Artificial intelligence is here. And “AI bootcamps” and “AI training courses” are seemingly everywhere.
Those offerings are rapidly maturing to meet the needs of specific industries, organizations and departments. The best programs are designed with real-world applications purposefully built into the training experience.
That’s what the Center for Manufacturing Advancement (CMA) at the Institute for Advanced Learning and Research (IALR) created: a custom, 300-hour Applied Data Science Accelerator tiered program to upskill engineers into data science practitioners. Twelve BWXT employees graduated from this pilot program on July 8.
“The Applied Data Science Accelerator Program stands out in a crowded AI training landscape by focusing on practical capability development and measurable business impact, not just conceptual learning,” said Meredith Gregory, Director of Digital Strategy and Program Management at IALR.
“We’re building a workforce that doesn’t just understand AI but uses it. This program equips our teams to apply BWXT’s unique data and expertise to real manufacturing challenges, making us faster, more precise, and more competitive. By training our people to work directly with data and models, we’re turning BWXT’s hard‑won expertise into actionable insight we can use to boost speed, cut rework, and strengthen performance.” – Shane Jacobs, General Manager, BWXT.
Creating a Program that Meets the Mission
BWXT, which manufactures naval nuclear components and reactors, has consistently hired graduates of the Accelerated Training in Defense Manufacturing (ATDM) program at IALR to work at its facilities in Lynchburg, Virginia, and in Mount Vernon, Indiana. The company has also received optimization services from IALR’s CMA, which helps manufacturers deploy proven technology, strengthen processes and build workforce capability in ways that deliver results on the floor.
The idea for this accelerated program happened during a meeting between IALR and BWXT staff. Those conversations quickly went from discussing the need to outlining a possible structure and scope.
Over the next several months, seven staffers of the CMA and IALR, as well as two expert consultants, had varying levels of involvement in the program’s development and execution. BWXT provided needed insight to adapt what we were planning to their environment and by extension, manufacturing environments. The course officially launched on April 8.
“Not everyone can just create a class like this if you don’t have a good idea of what works,” Gregory said. “We pulled a lot of what works from our other workforce training programs and even machine learning and AI internship experiences we offered in the summer of 2025.”
This training equipped these 12 BWXT employees to implement AI technologies more effectively into plant operations. In short, they can manipulate data, train models, evaluate those models, and put those models into production.
Tiers of Capability
While grounded in traditional lecture and assessment style instruction, the course focuses on the application of skills through an organization-selected Agile class project. This course integrates proven practices from data science, team development, and engineering education to help organizations cultivate a data science capability within their existing workforce, emphasizing both technical and soft skills.
The program was designed to train four different tiers. Graduates from this cohort were spread across tiers 2-4.
- Data Science Foundations: Understands core data science and AI concepts at a conceptual level. Can identify appropriate use cases, recognize risks and engage in informed conversations, but is not expected to build, implement or own technical work. 16 hours
- Data Science Practitioner: Can execute well-defined data science tasks with guidance. Uses Python/SQL basics, supports pipeline and model implementation, and follows established processes. Limited ownership, but contributes effectively within structured workflows. ~ 300 hours
- Data Science Associate: Operates as an independent contributor. Can design and build models and pipelines with minimal oversight, analyze results and communicate insights to stakeholders. Begins contributing to technical decisions and may own smaller projects. ~300 hours
- Tier 4: Functions as a technical leader and system architect. Designs scalable solutions, owns technical decisions, ensures quality and performance, and leads projects end-to-end. Communicates effectively across stakeholders and mentors others while driving business impact. ~ 300 hours
“The CMA is built around a simple idea: manufacturers achieve better outcomes when people, processes and technology advance together. This program demonstrates how developing workforce capability in parallel with digital transformation efforts can accelerate adoption and create lasting impact on the production floor.” – John Ring, Vice President, Center for Manufacturing Advancement
Lessons Learned and Future Opportunities
Throughout the program, BWXT employees provided consistent feedback about what elements of the course were working and what weren’t. They shared this feedback every day, at the end of every sprint (2 weeks) and at the midpoint.
“Pilot programs hinge on feedback and short iteration cycles. BWXT could not have been more gracious in providing invaluable feedback,” Gregory said.
Now that this curriculum is developed, the CMA stands ready to deliver this course – informed by the lessons learned during this pilot phase and customized to each customer’s needs. The Applied Data Science Accelerator Program will help more manufacturers effectively integrate AI, machine learning and applied data science into their operations.
