Master Power BI Course: Data Cleaning, DAX, Dashboards & AI
This Microsoft Power BI Course will help you master data cleaning, DAX, dashboards, and AI visuals with hands-on projects.
Original price was: R$1,086.24.R$537.69Current price is: R$537.69.
12,820 already enrolled
15 modules
Gain insight into a topic and learn the fundamentals.
4.5 ⭐⭐⭐⭐⭐
(1058 reviews)
Hands-on Projects
Capstone + industry-based case studies
Career-Oriented
Boosts profile for analytics & BI jobs
Gain practical Power BI skills to turn data into insights. Learn data cleaning, modeling, DAX, visualizations, and real-world dashboards. Includes hands-on projects and a capstone for your portfolio. Earn a shareable certificate upon completion.
What You’ll Learn
- Understand Business Intelligence (BI) and Power BI’s key features.
- Install and navigate Power BI with confidence.
- Import, clean, and format datasets using Power Query and AI tools.
- Master data modeling with relationships, primary/foreign keys, and DAX.
- Create visualizations like charts, maps, KPIs, and AI-driven visuals.
- Hands-on Microsoft Power BI training with DAX, data modeling, AI visuals, and interactive dashboard design.
- Build and organize interactive dashboards for desktop and mobile.
- Apply Power BI to real-world project management (e.g., risk dashboards) and leadership (e.g., ESG insights).
- Gain skills to clean, transform, and model datasets in Power BI, mastering visualizations and advanced BI techniques.
Who This Course Is For
- This Power BI course is designed for beginners in data analytics, professionals in project management, and anyone seeking Power BI certification to boost their BI career.
- Professionals in project management, leadership, or e-commerce seeking data-driven skills.
- Job seekers aiming for better salaries in BI (Power BI skills can boost pay by 20-30%).
- Not for advanced users already proficient in DAX and AI visuals.
Requirements
- Basic computer skills.
- A Windows or Mac system for Power BI installation.
- No prior BI experience needed; the course starts from basics.
This course includes
- 17 hours on-demand video
- 9 articles
- 9 downloadable resources
- Access on mobile and TV
- Closed captions
- Certificate of completion
Course Syllabus
1. Introduction
2. Introduction to Power BI
2.1 Module Introduction
2.2 What is BI
2.3 What Are the Various BI Tools Used?
2.4 Key Features Of Power BI
3. Why Power BI?
3.1 Module Introduction
3.2 Benefits of Power BI
3.3 Industries and Companies Requiring Power BI Professionals
3.4 How Power BI Helps You Get a Better Job and Salary
3.5 Power BI Compared to Other BI Tools
3.6 Future Scope Of Power BI
4. Power BI Installation
4.1 Module Introduction
4.2 Types of Power BI Licenses and When They Are Used
4.3 Checking the Power BI Version According to System Configuration
4.4 Installing Power BI
5. Going through the Interface of Power Bi
5.1 Module Introduction
5.2 Introduction to Home Page
5.3 Home Ribbon (Top Panel)
5.4 Data Panel (Left Panel)
5.5 Bottom Panel
5.6 Visualization Panel(Right Panel)
5.7 Power Query Editor
6. Downloading & Importing The Dataset
6.1 Module Introduction
6.2 Sources And Types Of Dataset
6.3 Finding a Good Dataset for Power BI and Downloading It
6.4 Importing the Dataset to Power BI
6.5 Studying the Dataset and the Fields Present in the Dataset
6.6 AI For Dataset
6.6.1. AI – To Find The Dataset
6.6.2. AI – To Create A Sample Dataset
6.6.3. AI – To Create A Dataset With Errors
7. Cleaning & Formatting The Data
7.1 Module Introduction
7.2 What Is the Need for Cleaning the Dataset
7.3 Types of Anomalies Detected in a Dataset Before Cleaning
7.4 How to Clean the Dataset
7.4.1 How to clean the dataset – Introduction To The Lesson
7.4.2 How to clean the dataset – Exploring The Home Tab And Removing The Extra Rows
7.4.3 How to clean the dataset – Exploring The Transform Tab
7.4.4 How to clean the dataset – Exploring The Add Column Tab
7.4.5 How to clean the dataset – Exploring The View Tab
7.4.6 AI – Cleaning The Dataset
8. Data Modelling & Relationships
8.1 Module Introduction
8.2 Primary And Foreign Key
8.3 Types Of Relationship
