Mastering Modern AI Course
RECENT ADVANCES IN
RECENT ADVANCES IN
ML/AI MODEL DEVELOPMENT AND VALIDATION
Mastering Modern AI: From Transparent Models to Trustworthy Validation
RECENT ADVANCES IN
ML/AI MODEL DEVELOPMENT AND VALIDATION
Mastering Modern AI: From Transparent Models to Trustworthy Validation
ABOUT THE COURSE
A hands-on workshop facilitated by MoDeVa focused on recent advancements in machine learning (ML) and artificial intelligence (AI). This workshop is carefully structured to provide in-depth knowledge and practical skills for professionals and enthusiasts interested in the latest techniques for ML model development and validation.
Participants will gain insights into building inherently interpretable machine learning models, using cutting-edge methods such as Gradient Boosted Trees, Neural Trees, GAMI-Net, and Mixture of Experts. The session will also cover advanced methods of explainability both to design inherently interpretable machine learning via Functional ANOVA as well as post-hoc approaches
The workshop will emphasize rigorous validation approaches to ensure the reliability, robustness, and resilience of ML models. Attendees will explore conceptual soundness, model hacking techniques, advanced residual analysis, and techniques for identifying and clustering model weaknesses and failures.
Robustness diagnostics for overcoming overfitting. Resilience diagnostics to anticipate the impacts of distribution drift . Reliability diagnostics to identify decision uncertainty.
An important segment of the workshop will address fairness and debiasing in machine learning. Participants will learn how to measure and diagnose biases, apply effective de-biasing strategies, and design ethical ML solutions through thoughtful feature engineering and optimization.
Lastly, the workshop offers extensive insights into generative language model validation. Attendees will discover the intricacies of embedding models of contrastive and classifier training, automated test generation methods, and the evaluation of semantic similarity and natural language inference. Model weakness identification, robustness and adversarial testing methods will also be thoroughly discussed, preparing participants to address critical challenges in the deployment of generative AI systems.
Learning Objectives
Develop and Validate Interpretable Machine Learning Models
Apply Advanced Validation, Diagnostic, and Monitoring Techniques
Ensure Fairness, Ethical Integrity, and Robustness in Generative AI Systems
Lead Instructor
Location & Dates
Workshop Date:
July 7–8, 2025
Time: 9:00 AM – 5:00 PM (both days)
Venue:
Dubois Center at UNC Charlotte, Classroom 1101
320 E 9th Street, Charlotte, NC 28202
All attendees must check in at the Dubois Center lobby upon arrival to complete registration and receive name badges. Please plan to arrive at least 30 minutes early to allow time for check-in.
Agenda
Monday, July 7th
| Time | Session |
|---|---|
| 8:00 AM – 9:00 AM | Registration & Check-in |
| 8:30 AM – 9:15 AM | Breakfast |
| 9:15 AM – 10:45 AM | SESSION 1 |
| Introduction to Trustworthy Model Building & Validation | |
| Functional ANOVA & Gradient Boosting | |
| 10:45 AM – 11:00 AM | Morning Intermission (Coffee) |
| 11:00 AM – 12:30 AM | SESSION 2 |
| Data Loading, Preprocessing, Preparation | |
| Mixture of Experts & Advanced Trees | |
| 12:30 PM – 12:45 PM | Sponsor Introductions |
| 12:45 PM – 1:45 PM | Lunch |
| 1:45 PM – 3:15 PM | SESSION 3 |
| Introduction to ReLU and GAMI-Net | |
| Gradient Boosted Linear Trees & Neural Trees | |
| 3:15 PM – 3:30 PM | Afternoon Intermission (Coffee) |
| 3:30 PM – 5:00 PM | SESSION 4 |
| Model Testing, Outcome Analysis, and Resilience | |
| Reliability & Robustness Diagnostics | |
| 5:00 PM – 6:00 PM | Post-Workshop Social Hour (Light refreshments) |
Tuesday, July 8th
| Time | Session |
|---|---|
| 8:00 AM – 9:00 AM | Check-in |
| 8:30 AM – 9:15 AM | Breakfast |
| 9:15 AM – 10:45 AM | SESSION 5 |
| Recap of Day One | |
| Fairness & Debiasing in ML | |
| 10:45 AM – 11:00 AM | Morning Intermission (Coffee) |
| 11:00 AM – 12:30 AM | SESSION 6 |
| Introduction to Generative AI & LLM Validation | |
| 12:30 PM – 1:45 PM | Lunch |
| 1:45 PM – 3:15 PM | SESSION 7 |
| Design of Experiments & Query Generation | |
| Evaluation Metrics, Human Calibration, and Robustness Testing | |
| 3:15 PM – 3:30 PM | Afternoon Intermission (Coffee) |
| 3:30 PM – 4:30 PM | SESSION 8 |
| Generative AI Validation & Robustness Analysis | |
| 4:30 PM – 5:00 PM | Conclusion & Final Q&A |
Pricing Options
This hands-on workshop is priced per participant, with significant discounts available for organizations that are members of the TAIMing AI Center. Membership not only reduces the cost per attendee but also provides year-round access to other trainings, workshops, and research collaboration opportunities. Volume discounts apply for companies sending multiple participants, which stack with membership rates for maximum value. To discuss becoming a member, please contact us.
The deadline to register and pay all fees for the workshop is due July 6th at 12:00 P.M. No onsite registrations or payments will be accepted on the morning of the workshop (I.E. No walk-ins or late payments).
| Membership Level | 1–4 Participants | 5–9 Participants (10% off) | 10+ Participants (15% off) |
|---|---|---|---|
| Non-Member | $1,500 / person | $1,350 / person | $1,275 / person |
| Silver Member ($25K) | $1,125 / person | $1,012 / person | $956 / person |
| Gold Member ($50K) | $900 / person | $810 / person | $765 / person |
| Platinum Member ($150K) | $750 / person | $675 / person | $637 / person |
Parking Information
The gravel lot located at 422 E. 9th Street across from the Dubois Center is a restricted-use lot managed by UNC Charlotte Parking and Transportation Services.
UNC Charlotte Faculty/Staff: Must have a parking permit with a “+ CCB” designation (e.g., Standard + CCB or Premium + CCB) to use the lot. Faculty/staff without this suffix can email PaTS@charlotte.edu to request permission.
Visitors and Non-UNC Charlotte Attendees: Must pay using ParkMobile (Zone info available on site). No university permits are available for purchase by visitors.
Alternative Options include parking on main campus and riding the LYNX light rail or using the surrounding Preferred Parking lots (typically $10/day).
Security/Event Check In Requirements
All attendees—University and Non-University—must report to the Dubois Center lobby upon arrival to the property to complete visitor registration and receive name badges before proceeding to the classroom. A representative of the Center for TAIMingAI will be set up in the lobby to assist attendees with the check-in process. Representatives of the TAIMingAI Center are expected to arrive 30 minutes prior to the start of the event to begin assisting attendees with check-in. However, if a representative of the Center for TAIMingAI is not present upon your arrival, you must wait in the lobby. Faculty of UNC Charlotte must wear their University-issued nametag or other official identification.
*Please note that attendees who do not complete the check-in process will be denied classroom access, and may be asked to leave the property–as outlined by the Dubois Center’s Security Procedures and Event Guidelines—no exceptions.
Dubois Center Security Procedures
FAQs