Hands-on Tutorial on Multimodal AI Models
April 3 @ 9:00 am – 5:00 pm
Multimodal AI Models
8-Hour Deep-Dive Tutorial
Vision + Language + Audio + Action — from foundations to hands-on systems
✨ A Comprehensive, End-to-End Multimodal Approach
Unlike tutorials that focus on a single model or demo, this workshop builds a complete, practical toolkit: multimodal conversation systems, encoder-based retrieval, and vision-language-action (VLA) workflows. You’ll learn not only how to use these models, but when to choose each approach, how to evaluate reliability, and how to connect modalities into usable systems.
The Comprehensive Framework
Master multimodal AI through five interconnected pillars
Foundations & Landscape
What multimodal AI is, why it matters, and how modern systems combine modalities (text, vision, audio, video, sensors).
Multimodal Conversation
Build assistants that accept images + text (and optional audio), maintain context, and produce grounded, reliable answers.
Encoders & Retrieval
Use joint embedding spaces for zero-shot classification and cross-modal retrieval (“find images that match this text”).
Vision-Language-Action (VLA)
Explore embodied AI: models that perceive, reason, and act — including simulation environments and action grounding.
8-Hour Comprehensive Curriculum
A carefully crafted learning journey from fundamentals to VLA systems
🌍 Module 1: Introduction & Landscape
Define multimodal AI, survey model families, and build intuition for capabilities, limitations, and common failure modes.
💬 Module 2: Multimodal Conversation Systems
Build a working multimodal chatbot and learn how prompts, context, and grounding impact reliability and answer quality.
🍽️ Lunch & Networking
Connect with participants, discuss applications, and brainstorm capstone project ideas.
🧩 Module 3: Vision-Language Models & Encoders
Implement encoder workflows for zero-shot classification and cross-modal retrieval. Learn how embeddings enable scalable search and alignment.
🤖 Module 4: Vision-Language-Action (VLA) Models
Explore perception → reasoning → action loops and prototype an embodied agent workflow in simulation. Learn what “action grounding” means and how to test robustness.
✅ Wrap-Up: Capstone + Q&A
Review key takeaways, discuss next steps, and align on capstone expectations, resources, and submission timeline for the micro-credential badge.
Schedule shown is a workshop plan and may shift slightly to match group pace and Q&A.
Advanced Topics Covered
Go beyond the basics with practical patterns and evaluation techniques
Fusion & Alignment
How architectures align text and vision/audio signals, and why certain fusion strategies work better for different tasks.
Cross-Modal Retrieval
Embedding-based search, zero-shot classification, and practical evaluation for scalable multimodal retrieval systems.
Evaluation & Failure Modes
Hallucinations, grounding errors, spatial reasoning pitfalls, and systematic testing strategies for real deployment.
Embodied AI & VLA
Perception-to-action loops, simulation-driven development, and how multimodal models operate in interactive environments.
Safety & Guardrails
Practical safety constraints, output verification, and human-in-the-loop patterns for robust multimodal systems.
Technologies & Tools
A modern toolkit for multimodal systems and prototyping
Who Should Attend
Designed for diverse backgrounds across research, engineering, and applied AI
Software Developers
Learn patterns for building multimodal assistants and retrieval systems you can integrate into applications.
Students & Researchers
Understand modern multimodal architectures and build reproducible demos for projects and publications.
Industry Professionals
Evaluate model options and workflows for real use cases in manufacturing, analytics, or product teams.
Robotics & Embodied AI
Explore VLA concepts and how multimodal learning powers autonomy and interactive agents.
Prerequisites & Requirements
What you need to succeed in this comprehensive program
💻 Technical Skills
- Basic to intermediate Python programming
- Comfort running notebooks/scripts and debugging basics
- Laptop with Python installed (3.10+ recommended)
- Git basics helpful but not required
🧠 AI Knowledge
- Basic understanding of ML concepts is helpful
- No prior multimodal experience required
- We’ll cover core foundations during the workshop
- Curiosity and willingness to experiment!
📦 Materials to Bring
- Your laptop (fully charged)
- Notebook for notes
- Questions and use cases from your domain
- Any required access/keys provided during workshop (as applicable)
What You’ll Earn
Recognized credentials and reusable materials for your next project
Official Micro-Credential Badge
Earn a verified digital badge recognizing your fluency in multimodal AI models and workflows.
Complete Code & Materials
Access workshop notebooks, examples, and reference implementations to reuse after the session.
Professional Network
Connect with fellow participants and practitioners working on multimodal AI across domains.
Registration
Invest in your AI expertise with flexible pricing options
Micro-credential completion includes participation plus a capstone submission window following the workshop.
Ready to Master Multimodal AI?
Limited seats available for this intensive, hands-on program. Secure your spot and start building multimodal systems that combine vision, language, and action for real-world applications.
Register Now – Reserve Your Seat! →Questions? Contact us at jrwaite@iastate.edu