machine Learning and Artificial Intelligence in Power BI

Learn how to integrate Machine Learning and AI in Power BI with hands-on projects and professional Power BI instructors
Machine Learning and Artificial Intelligence in Power BI
File Size :
1.53 GB
Total length :
4h 39m



Data Bootcamp


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Machine Learning and Artificial Intelligence in Power BI

What you’ll learn

Machine Learning in Power Bi
Artificial intelligence in Power BI
Advanced analytics
Data analytics

Machine Learning and Artificial Intelligence in Power BI




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 analyticsMachine Learning FundamentalsPython installation and synchronization with Power BIAutoML Fundamentals with Python and PycaretIntegration of models in Power BIRegression models with Python in Power BIClassification models with Python in Power BIClustering models with Python in Power BIBy 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 filesPractical exercises and quizzesPower BI resources like: Cheatsheets and summaries1-on-1 expert supportCourse questions and answers forumSee you there!


Section 1: Introduction to this course

Lecture 1 How to get the most out of the course

Lecture 2 Course Material

Section 2: Introducción a Power BI

Lecture 3 Introducción a Power Bi

Lecture 4 Descarga y presentación de Power BI Desktop

Lecture 5 Importación de datos

Lecture 6 Herramientas para analizar la calidad del dato

Lecture 7 Funciones de pre-procesamiento de datos

Section 3: Artificial intelligence graphics

Lecture 8 Visual Q&A

Lecture 9 Configuring the Q&A visual

Lecture 10 Solution Exercise 1

Lecture 11 Key Influencers

Lecture 12 Major Chart Segments Key Influencers

Lecture 13 Correlation vs Causation

Lecture 14 Solution Exercise 2

Lecture 15 Exercise 3 Hierarchical scheme

Lecture 16 Solution Exercise 3

Lecture 17 Predictions with time series

Lecture 18 Solution Exercise 4

Lecture 19 Detection of anomalies in time series

Lecture 20 Solution Exercise 5

Section 4: Install Python and sync with Power BI

Lecture 21 Install Python and synchronization with Power BI

Lecture 22 Installing Pycaret

Lecture 23 Jupyter Notebook Fundamentals

Section 5: Advanced analytics

Lecture 24 How to run python scripts

Lecture 25 Seaborn Basics

Lecture 26 Selecting the correct chart type

Lecture 27 Applied project_Data preprocessing with Python

Lecture 28 Applied project_Analysis of numerical variables with Seaborn

Section 6: Machine Learning Fundamentals

Lecture 29 Introduction to AI

Lecture 30 Types of Machine Learning Models

Lecture 31 Phases of training Machine Learning models

Lecture 32 Main Machine Learning algorithms

Section 7: Deploy models in Power BI

Lecture 33 Deploy models in Power BI

Section 8: Machine Learning models with Scikit-learn

Lecture 34 Entrenando un modelo de regresión con Sklearn en Power BI

Lecture 35 Evaluation and obtaining of metrics of the Sklearn regression model

Section 9: AutoML Fundamentals with Python and Pycaret

Lecture 36 Introduction to autoML

Lecture 37 Training and optimization of models with Pycaret

Lecture 38 Model evaluation and deployment with Pycaret

Section 10: Regression models with Python in Power BI

Lecture 39 Fundamentals of regression models with Pycaret in Power BI

Lecture 40 Applied project_Development of a regression model of XGBoost

Lecture 41 Applied project_Integration of the XGBoost model in Power BI

Lecture 42 Applied project_Adding model evaluation charts to PowerBI

Lecture 43 Exercise 1. Regression models in Power BI

Lecture 44 Solution Exercise 1

Section 11: Classification models with Python in Power BI

Lecture 45 Fundamentals of classification models with Pycaret in Power BI

Lecture 46 Evaluation metrics of classification models

Lecture 47 Applied project_Development of a classification model in Power BI

Lecture 48 Applied project_Model load and prediction in Power BI

Lecture 49 Applied project_Applying advanced pre-processing to the data

Lecture 50 Applied project_Evaluation of the classification model in Power BI

Lecture 51 Exercise 2. Classification models in Power BI

Lecture 52 Solution_Exercise 2

Section 12: Clustering models with Python in Power BI

Lecture 53 Fundamentals of Clustering Models with Pycaret in Power BI

Lecture 54 Clustering model evaluation metrics

Lecture 55 Applied project_Development of a clustering model in Power BI

Lecture 56 Applied project_Development of the model in Jupyter and integration in Power BI

Lecture 57 Exercise 3. Clustering models in Power BI

Lecture 58 Solution Exercise 3

Anyone looking for a hands-on, project-based introduction to machine learning and advanced analytics with Power BI,Data analysts and data scientists hoping to develop advanced analytics skills,Aspiring data professionals looking to integrate advanced analytics capabilities into their Power BI dashboards,Students who want a comprehensive and practical training approach,Anyone who wants to develop their career as a data analyst, data scientist or business intelligence developer

Course Information:

Udemy | English | 4h 39m | 1.53 GB
Created by: Data Bootcamp

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