Dedika is a platform for learning by doing: whether it's creating a business proposal, becoming a manicurist, or using a new tool, for example. No matter your goal, the best content on the subject already exists. The problem is, it's often in another language, expensive, scattered around, lacks practice activities, or comes in courses that are too long for busy people. That's why Dedika has its own method: we find this material wherever it is, organize what makes sense for your goal, review it with the help of experts who are available to answer questions, and create hands-on activities so you can learn by doing. You are the most important part of your journey, and no one knows it better than you: choose the content and course length, decide if you'll learn online or offline, and pick your preferred format. It can be video, text, audio, or a summary. Your way, only with what makes sense for you. Here, every moment you dedicate is worth more, and you reach what matters faster.

Our courses include a summary at the end of each chapter, which you can download as a PDF and print.

More than 2 million students worldwide

Present in more than 180 countries

Certificate valid in your country

Home Page

...

Power BI and Artificial Intelligence Course

All courses

Business and Economics

Business Intelligence

Power BI and Artificial Intelligence Course

For all levels

Power BI and Artificial Intelligence Course

Name: Power BI and Artificial Intelligence Course
Price: 222 USD

Master Power BI from the ground up and layer in real artificial intelligence — from native AI visuals and natural language queries to Python-driven machine learning models. This course takes you from installation to enterprise deployment, covering DAX, Power Query, data modeling, and Azure ML integration. If you work with data and want results that actually drive decisions, this is your next move.

Dedika for businesses

What you will learn:

You will build a complete Power BI skill set, starting with data connections and Power Query transformations, then advancing through relational modeling, DAX calculations, and professional report design. You will activate Power BI's built-in AI features, including Copilot, Q&A, and anomaly detection, and extend them with Python and R scripts for clustering, forecasting, and custom visuals. You will connect Power BI to Azure Machine Learning to score datasets with enterprise-grade models. Finally, you will publish and govern reports at scale using row-level security, dataflows, and performance optimization techniques.

How you study in practice Power BI and Artificial Intelligence Course

How you practice Power BI and Artificial Intelligence Course

For companies looking to train their teams

With Dedika for businesses, the course includes exercises and examples tailored to your own business and the way your company needs.

Click here

Course Content

8 Chapters • 40 LessonsDuration between 4 and 360 hours (you decide)

Chapter 1See details

Power BI Foundations and Environment Setup

Lesson 1 • Saving and Publishing Reports
Explains PBIX file management and publishing to Power BI Service. Students understand the full round-trip from desktop authoring to cloud sharing.
Lesson 2 • Navigating the Power BI Interface
Introduces the ribbon, panes, and canvas layout of Power BI Desktop. Students gain the spatial familiarity needed to work efficiently throughout the course.
Lesson 3 • Power BI Ecosystem Overview
Covers Power BI Desktop, Service, and Mobile roles within the platform. Establishes the architectural context needed for all subsequent chapters.
Lesson 4 • Installing and Configuring Power BI Desktop
Guides students through installation, initial settings, and update management. Ensures a consistent, functional environment before any data work begins.
Lesson 5 • Connecting to Data Sources
Demonstrates how to connect to common file, database, and cloud sources. Establishes the data ingestion skills required for every subsequent chapter.

Chapter 2See details

Data Transformation with Power Query

Lesson 1 • Power Query Editor Interface
Introduces the Query Editor layout, Applied Steps pane, and formula bar. Provides the navigational foundation for all transformation tasks in this chapter.
Lesson 2 • Advanced Transformations and M Language
Introduces custom columns, conditional logic, and M formula authoring. Students gain flexibility to handle transformations beyond the graphical interface.
Lesson 3 • Query Performance and Best Practices
Explains query folding, load optimization, and diagnostic tools. Students learn to build efficient pipelines that scale with larger datasets.
Lesson 4 • Cleaning and Shaping Data
Covers removing duplicates, handling nulls, and changing data types. These operations ensure data quality before modeling and visualization.
Lesson 5 • Combining and Appending Queries
Teaches merge and append operations to unify data from multiple sources. Students build consolidated datasets essential for cross-source analysis.

Chapter 3See details

Data Modeling and Relationships

Lesson 1 • Creating and Managing Relationships
Demonstrates how to define, edit, and validate table relationships in Power BI. Correct relationships are the prerequisite for accurate DAX measures.
Lesson 2 • Model Optimization Techniques
Covers column compression, hiding unused fields, and reducing model size. Optimized models load faster and consume fewer resources in Power BI Service.
Lesson 3 • Relational Modeling Concepts
Covers fact tables, dimension tables, and star vs. snowflake schemas. Provides the conceptual framework for all modeling decisions in this chapter.
Lesson 4 • Calculated Columns and Tables
Introduces DAX-based calculated columns and generated tables within the model. Students extend their schema without modifying source data.
Lesson 5 • Role-Playing Dimensions and Many-to-Many
Addresses advanced relationship patterns including role-playing dimensions and many-to-many scenarios. Students handle complex real-world schemas confidently.

