Introduction

3D data visualization plays an important role in representing complex datasets in a more intuitive and interactive manner. It is widely used across fields such as science, engineering, finance, gaming, and even in business intelligence. This course will provide an in-depth understanding of 3D visualization techniques, from creating 3D models to visualizing data in three-dimensional space. Participants will learn how to apply various libraries and tools to create compelling 3D visuals that help users understand complex data structures and relationships.

Objectives

By the end of this course, participants will:

• Understand the fundamentals of 3D visualization and its applications across various industries.
• Gain hands-on experience with popular 3D visualization libraries such as Matplotlib, Plotly, Mayavi, and Three.js.
• Learn how to create 3D scatter plots, surface plots, and volumetric visualizations.
• Develop interactive 3D models and visualizations for real-time data.
• Explore advanced 3D rendering techniques, such as lighting, textures, and animations.
• Learn best practices for integrating 3D visualizations into web applications or dashboards.

Who Should Attend?

This course is ideal for:

• Data scientists and analysts who want to expand their knowledge of 3D visualization techniques.
• Developers and engineers interested in integrating 3D visualization into applications and dashboards.
• Geospatial analysts working with 3D terrain, geographic data, or volumetric data.
• Researchers, architects, and designers who need to create 3D models for presentations or reports.

Day 1: Introduction to 3D Visualization

Morning Session: Overview of 3D Visualization

• Introduction to 3D visualization and its importance in various industries
• Key concepts in 3D visualization: Coordinate systems, perspectives, and depth
• Types of 3D visualizations: Points, surfaces, volumes, and meshes
• Introduction to popular 3D visualization libraries: Matplotlib, Plotly, Mayavi, Three.js
• Hands-on: Installing libraries and setting up the environment for 3D visualization

Afternoon Session: Basic 3D Plotting with Matplotlib

• Creating 3D scatter plots and surface plots using Matplotlib
• Customizing axes, labels, and tick marks in 3D plots
• Introduction to plot customization: Colors, markers, and styles
• Hands-on: Creating a simple 3D scatter plot and a 3D surface plot using Matplotlib

Day 2: Advanced 3D Data Visualizations

Morning Session: Advanced 3D Plotting with Plotly

• Introduction to Plotly for interactive 3D plots
• Creating and customizing 3D scatter plots, surface plots, and mesh plots in Plotly
• Adding interactivity: Rotation, zoom, and hover effects
• Hands-on: Building interactive 3D plots and dashboards using Plotly

Afternoon Session: Volumetric Visualizations with Mayavi

• Introduction to Mayavi: A powerful 3D visualization tool for scientific data
• Visualizing volumetric data and creating 3D volume plots with Mayavi
• Using Mayavi’s advanced features for 3D rendering and visualization
• Hands-on: Visualizing a volumetric dataset using Mayavi

Day 3: Creating Interactive 3D Models

Morning Session: Introduction to Three.js for 3D Models

• Understanding Three.js as a web-based 3D visualization library
• Setting up Three.js environments for rendering 3D models
• Basics of 3D objects: Meshes, lights, and cameras
• Hands-on: Creating a basic 3D model (e.g., a rotating cube) with Three.js

Afternoon Session: Building Interactive 3D Models

• Adding textures and materials to 3D objects
• Implementing animations and controls in 3D models
• Creating interactive 3D scenes using HTML, CSS, and JavaScript with Three.js
• Hands-on: Developing an interactive 3D model (e.g., rotating 3D object with interactive user controls)

Day 4: Advanced Rendering Techniques

Morning Session: Lighting, Shading, and Texturing

• Introduction to 3D lighting techniques: Ambient, point, directional, and spotlight
• Understanding shaders and how they affect the appearance of 3D objects
• Applying textures to 3D models to enhance realism
• Hands-on: Adding lighting, shading, and textures to a 3D model

Afternoon Session: 3D Data Animation

• Creating dynamic 3D visualizations with time-based data
• Implementing animations to visualize changes in data over time
• Working with Plotly and Three.js to animate 3D objects and scenes
• Hands-on: Animating 3D data (e.g., animated surfaces, moving objects, etc.)

Day 5: Integration and Best Practices

Morning Session: Integrating 3D Visualizations into Web Applications

• Embedding 3D visualizations into web applications with Plotly, Three.js, and other libraries
• Integrating 3D visualizations into modern web frameworks (e.g., React, Angular, Vue.js)
• Best practices for performance optimization: Reducing rendering time, optimizing data, and caching
• Hands-on: Embedding a 3D plot or model into a basic web application

Afternoon Session: Final Project and Course Wrap-Up

• Final project: Participants will create a complete 3D visualization or interactive model that includes data import, visualization, and interactivity
• Best practices for presenting 3D visualizations in reports and presentations
• Wrap-up and Q&A session
• Final project presentations and feedback

Materials and Tools:

• Required tools: Matplotlib, Plotly, Mayavi, Three.js, Python, JavaScript, and web development tools
• Sample datasets for visualization (e.g., geographical, scientific, and volumetric data)
• Access to example code and project files for hands-on sessions
• Recommended resources: Documentation for Plotly, Three.js, and Mayavi