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Course Overview:
This class uses a sample product development initiative to illustrate the course principles. If you need to learn what is required to lead or participate in an Agile effort using the SCRUM approach within your organization, this course will cover the Agile adaptive life cycle framework and all of the ceremonies, artifacts, and roles.
Attendees to PM-222: Agile Principles using will receive TechNow approved course materials and expert instruction.
Dates/Locations:
Duration: 2 Days
Course Objectives: At the conclusion of this course, students will be able to:
Target Student:
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Here are the security courses specific to TechNow:
Certified AI Program Manager (CAIPM) is EC-Council’s professional certification for people responsible for owning AI decisions and driving execution: business, technology, data, and risk.
The Certified AI Program Manager (CAIPM) Course equips you with hands-on expertise across the full spectrum of AI tools, from conversational AI and image generation to code assistants and audio synthesis.
Participants will learn how to evaluate, deploy, and integrate AI tools into enterprise workflows, understanding not just how they work, but how to leverage them for maximum business impact. This course covers how to assess AI readiness across teams and processes, Prioritize AI use cases tied to business outcomes, Design adoption and rollout roadmaps , Coordinate delivery across cross-functional teams, implement governance, Responsible AI, and security controls , and how to track performance and ROI to prove value
By the end of the course, learners will be well-prepared to take the Certified AI Program Manager (CAIPM) exam and demonstrate the ability to own AI initiatives end to end , validate mastery of decision framing and trade-off analysis for AI initiatives and Apply governance, ethics, and risk management principles across the AI lifecycle.
Course Objectives:
•MLOps Principles: Model life cycle management for scalable, production-ready AI
•Use Case Evaluation: ROI-driven assessment and prioritization of AI initiatives
•AI Strategy Frameworks: Enterprise AI roadmapping, portfolio planning, and value prioritization
•AI Investment Justification: Quantifying AI value, ROI, and mission impact for funding decisions
•Change Management: Workforce enablement and stakeholder alignment
•KPI Development: AI metrics, success indicators, and executive dashboards
•AI Governance: Risk, ethics, compliance, and responsible AI principles
•Vendor Evaluation: AI platform and tool selection aligned with enterprise needs
Dates/Locations:
Prerequisites: Familiarity with generative AI concepts, prompt engineering fundamentals, and AI workflows will help you succeed.
