Day01
AI Foundations for And Big Data
- AI capabilities, limitations and business value
- Machine learning, generative AI and large language model concepts
- Selecting high-value AI use cases
- Data requirements and model inputs
AI-008
Artificial Intelligence and Machine Learning
PROGRAMME BROCHURE
Artificial Intelligence and Big Data
Five days of practical AI application, governance and implementation for And Big Data.
KAIZEN EUROPEAN ACADEMY
Executive & Professional Development
www.kaizeneurope.academy
01
Programme Overview
This five-day Kaizen European Academy programme is specifically about Artificial Intelligence and Big Data; AI is the core subject throughout all five days. Participants learn how artificial intelligence and generative AI can be applied to And Big Data, design practical workflows, evaluate tools and outputs, manage governance and risk, and build an implementation roadmap supported by hands-on exercises.
02
Learning Objectives
Explain the AI, generative AI and automation concepts most relevant to And Big Data.
Identify and prioritize high-value AI use cases in And Big Data.
Design practical human-AI workflows and validate AI outputs for And Big Data.
Manage privacy, bias, security, governance and human-oversight risks when using AI in And Big Data.
Build a practical AI pilot and implementation roadmap for And Big Data.
Who Should Attend
Professionals, specialists, supervisors and managers whose responsibilities involve artificial intelligence and big data or who need to build practical capability in this area.
Programme Methodology
Instructor-led explanation, facilitated discussion, subject-specific case studies, practical templates, individual and group exercises, simulations or technical scenarios where appropriate, peer review and a final implementation workshop.
Learning Outcomes
Explain the AI, generative AI and automation concepts most relevant to And Big Data. Identify and prioritize high-value AI use cases in And Big Data. Design practical human-AI workflows and validate AI outputs for And Big Data. Manage privacy, bias, security, governance and human-oversight risks when using AI in And Big Data. Build a practical AI pilot and implementation roadmap for And Big Data.
Prerequisites
No formal prerequisite is required. Relevant professional experience is helpful; technical courses may assume basic familiarity with the operating environment.
03
Course Outline
Day02
AI Use Cases and Workflow Design in And Big Data
- Prompt design and interaction patterns
- Human-AI workflow design
- AI-assisted analysis and decision support
- Automation and intelligent agents
Day03
AI Tools, Data and Automation for And Big Data
- Evaluating accuracy, hallucination and output quality
- AI governance and accountability
- Bias, fairness and responsible AI
- Privacy, confidentiality and information security
Day04
Responsible AI, Risk and Governance in And Big Data
- Model risk and human oversight
- AI adoption and change management
- AI value measurement and ROI
- Building an AI implementation roadmap
Day05
Applied AI Lab: And Big Data Implementation
- Vendor and platform evaluation
- AI policy and acceptable-use controls
- Practical AI workflow prototyping
- Scaling AI safely across teams
04
What You Will Receive
Programme learning materials
Practical resources and templates where applicable
Kaizen completion certificate
Participant support throughout the learning week
Kaizen European Academy
Executive & Professional Development across selected European destinations.
CONTACT & INFORMATION
Website: www.kaizeneurope.academy
Contact: www.kaizeneurope.academy/#contact