AI Udaan syllabus · Week 4–5
Data Visualization with Matplotlib for AI Projects
Before training a model, you need to see your data. AI Udaan teaches Matplotlib line charts, bar charts, pie charts, histograms, scatter plots, and box plots — tied to outlier detection and feature understanding.
Visualization in the ML workflow
Histograms reveal distribution skew. Scatter plots show correlations. Box plots highlight outliers you may remove or cap. These visuals appear in assignments and portfolio projects throughout the bootcamp.
Syllabus coverage
Week 4 focuses on Matplotlib anatomy and chart types. Week 5 connects box plots to NumPy and statistical outlier methods (IQR, Z-score) taught in the data cleaning modules.
Covered in AI Udaan
- Line, bar, pie, histogram, scatter plots
- Bins, chart anatomy, grouping with aggregation
- Box plots for outlier analysis
- Visual exploration before modeling
Go deeper with the full bootcamp
This guide is a free overview. AI Udaan is a 16-week mentor-led Python with AI/ML bootcamp — live classes, assignments, projects, certificate, and career support for learners across Nepal.
FAQ
Does AI Udaan use other visualization libraries?
Matplotlib is the primary visualization tool in the early syllabus. The focus is on interpreting data for ML decisions rather than dashboard design.
Related AI guides
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