Chapter 4See details

DAX Language for Analytics

Lesson 1 • Iterators and Table Functions
Covers SUMX, AVERAGEX, FILTER, and RELATED for row-by-row calculations. Students write measures that iterate over tables for complex business logic.
Lesson 2 • Advanced DAX Patterns and Optimization
Introduces variables, DIVIDE, error handling, and DAX Studio for performance tuning. Students write efficient, maintainable measures for production reports.
Lesson 3 • DAX Fundamentals and Syntax
Introduces DAX operators, data types, and the difference between measures and columns. Establishes the syntactic foundation for all DAX work in this chapter.
Lesson 4 • Filter Context and Row Context
Explains how evaluation context shapes DAX results and how CALCULATE modifies it. Mastering context is the key to writing correct, predictable measures.
Lesson 5 • Time Intelligence Calculations
Teaches TOTALYTD, SAMEPERIODLASTYEAR, DATEADD, and related functions. Students build period-over-period comparisons essential for business reporting.

Chapter 5See details

Data Visualization and Report Design

Lesson 1 • Core Visualization Types
Covers bar, line, pie, scatter, and map visuals with appropriate use cases. Students select the right chart type for each analytical question.
Lesson 2 • Report Layout and Design Principles
Applies visual hierarchy, color theory, and whitespace to report layouts. Well-designed reports reduce cognitive load and accelerate decision-making.
Lesson 3 • Tooltips, Bookmarks, and Drill-Through
Covers report page tooltips, bookmark navigation, and drill-through pages. These features create guided, story-driven analytical experiences.
Lesson 4 • Advanced Visuals and Custom Visuals
Introduces decomposition trees, key influencers, and AppSource custom visuals. Students extend Power BI's native capabilities for specialized analytical needs.
Lesson 5 • Slicers, Filters, and Interactions
Demonstrates slicers, filter panes, and cross-visual interaction settings. Students build interactive reports that let users explore data independently.

Chapter 6See details

AI Features Built into Power BI

Lesson 1 • Key Influencers and Decomposition Tree
Explores AI-powered root-cause analysis using Key Influencers and Decomposition Tree visuals. Students identify drivers of metrics without manual segmentation.
Lesson 2 • Smart Narratives and Anomaly Detection
Covers auto-generated text summaries and anomaly detection on time-series visuals. Students add AI-written context and alerts to reports automatically.
Lesson 3 • Q&A Natural Language Queries
Teaches the Q&A visual, synonym configuration, and question suggestions. Users can query data in plain English, reducing reliance on pre-built visuals.
Lesson 4 • AI Insights in Power Query
Demonstrates Text Analytics, Vision, and Azure ML model invocation from Power Query. Students enrich datasets with AI-scored columns during the ETL phase.
Lesson 5 • Copilot for Power BI Overview
Introduces Microsoft Copilot's report generation, measure suggestion, and summary features. Students understand current capabilities and appropriate use cases.

Chapter 7See details

Integrating Python and R for Advanced AI

Lesson 1 • Python and R Custom Visuals
Shows how to render matplotlib, seaborn, and ggplot2 charts as Power BI visuals. Students create statistical plots not available in the native visual library.
Lesson 2 • Python Scripts for Data Transformation
Demonstrates using Python in Power Query to clean, reshape, and enrich data. Students apply pandas and NumPy operations unavailable in native Power Query.
Lesson 3 • Configuring Python and R in Power BI
Covers environment setup, library installation, and scripting options in Power BI Desktop. A correctly configured environment is the prerequisite for all scripted AI work.
Lesson 4 • Machine Learning Models in Power BI
Teaches training and scoring scikit-learn models within Power BI Python scripts. Students add predictive columns to their data model using ML pipelines.
Lesson 5 • Clustering and Forecasting with Scripts
Applies K-means clustering and time-series forecasting models inside Power BI. Students deliver segmentation and predictive analytics directly within reports.

Chapter 8See details

Publishing, Governance, and AI Strategy

Lesson 1 • AI Ethics, Governance, and Roadmap Planning
Addresses responsible AI principles, bias detection, and building an AI analytics roadmap. Students align technical capabilities with ethical standards and business goals.
Lesson 2 • Dataflows and Certified Datasets
Introduces Power BI dataflows for reusable ETL and dataset certification workflows. Students build a governed, single-source-of-truth data layer.
Lesson 3 • Scheduled Refresh and Gateway Setup
Configures on-premises data gateways and scheduled dataset refresh in Power BI Service. Students ensure reports always reflect current data without manual intervention.
Lesson 4 • Power BI Service and Workspaces
Covers workspace creation, app publishing, and content organization in Power BI Service. Students manage report distribution across teams and departments.
Lesson 5 • Row-Level Security and Data Protection
Implements static and dynamic row-level security and sensitivity labels. Students protect sensitive data while maintaining broad report accessibility.

Certification

Your valid completion certificate

This course is for you:

Business analyst: wants to replace slow manual reporting with automated dashboards.
Data enthusiast: curious about AI but unsure where to start practically.
Finance professional: needs dynamic forecasting tools beyond traditional spreadsheet models.
Career changer: transitioning into data roles and building a competitive technical portfolio.
IT generalist: supporting BI tools and wanting deeper hands-on analytical expertise.
Operations manager: seeking data-driven visibility into team performance and business trends.

What our students say

Your classes are perfect. I purchased the one-year package and finally have the opportunity to follow various topics of interest without needing to switch platforms... I thank you for everything you do, I've already recommended you to other people...