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AI Learning Over Time • Cohort-Based

Cohorts and Workshops

These offerings are designed for groups who want to build practical AI capability together over time—using a repeatable, outcomes-focused approach. Explore the options below, then visit each class page for the full details.

  • Team Activation — align on goals, tools, and guardrails.
  • AI Audit — assess readiness, risks, and highest-value use cases.
  • AI + Scrum Cohorts — build habits across roles with hands-on practice.
  • AI for Scrum Teams — practical, role-based workflows your team can adopt.
Tip: If you’re not sure where to start, choose AI Audit first—then map a cohort plan from the findings.

Ready to start?

Pick your next step—start with free learning, watch the videos, or browse the full course catalog.

Prefer Virtual or On-Site delivery for your team? See Corporate Training Offerings.

Search Results

24 Feb 2026

Picking a Model for Your Team and Product March 23, 2026.

Author: Rod Claar  /  Categories: Picking a Model for Your Team or Product  / 

Event date: 3/23/2026 2:00 PM - 5:00 PM Export event

  • Attending: 0
  • Seats: 6
  • Remaining: 6
  • Price: $99.00 - $349.00
$99.00 - $349.00
Only registered users can register for an event. Please login or register.
March 23, 2026 | 2:00 PM – 5:00 PM PST

Course Overview

Selecting the right development model is critical to delivering value effectively. This interactive live session examines common Agile and hybrid approaches and helps you determine which model best aligns with your team’s structure, product type, stakeholder expectations, and organizational constraints.

Participants will explore the trade-offs between frameworks such as Scrum, Kanban, and hybrid implementations, learning how to evaluate complexity, uncertainty, regulatory needs, and team maturity before committing to an approach.

Key Learning Objectives

  • Assess your product and team context to determine appropriate delivery models
  • Compare Scrum, Kanban, and hybrid approaches with clarity
  • Identify risk, uncertainty, and compliance factors influencing model choice
  • Align stakeholder expectations with delivery structure
  • Apply decision criteria to avoid “one-size-fits-all” thinking
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