8.4 Edit Relationships
8.5 Cross Filter Relation
8.6 Active And Inactive Relationship
8.7 AI – Data Modelling And Relationships
9. Data Analysis Expressions
9.1 Module Introduction
9.2 How To Create a New Column
9.3 What Are The Measures And How To Create New Measures
9.4 Difference Between Calculated Columns And Measures
9.5 Functions In DAX
9.6 AI – DAX Operations
10. Data Visualization
10.1 Module Introduction
10.2 Cards and Multi-Row Cards
10.3 Slicers
10.4 Stacked Bar Chart
10.5 Line And Stacked Column Chart
10.6 Pie Chart
10.7 Map And Tree Map
10.8 Line Chart
10.9 KPI
10.10 AI – Creating Visuals
11. Creating & Organising the dashboard
11.1 Module Introduction
11.2 What Is A Dashboard
11.3 Uses Of Dashboard
11.4 How To Create And Organise Dashboard
11.4.1. Dashboard On Desktop
11.4.2. Dashboard On Mobile
11.5 Importing And Exporting Templates
12. AI Visuals
12.1 Module Introduction
12.2 Question And Answer Visual
12.3 Key Influencers
12.4 Decomposition Tree
12.5 Smart Narrative Visual
13. Project Management Use Cases
13.1 Module Introduction
13.2 Executive Project Status Dashboard
13.3 Amazon E-commerce Dataset Portfolio
13.4 Resource Utilization & Timesheet Compliance
13.5 Budget vs Actual Cost Monitoring
13.6 Forecasting Delays & Timeline Slippage
13.7 Risk & Issue Management Dashboard
13.8 Change Request Impact Analysis
13.9 Agile/Sprint Tracking Reports
13.10 Team Performance & Task Completion Metrics
13.11 Stakeholder & Customer Satisfaction Monitoring
13.12 Lessons Learned – Agile Scrum
14. Leadership Use Cases
14.1 Module Introduction
14.2 Leadership Performance Dashboard
14.3 Decision-Making Tracker
14.4 Strategic Goal Alignment Tracker
14.5 Crisis Management Insights Dashboard
14.6 Revenue Leadership Insights
14.7 Cost Optimization Simulator
14.8 Employee Engagement Monitor
14.9 Diversity and Inclusion Dashboard
14.10 Cross-Functional Collaboration Index
14.11 Leadership Decision Justification Dashboard
14.12 Innovation Pipeline Overview
14.13 Board Meeting Dashboard Pack
14.14 Global Operations Overview
14.15 ESG (Environmental, Social, Governance) Leadership Insights
15. Capstone Project
16 Final Thoughts & What’s Next
Benefits
The global business intelligence market size is expected to grow from $ 33.34 billion in 2024 to $ 61.86 billion by 2029, growing at a CAGR of 13.16% during the forecast period. Over the last decade, BI and analytics tools have experienced a substantial surge in market share.
With BI tools like Power BI in high demand, this course prepares you for roles such as Data Analyst, BI Engineer, and Analytics Manager. Companies like Microsoft, Amazon, Meta, and NVIDIA actively hire professionals with Power BI certification and skills.
Annual Salary
₹500K
Min
₹770K
Average
₹1100K
Max
Hiring Companies
Annual Salary
₹600K
Min
₹1000K
Average
₹2200K
Max
Hiring Companies
Annual Salary
₹1700K
Min
₹2500K
Average
₹3600K
Max
Hiring Companies
Course completion Certificate
Then Microsoft Power BI is the right tool for you and this comprehensive course will teach you everything you need to know to use Power BI.
This hands on (Beginner to Intermediate) course will prepare you to start your data analytics career and also will prepare you to Successfully implement Power BI in your organization.
Reviews
This course is both an incredible education tool and is structured superbly for future referencing as your experience in Power Query and Power BI develops. Its breadth and depth is sufficiently comprehensive to make a big impact at pace in your career. Highly recommended.
Alax Jane
I had a truly great experience learning the complete Power BI course. I gained valuable insights and discovered many new concepts. I will definitely recommend this course to others and look forward to learning more from you and your team. Thank you once again!
Jennifer Jose
I really enjoyed this course — it was fun, engaging, and surprisingly eye-opening! What stood out most to me was how many different ways there are to solve the same problem in Power BI. It’s not just about following steps, but really understanding how to think like a data analyst.
Juan Sanchez
