Foundations in Responsible AI Adoption (4 Hours)

Instructor-Led Formats: In-Person or Virtual Live

1 Day
4 Hours

COURSE DESCRIPTION

Foundations in Responsible AI Adoption is a 4-hour, instructor-led course that gives leaders a practical, non-technical foundation for adopting AI responsibly in their organizations. The course covers practical AI use cases, data governance and privacy, fraud and anomaly detection, responsible oversight, organizational accountability, and the evaluation of AI technologies. Participants learn how to identify AI uses that offer high value at low risk, apply core governance and privacy principles when introducing AI tools, and assess vendor and tool claims with a critical eye.
The course is designed for business owners, executives, public-sector leaders, and other professionals responsible for decisions involving AI adoption and governance. It is taught by Raj Prahast Maheswarapu, PMP. Participants leave with practical frameworks for evaluating AI use cases, data governance, and vendor claims, along with a Certificate of Completion. The course is offered in person or live online.

WHO SHOULD TAKE THIS COURSE

This course is designed for:

  • Business owners, executives, public-sector leaders, and other professionals responsible for decisions involving AI adoption and governance.

WHAT YOU LEARN

  1. Understand core AI concepts, capabilities, and limitations;
  2. Identify practical AI applications and assess their potential value and risks;
  3. Understand data governance, privacy, ethics, human oversight, and organizational accountability;
  4. Recognize how AI can support fraud and anomaly detection, including the need for human review;
  5. Evaluate AI tools and vendor claims and identify initial steps for responsible adoption.

WHAT YOU GAIN

4 hours of in-person or live online instructor-led training on responsible AI adoption

Practical frameworks for evaluating AI use cases, data governance and privacy, and vendor claims

Certificate of Completion

SCHEDULE OPTIONS

  • AM Virtual-Live Session
    • Virtual-live and instructor-led training
    • 8:30 AM – 12:30 PM ET
  • PM Virtual-Live Session
    • Virtual-live and instructor-led training
    • 12:30 PM – 4:30 PM ET

UPCOMING COURSE DATES

December 11, 2026 – December 11, 2026  |  Virtual-Live  |  PM Virtual-Live Session  |  Instructor: Raj Prahast Maheswarapu, PMP

COURSE POLICIES

Course Retake Policy: To further support learner success, SOAR offers a complimentary course retake opportunity for certification preparation programs. Participants who complete one of our certification preparation programs (a specific course listed as completing requirements to qualify for a particular certification exam) and do not pass the certification exam on their first attempt may attend one future session of the same certification preparation course at no additional cost, provided the class is not full and seats remain available. This policy reflects SOAR’s commitment to learner achievement and continuous professional growth.

Note: Verification of the first exam attempt failure is required to qualify for a course retake. This Course Retake Policy only applies to courses listed as completing the requirements to qualify for a certification exam.

Course Refund Policy: All training purchases are final and non-refundable. Please review course details carefully before registering. If SOAR cancels a training, registrants will receive rescheduling options.

Next Start Date:

December 11, 2026
PM Virtual-Live Session

Price: $580

Download the Course Information Page

Get detailed information about this course in PDF format.

Meet the Instructor for Our Next Session:

Raj Prahast Maheswarapu, PMP
Raj Prahast Maheswarapu is an IT and data safeguarding leader whose role in Florida centers on protecting sensitive government data.
Why Learn from This Instructor
Prahast teaches from direct experience rather than theory. His work sits within the regulatory, security, and accountability requirements that government technology leaders face, so students learn approaches that hold up in real organizations.
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