Ashutosh Dumka
This Level 3 Mastery Badge signifies successful completion of the Mastery in Applied Translational AI milestone, a capstone experience within the Certificate in Translational AI Pathway. Badge earners have demonstrated their ability to apply advanced artificial intelligence (AI) principles and methods in collaboration with industry partners, translating academic and technical knowledge into real-world, high-impact solutions.
This badge reflects master-level proficiency, where learners independently define project objectives, develop and deploy machine learning (ML) pipelines, and communicate tailored solutions that address complex business or research challenges. Embedded in real-world applications, participants collaborate directly with industry partners to define business needs, develop and deploy ML pipelines on cloud platforms, and deliver data-driven solutions.
In addition to technical development, learners engage in seminars on ethics, business requirement analysis, and advanced ML techniques, while refining soft skills through professional client communications, presentations, and team collaboration. This experience prepares students for high-impact roles in AI-driven industries, particularly where communication, cloud deployment, and ethical decision-making intersect with technical skill.
Skills / Knowledge
- Artificial Intelligence
- Cloud Computing
- Programming in Python
- Teamwork
- Communication
- Problem-solving
Issued on
Expires on
Earning Criteria
Required
Participants have successfully completed a 16-week hybrid course focused on industry-sponsored machine learning (ML) projects. Embedded in real-world applications, participants collaborate directly with industry partners to define business needs, develop and deploy ML pipelines on cloud platforms, and deliver data-driven solutions.
In addition to technical development, learners engage in seminars on ethics, business requirement analysis, and advanced ML techniques while refining professional client communications, presentations, and team collaboration. This experience prepares learners for high-impact roles in AI-driven industries, particularly where communication, cloud deployment, and ethical decision-making intersect with technical skills.
Earning Criteria:
To earn the Industry-Based Machine Learning Solutions micro-credential, learners must:
Participate in weekly 3-hour hybrid sessions over a 16-week semester
Collaborate with industry clients to identify and define business problems and ML-based solutions
Design and deploy machine learning pipelines using cloud platforms
Submit weekly progress reports and deliver milestone presentations to clients and instructors
Develop final deliverables including a professional technical report, dashboard visualizations, and a client-facing presentation
Assessment:
Weekly Progress Reports – Demonstrating project updates, problem-solving, and next steps
Midterm Client Report & Presentation– Summarizing early progress, approach, and alignment with client needs
Final Presentation – Delivering professional-grade results and insights to clients and faculty
Final Technical Report – Documenting the entire project, including methods, outcomes, and implementation details
Team Collaboration & Participation – Reflecting active engagement, teamwork, and peer accountability
A cumulative score of 70% or higher across all assessments is required to earn the micro-credential.
About TrAC
The Translational AI Center will break down disciplinary silos to bring together core Iowa State artificial intelligence researchers and subject matter experts interested in applying new technologies to their work. The center will initially focus on conducting core artificial intelligence research, as well as pursuing five application areas of artificial intelligence:
Materials design and manufacturing
Biology, healthcare, and quality of life
Autonomy, intelligent transportation, and smart infrastructure
Food, energy, and water
Ethics, fairness, and adoption.
In addition to serving as a scientific hub for translational artificial intelligence, the center will organize research seminars, host workshops, training, and onboarding programs, offer seed funding for research projects, and serve as an intermediary between private industry partners seeking research services and appropriate university faculty.