3D Modelling and Printing with Artificial Intelligence Course

Lesson 1 • Setting Up Your Modelling Environment

Guides students through software installation, viewport navigation, and unit configuration. Ensures a functional workspace before modelling begins.

Lesson 2 • Overview of Additive Manufacturing

Explains how 3D printers build objects layer by layer. Connects printing physics to design decisions made in modelling software.

Lesson 3 • 3D File Formats and Data Standards

Introduces STL, OBJ, 3MF, and STEP formats and their use cases. Prepares students to export models correctly for downstream tools.

Lesson 4 • Introduction to 3D Modelling Concepts

Covers geometric primitives, coordinate systems, and mesh topology. Establishes vocabulary used throughout the course.

Lesson 1 • Boolean and Constructive Solid Geometry

Applies union, difference, and intersection operations to combine shapes. Enables rapid creation of complex mechanical parts.

Lesson 2 • Parametric and Procedural Modelling

Uses constraint-based and node-driven tools to create editable, dimension-accurate models. Supports engineering and product design workflows.

Lesson 3 • Subdivision and Smoothing Workflows

Introduces subdivision surface modifiers to achieve smooth, high-resolution forms. Connects low-poly control cages to final print geometry.

Lesson 4 • Polygon Modelling Fundamentals

Teaches extrusion, loop cuts, and face manipulation to build organic and hard-surface shapes. Forms the primary modelling skill set for the course.

Lesson 1 • Introduction to Generative AI for 3D

Surveys the landscape of AI tools that produce 3D geometry from prompts or images. Positions AI as a creative accelerator within the modelling pipeline.

Lesson 2 • Cleaning and Retopologizing AI Meshes

Covers manual and automated retopology workflows to convert raw AI output into clean, print-ready models. Bridges AI generation and professional quality standards.

Lesson 3 • Prompt Engineering for 3D Generation

Develops skills in writing effective prompts that yield usable geometry. Reduces iteration cycles by improving prompt specificity and structure.

Lesson 4 • Evaluating AI-Generated Mesh Quality

Applies mesh analysis tools to assess AI output for topology errors and print viability. Builds critical judgement before committing to cleanup work.

Lesson 1 • Thermoplastic Filament Properties

Compares PLA, ABS, PETG, TPU, and engineering-grade filaments by strength, flexibility, and printability. Guides material selection for FDM workflows.

Lesson 2 • Resin and Photopolymer Materials

Covers standard, ABS-like, flexible, and castable resins for SLA and MSLA printing. Connects resin chemistry to surface finish and post-cure requirements.

Lesson 3 • Post-Processing and Surface Finishing

Applies sanding, priming, chemical smoothing, and painting techniques to improve print aesthetics and function. Completes the production workflow from print to finished part.

Lesson 4 • Material Selection with AI Assistance

Uses AI recommendation tools to match material properties to functional requirements. Reduces trial-and-error by leveraging data-driven material databases.

Lesson 1 • Slicer Software Fundamentals

Introduces slicer interface, model import, and basic print profile selection. Establishes the link between model geometry and G-code output.

Lesson 2 • Layer Height, Speed, and Temperature

Tunes layer height, print speed, and nozzle temperature for quality and efficiency. Connects slicer parameters to physical print outcomes.

Lesson 3 • Support structures and overhangs

Explains overhang angle thresholds and support generation strategies. Reduces post-processing time through intelligent support placement.

Lesson 4 • G-code review and custom commands

Reads and edits G-code to insert custom start, end, and pause sequences. Gives students direct control over printer behaviour beyond slicer defaults.

Lesson 1 • Printability constraints in optimisation

Incorporates overhang, minimum feature size, and build direction constraints into optimisation runs. Ensures AI-optimised geometry is manufacturable without excessive support.

Lesson 2 • Generative design workflows

Uses AI generative design tools to explore multiple design alternatives simultaneously. Accelerates engineering design by automating constraint-driven geometry creation.

Lesson 3 • Principles of topology optimisation

Explains how optimisation algorithms redistribute material under load constraints. Provides the theoretical basis for AI-assisted structural design.

Lesson 4 • Lattice and infill structure generation

Creates internal lattice structures using AI tools to reduce weight while maintaining strength. Applies directly to functional part design for additive manufacturing.

Lesson 1 • AI-driven print failure prediction

Applies machine learning models trained on print data to predict and prevent common failures. Reduces material waste and reprints through proactive quality control.

Lesson 2 • Automated mesh repair with AI

Uses AI-powered repair pipelines to fix holes, inverted normals, and self-intersections automatically. Reduces manual cleanup time in high-volume production contexts.

Lesson 3 • Scripting and automation in modelling tools

Introduces Python and built-in scripting APIs to automate repetitive modelling and export tasks. Scales individual workflows to batch production efficiency.

Lesson 4 • Building a semi-automated design pipeline

Connects AI generation, optimisation, repair, and slicing into a unified automated workflow. Demonstrates end-to-end pipeline construction for professional production environments.

Lesson 1 • Portfolio documentation and presentation

Structures project documentation, renders, and process narratives into a professional portfolio. Prepares students to communicate design decisions to clients and employers.

Lesson 2 • Full model development and optimisation

Builds the selected concept into a complete, optimised, print-ready model using all course techniques. Integrates manual modelling, AI assistance, and simulation validation.

Lesson 3 • Printing, testing, and iteration

Executes physical prints, tests against design criteria, and iterates based on results. Closes the design loop between digital model and physical prototype.

Lesson 4 • Concept development with AI tools

Uses AI generation and generative design to rapidly explore concept variations. Accelerates ideation while maintaining alignment with the design brief.