What You’ll Learn: Master Jupyter for AI
You’ll go from opening your first notebook to creating polished, shareable, and reproducible AI workflows — in just two weeks.
Notebook Structure
Organize cells, use keyboard shortcuts, and manage kernel states like a pro.
Markdown & Formatting
Write beautiful documentation with headers, lists, math (LaTeX), and embedded media.
Data Visualization
Plot charts inline with Matplotlib, Seaborn, and interactive widgets.
Reproducibility & Sharing
Export to HTML/PDF, version-control with Git, and collaborate via GitHub or Colab.
Who Is This Course For?
Perfect for anyone starting their AI or data journey and wants to work efficiently from day one.
- Students beginning data science or machine learning
- Researchers documenting experiments and results
- Professionals preparing reports or portfolios
Hands-On Projects
Exploratory Data Report
Analyze a real-world dataset and document your insights with Markdown, code, and visualizations.
Model Experiment Log
Track multiple ML experiments, compare results, and explain your choices clearly.
Capstone
Publishable Notebook
Create a complete, self-contained notebook and export it as a portfolio-ready HTML report.
2-Week Jupyter Syllabus
~20 hours total • Lifetime LMS access • 1:1 mentor support
Week 1: Notebook Basics
- Installing Jupyter Lab & Notebook
- Cell types: code, Markdown, raw
- Keyboard shortcuts & magic commands
- Inline plotting and basic visualization
- Managing kernels and environments
Week 2: Collaboration & Publishing
- Writing rich Markdown with LaTeX
- Version control with Git and .ipynb
- Exporting to HTML, PDF, and slides
- Sharing via GitHub, Colab, or Binder
- Best practices for reproducible research
NSTC‑Accredited Certificate
Share your verified credential on LinkedIn, resumes, and portfolios.
Frequently Asked Questions
Basic familiarity helps, but it’s not required. We’ll show you how to run simple code and focus more on notebook structure, Markdown, and best practices.
Yes! You’ll export notebooks to HTML, PDF, and version-control them with Git — key skills for collaboration and portfolio building.
