Duration: Three Days
Course Overview:
This course is meant to equip experienced Python users with the applied data analytics skills and to integrate Python scripts directly into Power BI reports for advanced analysis, automation, and visualization. This course will also equip experienced Python users with the applied data analytics skills needed to prepare for the PCED-30-02 certification.
Participants leave able to:
- Perform complete data analytics workflows in Python (collect → clean → analyze → visualize)
- Embed Python analytics directly inside Power BI visuals
- Communicate insights effectively with business stakeholders
Recommended Prerequisites:
Design and Manage Analytics Solutions using Power BI
Introduction to Programming with Python or Certified Entry-Level Python Programmer (PCEP™ Prep Course)
Advanced Programming Techniques with Python or Certified Associate in Python Programming (PCAP™ Prep Course)
Learning Outcomes:
After completing this course, participants will be able to:
- Use pandas, numpy, and visualization libraries to analyze real-world datasets
- Apply statistical techniques and exploratory data analysis (EDA)
- Connect Power BI to Python for custom transformations and visuals
- Interpret and communicate insights using Power BI dashboards and Python scripts
Objectives:
Data Analytics Foundations with Python
- Recap: the data analytics process (collection → cleaning → analysis → visualization)
- The role of Python in business analytics pipelines
- Working with datasets using pandas
- Importing, cleaning, transforming data
- Handling missing values and outliers
- Summarizing data with descriptive statistics
Analysis, Visualization & Applied Problem-Solving
- Using pandas for grouping, aggregating, and joining datasets
- Calculating KPIs (growth %, contribution %, variance)
- Exploring data relationships (correlations, outliers)
- Visual analytics in Python: matplotlib and seaborn
- Intro to data storytelling — turning findings into visual narratives
Power BI + Python Integration
- Review: Power BI’s role in data transformation and visualization
- Setting up Python scripting in Power BI
- Using Python for Data Transformation in Power Query
- Clean and enrich data before loading into the model
- Using Python for Custom Visuals in Power BI
- Build a correlation heatmap
- Create boxplots or histograms with Python
- Compare Python visuals with native visuals
- Exporting data from Power BI → Python (and vice versa)
