What will you learn in Applied Plotting, Charting & Data Representation in Python Course
Understand the principles of effective data visualization—what makes a chart clear or misleading and the heuristics behind visualization design.
Gain hands‑on experience creating charts using Matplotlib, including line plots, scatterplots, bar charts, and overlays.
Explore advanced plotting techniques: histograms, boxplots, heatmaps, subplots, animations, and interactive visualizations
Learn to use Seaborn and Pandas for statistical plotting and clean styling aligned with best practice principles.
Program Overview
Module 1: Principles of Information Visualization
Duration: ~3 hours
Topics: Visualization design principles (Tufte’s data-ink ratio, Cairo’s visualization wheel, truthful charts)
Hands-on: Peer-reviewed exercise critiquing misleading visualizations
Module 2: Basic Charting
Duration: ~7 hours
Topics: Working with real-world CSV data, creating line charts and overlay scatter plots using Matplotlib
Hands-on: Plot weather records and overlay recent outliers for visual comparison
Module 3: Charting Fundamentals (Advanced)
Duration: ~8 hours
Topics: Use of subplots, histograms, boxplots, heatmaps, and animations or interactive elements
Hands-on: Build custom visualizations exploring design and interaction possibilities
Module 4: Applied Visualizations
Duration: ~4 hours
Topics: Applied Seaborn and Pandas plotting, choosing correct charts for storytelling
Hands-on: Final capstone: develop a visualization answering a self-defined question using at least two datasets
Get certificate
Job Outlook
Strong demand for Python visualization skills across data science, analytics, business intelligence, and reporting fields
Presentation-ready charting is valued in industries like finance, healthcare, marketing, and tech
Roles ranging from Data Analyst to BI Developer earn between $65K–$125K+; visualization expertise boosts employability
Visual storytelling skills are increasingly sought after for freelance analytics and dashboard reporting opportunities
Specification: Applied Plotting, Charting & Data Representation in Python
|
