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Masterclass details
Prerequisites
• A Windows 10/11 computer capable of running Power BI Desktop.
• Microsoft Power BI Desktop installed before the first practical session.
• Basic data literacy: understanding tables, rows, columns and simple Excel concepts.
• A work or school email is recommended for later exposure to Power BI Service in the full Program.
About this masterclass
Program Duration | 1 Month | 8 Practical Live Sessions |
Target Audience | College / university students |
Entry Level | Beginner — no prior Power BI experience required |
Delivery | Tuesday & Thursday live sessions | Practical, hands-on learning |
Training Objective
To give learners a practical first experience of the Power BI workflow: connecting to data, transforming messy data, creating simple relationships and DAX measures, building interactive visuals, and presenting insights. The program is intentionally designed as a discovery experience rather than a compressed version of the full 3-month course.
Why It Matters
1. From raw data to insight: Learners experience how Power BI can turn a familiar Excel file into an interactive report.
2. Beyond manual reporting: Power Query introduces the idea of cleaning data once and reusing the transformation steps.
3. Make Power BI think: Basic relationships and DAX show how a model can answer questions dynamically.
4. Storytelling, not just charts: Learners practice choosing visuals and arranging a dashboard for a specific audience.
5. A clear next step: The month ends with a mini-capstone that demonstrates what can be achieved with a deeper 3-month Program.
TRAINING FRAMEWORK
Day | Date | Objectives | Delivery |
Module 1: Discover Power BI & Connect to Data | |||
Tuesday |
6/10/2026 | Lesson 1: Introduction to BI & Power BI • Introduction to Business Intelligence and why organizations use data to make decisions. • Power BI ecosystem: Desktop vs. Service. • Navigating Report, Data and Model views. • Opening a dataset and creating a first simple visual. Hands-on Lab: Turn a raw college/student Excel dataset into a simple interactive report. |
Online (Live Session) |
Thursday |
8/10/2026 | Lesson 2: Connecting to Real Data • Connecting to Excel and CSV files. • Understanding tables, rows, columns and data types. • Raw data vs. analysis-ready data. • Inspecting a dataset before analysis. Mini Challenge: Find three useful insights from a college/student dataset without relying on manual Excel formulas. |
Online (Live Session) |
Module 2: From Messy Data to Useful Data | |||
Tuesday |
13/10/2026 | Lesson 3: Power Query Fundamentals • Introduction to the Power Query interface and Applied Steps. • Setting correct data types and headers. • Renaming fields and removing unnecessary rows/columns. • Removing duplicates and handling basic null values. Challenge: Clean intentionally messy student data without changing the original source file. |
Online (Live Session) |
Thursday |
15/10/2026 | Lesson 4: Data Transformation • Split, merge and replace values. • Conditional columns and grouping/aggregation. • Introduction to pivoting and unpivoting. • Understanding wide vs. tall data for analysis. Mini-Project: Convert a manually formatted college report into an analysis-ready dataset. |
Online (Live Session) |
Module 3: Make Power BI Think | |||
Tuesday |
20/10/2026 | Lesson 5: Introduction to Data Modelling • Understanding tables and relationships. • Primary keys and foreign keys. • Introduction to fact and dimension tables. • Creating a simple one-to-many relationship. • Seeing how filters move between related tables. Practical Lab: Build a simple Student–Enrollment–Course–Date model. |
Online (Live Session) |
Thursday |
22/10/2026 | Lesson 6: Your First DAX Measures • Measures vs. calculated columns — when each is appropriate. • Basic measures using SUM, AVERAGE, COUNT and DISTINCTCOUNT. • DIVIDE and simple IF logic. • Building introductory KPIs. Challenge: Create Total Students, Average Score, Total Fees, Number of Courses, Pass Rate and Attendance Rate. |
Online (Live Session) |
Module 4: Build Your First Professional Dashboard | |||
Tuesday |
9/10/2026 | Lesson 7: Interactive Visualizations & Dashboard Design | Online (Live |
Day | Date | Objectives | Delivery |
• Cards, bar/column charts, line charts, tables and matrices. • Slicers, visual interactions and basic filters. • Introduction to drill-down. • Choosing appropriate visuals for different questions. • Layout, alignment, white space and visual hierarchy. Design Challenge: Redesign a poor dashboard for a college principal or administrator. | Session) | ||
Thursday |
27/10/2026 | Lesson 8: Mini Capstone & Presentation • Connect and clean the dataset. • Create a simple model and introductory DAX measures. • Build an interactive dashboard with slicers. • Identify and communicate three important findings. • Present the final dashboard and receive trainer feedback. Final Project: College Performance Intelligence Dashboard. |
Online (Live Session) |
WEEKLY LEARNING JOURNEY & OUTCOMES
Week 1 — Discover Power BI
Sessions: Tuesday: Power BI & BI Foundations Thursday: Connecting to Data
Weekly Outcome: Learners can open Power BI, understand its basic environment, connect to familiar data and produce their first interactive visuals.
Interest Hook: Hook: “I can turn an Excel file into something interactive.”
Week 2 — Transform Data
Sessions: Tuesday: Power Query Fundamentals Thursday: Data Transformation
Weekly Outcome: Learners can clean and reshape a messy dataset and understand why repeatable transformations are better than manual editing.
Interest Hook: Hook: “I can make messy data usable.”
Week 3 — Build Intelligence
Sessions: Tuesday: Data Modelling Thursday: Introduction to DAX
Weekly Outcome: Learners can create a simple relationship between tables and build measures that respond dynamically to filters.
Interest Hook: Hook: “I can make Power BI answer questions.”
Week 4 — Tell the Story
Sessions: Tuesday: Visualization & Dashboard Design Thursday: Mini Capstone & Presentation
Weekly Outcome: Learners can combine the skills into a small, audience-focused dashboard and communicate meaningful findings.
Interest Hook: Hook: “I can build something that looks professional.”
FINAL MINI-CAPSTONE: COLLEGE PERFORMANCE INTELLIGENCE DASHBOARD
Suggested dataset areas: students, courses, attendance, academic performance, fees, gender, county, enrollment and completion.
• KPIs: Total Students, Average Performance, Attendance Rate and Completion/Pass Rate.
• Analysis: at least one comparison, one trend, one distribution and one detailed table/matrix.
• Interaction: at least two slicers with working visual interactions.
• Insight section: three important findings written in plain language.
• Presentation: explain what the dashboard shows, what the most important findings are, and what a decision maker should notice.