AI Bootcamp: AI for Executives

 

The Executive AI Bootcamp is an intensive 2.5-day program designed for business participants that are ready to turn AI from a buzzword into a strategic advantage. Through 11 focused sessions, participants gain a clear, technical understanding of how modern AI systems operate, how machine learning models are built and validated, and what differentiates successful AI initiatives from costly failures. The program takes a bottom-up approach, showing how foundational technical decisions drive business outcomes.

The bootcamp blends technical insight with executive decision-making, covering topics such as data readiness, workflows, infrastructure, team design, and the key drivers of business value. Interactive debates and panels provide opportunities to challenge assumptions and learn from scientific and real-world AI deployments.

Participants also explore responsible AI, practical strategies for scaling AI across the enterprises, and the latest trends shaping the future of AI. The program ends with a group exercise where teams design an AI initiative for their organization – leaving participants not just informed, but ready to act.

Who is it for?

The Executive AI Bootcamp is designed for senior professionals who need to make informed, high-stakes decisions about AI without becoming hands-on engineers. It is ideal for leaders who are accountable for AI outcomes and want to understand what is happening “under the hood” well enough to challenge assumptions, evaluate proposals, and steer initiatives toward real business value.

The program is particularly relevant for executives and decision-makers operating at the intersection of strategy, technology, and operations where AI investments succeed or fail based on data quality, system design, governance, and organizational readiness rather than hype or tooling alone.

Syllabus

  • Introduction to AI and modern machine learning systems
  • How machine learning models work: algorithms, training, and tuning
  • Data, features, exploratory analysis, and preprocessing
  • Model validation, metrics, and common failure modes
  • ML projects in practice and hidden technical debt
  • ML infrastructure, MLOps, and deployment considerations
  • Responsible AI, governance, and model risk management
  • Future trends in AI and their business implications
  • Interactive sessions

What will you learn

  • understand how modern ML systems function, why they fail and what they require
  • evaluate data quality, readiness and infrastructure maturity
  • interpret model metrics and identify misleading KPIs
  • recognize technical debt and assess ML system health
  • align ML accuracy with real business value and ROI
  • lead and support ML teams effectively across the lifecycle
  • understand regulatory obligations and responsible AI principles
  • design high-level AI initiatives grounded in technical and organizational reality

Prerequisites

  • no coding or data science background required
  • familiarity with business analytics or digital transformation concepts is helpful
  • experience in a managerial, strategic, or decision-making role
  • willingness to engage in technical discussions at a conceptual and architectural level

Pricing

  • 1.200 EUR per person (w/o VAT) includes:
    • 20h course over three days
    • course materials (presentations, supplementary materials)
    • lunch
    • shareable certificate

Schedule

Track Record & References

Applied AI Systems

 

 

  • 10+ applied AI and data-driven projects

  • End-to-end ML system design: data, models, validation, deployment

  • Focus on reliability, robustness, and real-world constraints

  • Experience with systems evaluated in operational environments

Projects & Collaboration

 

 

  • Participation in 20+ national and EU-funded R&D projects

  • Collaboration with industry and public-sector partners

  • Applied work in energy systems, infrastructure, and optimization

  • Transfer of research results into decision-support contexts

Research & Executive Expertise

 

  • 50+ peer-reviewed scientific publications

  • Expertise in AI performance metrics, risk, and failure modes

  • Experience in executive and professional education

  • Emphasis on realistic capabilities and responsible AI use

The Executive Edition builds on applied research and project experience, emphasizing realistic AI capabilities, limitations, and decision-relevant insight.

Meet the team

Assoc. Prof., Ph.D.

VINKO LEŠIĆ

 

Vinko Lesic

Ph.D.

HRVOJE NOVAK

 

Hrvoje Novak

Asst. Prof., Ph.D.

ANITA BANJAC

 

Anita Banjac

Prof., Ph.D.

MARIO VAŠAK

 

Mario Vašak

Contact

Address

 

Laboratory for Renewable Energy Systems (LARES)
Faculty of Electrical Engineering and Computing
Unska 3
HR-10000 Zagreb
Croatia
Address
(temporary)
Laboratory for Renewable Energy Systems (LARES)
Faculty of Electrical Engineering and Computing
Banjavčićeva 1A
HR-10000 Zagreb
Croatia
Phone +385 99 734 8453
Email hrvoje.novak@fer.unizg.hr