Scrum Master, Scrum Product Owner, and Fundamentals of AI

Course overview

This training combines Scrum Master and Scrum Product Owner with fundamentals of Artificial Intelligence (AI) and imparts in-depth knowledge in agile team leadership and product responsibility, as well as foundational knowledge of artificial intelligence. It covers the responsibilities of the Scrum Master in team coaching and conflict management, as well as the tasks of the Product Owner in product backlog management and central AI concepts such as machine learning and generative AI. Additionally, prioritization methods, stakeholder communication, and scaling agile projects are taught, along with AI ethics, data protection, and the business case for AI. The content connects agile methodological competence with technological understanding of AI. The length of the training depends on the composition of the course modules and individual prior knowledge. Agile Scrum Master o Agile mindset and continuous process improvement o Responsibilities of the Scrum Master, team coaching, and conflict management o Agile estimation, planning, monitoring, and controlling the backlog o Scaling agile projects and tool integration in complex endeavors o Introduction of Agile in organizations and promotion of self-organization o Exam preparation and certification: Agile Scrum Master Agile Scrum Product Owner o Agile mindset and other agile frameworks such as Kanban, SAFe, and LeSS o Tasks and responsibilities of the Product Owner in the Scrum team o Product backlog management from vision to user stories and epics o Prioritization of requirements and stakeholder communication o Management of complex product and service backlogs as well as value creation (business value) o Exam preparation and certification: Agile Scrum Product Owner EXIN BCS Artificial Intelligence Foundation o Fundamentals of Artificial Intelligence (AI) o Terminology, history, and types of AI, as well as its societal significance and sustainable AI o AI ethics, bias, data protection, ethical principles, regulation, and risk management for AI o Application examples, robotics, basics of machine learning, as well as supervised, unsupervised, and semi-supervised learning o Data quality, data risks, data governance, big data, data visualization, large language models, generative AI, and AI training o Business case for AI, stakeholders, project management approaches, risks, costs, benefits, as well as AI governance and implementation o Career opportunities, practical examples, future impacts of AI, as well as AI awareness and ethical issues o Exam preparation and certification: EXIN BCS Artificial Intelligence Foundation Next step: Request a non-binding consultation for individual course composition and flexible start dates. This training can be combined with other courses from our offerings in IT and project management (PRINCE2®, ITIL®, Kanban, DevOps) as well as Microsoft® Office. Through the Qualification Opportunities Act, completing the training is also possible alongside work.

Upcoming dates

• 2026-10-25T23:00:00.000Z · 2027-01-14T23:00:00.000Z · Düsseldorf · Combined Learning
• 2026-10-25T23:00:00.000Z · 2027-01-14T23:00:00.000Z · Nürnberg, Mittelfranken · Combined Learning
• 2026-10-25T23:00:00.000Z · 2026-12-03T23:00:00.000Z · Hannover · Combined Learning
• 2026-10-25T23:00:00.000Z · 2026-12-03T23:00:00.000Z · Stuttgart · Combined Learning
• 2026-10-25T23:00:00.000Z · 2026-12-03T23:00:00.000Z · Nürnberg, Mittelfranken · Combined Learning