Certified Artificial Intelligence Professional
2–3 November 2026 • Hyatt Place, Westlands • USD 1,250 per participantThis 2-day workshop provides a comprehensive, hands-on introduction to Certified Artificial Intelligence Professional (CAIP) and its practical applications in today's digital world. Participants will gain a solid understanding of AI concepts, machine learning fundamentals, generative AI technologies, and real-world implementation strategies. Designed for professionals, students, and technology enthusiasts, the workshop focuses on practical skills, industry use cases, and responsible AI adoption.
The workshop begins with the foundations of Artificial Intelligence, exploring key concepts, terminology, and the evolution of AI technologies. Participants will then dive into machine learning principles, data-driven decision-making, generative AI tools, prompt engineering, and AI-powered business solutions. Throughout the program, attendees will engage in interactive exercises, demonstrations, and hands-on activities that reinforce learning and build confidence in applying AI tools effectively.
By the end of the workshop, participants will understand how AI systems work, identify opportunities for AI adoption within their organizations, leverage modern AI platforms to improve productivity, and apply best practices for ethical and responsible AI usage. Each day combines theory with practical application, ensuring participants leave with actionable knowledge and skills they can immediately use in their careers and businesses.
Introduction
This workshop will cover the core principles, technologies, and practices that drive modern Artificial Intelligence (AI). You will learn how AI systems are designed, developed, and deployed, while gaining practical knowledge in machine learning, deep learning, natural language processing (NLP), computer vision, robotics, AI governance, and risk management.
Throughout the workshop, you will explore real-world AI applications, participate in practical exercises, and work through hands-on demonstrations designed to reinforce key concepts. You will gain exposure to industry-relevant tools, methodologies, and frameworks used to build intelligent systems and support data-driven decision-making. In addition, you will receive resources and guidance to continue developing your AI expertise beyond the training.
These interactive sessions are designed to strengthen your understanding of AI technologies, improve your ability to identify and implement AI opportunities, and equip you with the skills needed to manage AI initiatives responsibly. The workshop encourages collaboration, discussion, and knowledge sharing, enabling participants to learn from both the instructor and fellow professionals from diverse backgrounds.
By the end of this workshop, you will understand the foundational and advanced concepts of Artificial Intelligence, be able to apply machine learning and deep learning techniques to real-world challenges, evaluate AI risks and ethical considerations, and align AI solutions with organizational objectives. This workshop is ideal for AI practitioners, data scientists, IT professionals, technology leaders, business decision-makers, and anyone seeking to build or advance a career in Artificial Intelligence.
Pre-requisites
A basic understanding of computer systems, data concepts, and information technology is recommended. Familiarity with programming, data analysis, or digital technologies can be beneficial but is not required. No prior experience in Artificial Intelligence or Machine Learning is necessary.
Who Is This Workshop For?
This workshop is designed for professionals and decision-makers who want to develop practical knowledge and skills in Artificial Intelligence and its business applications. It is particularly useful for:
- AI professionals involved in the development, deployment, or management of AI solutions
- Data scientists and data analysts seeking to expand their expertise in machine learning and deep learning
- IT managers and technology leaders overseeing AI initiatives and digital transformation projects
- Software developers and engineers interested in integrating AI into applications and business processes
- Risk, compliance, and governance professionals responsible for managing AI-related risks and regulatory requirements
- Business executives, including CIOs, CTOs, CEOs, and COOs, involved in AI strategy and decision-making
- Project managers leading AI implementation and innovation initiatives
- Aspiring AI practitioners and technology enthusiasts looking to build or advance a career in Artificial Intelligence
What Will You Learn?
By completing this workshop, you will gain a practical understanding of Artificial Intelligence concepts, technologies, and implementation strategies, enabling you to confidently apply AI solutions in professional and organizational settings.
You will learn:
- The foundational concepts, principles, and real-world applications of Artificial Intelligence
- How to analyze, prepare, and visualize data to support AI-driven decision-making
- The fundamentals of machine learning, including supervised and unsupervised learning techniques
- How deep learning models, neural networks, and advanced AI architectures are used to solve complex problems
- The principles and applications of Natural Language Processing (NLP), Large Language Models (LLMs), and generative AI technologies
- How computer vision and robotics systems enable intelligent automation and advanced decision-making
- Strategies for identifying, managing, and mitigating AI-related risks, privacy concerns, and compliance requirements
- Best practices for implementing ethical AI, governance frameworks, and AI strategies aligned with organizational goals
Business/Organization Benefits
Organizations that invest in AI capabilities gain a competitive advantage through improved efficiency, innovation, and data-driven decision-making.
This workshop will help your organization:
- Accelerate digital transformation initiatives through the effective adoption of Artificial Intelligence
- Improve operational efficiency and productivity by leveraging AI-powered automation and intelligent systems
- Enable better business decisions through data analysis, predictive insights, and machine learning applications
- Identify and manage AI-related risks while ensuring compliance with ethical, privacy, and regulatory requirements
- Develop internal AI expertise to reduce reliance on external resources and consultants
- Align AI initiatives with strategic business objectives to maximize value and return on investment
- Foster innovation by identifying new opportunities for AI-driven products, services, and process improvements
- Establish a strong foundation for responsible, scalable, and sustainable AI implementation across the organization
Requirements
A basic understanding of computer systems, information technology, and digital tools is recommended. No prior experience in Artificial Intelligence or Machine Learning is required.
For the best learning experience, participants are encouraged to use their own laptop to participate in hands-on exercises, demonstrations, and practical activities throughout the workshop. Individuals without suitable hardware can follow along using the instructor's live demonstration environment and guided examples.
General Information
- Certification and examination fees are included in the price of the training course
- An attestation of course completion worth 31 CPD (Continuing Professional Development) credits will be issued to the participants who have attended the training course.
- Candidates who have completed the training course but failed the exam are eligible to retake it once for free within a 12-month period from the initial date of the exam.
Trainer Profile
Remi Afon
(https://www.linkedin.com/in/remiafon/)
CISSP | CISM | CEH | PECB Certified Trainer | EC Council Certified Trainer | GIAC Cloud Security Automation Certification (GCSA) | SANS Gen AI & LLL Application Security
Remi Afon is a cybersecurity and artificial intelligence security professional, certified trainer and Founder of Lynsec, a PECB Partner. He specialises in AI security, responsible AI governance, cloud security, DevSecOps, application security and secure digital transformation.
Remi holds a BSc in Computer Science and an MSc in Information Security, complemented by specialist training in Artificial Intelligence for Cyber Security from the University of Oxford. His professional certifications include Certified Information Systems Security Professional (CISSP), Certified Information Security Manager (CISM), GIAC Cloud Security Automation Certification (GCSA), Certified Artificial Intelligence Professional, Certified ISO42001 and ISO27001 Lead Implementer and Certified Ethical Hacker (CEH). He is also a PECB Certified Trainer and EC Council Certified Trainer.
Through Lynsec, Remi delivers professional training in artificial intelligence, AI governance and cybersecurity, including the PECB Certified Artificial Intelligence Professional – CAIP®, ISO/IEC 42001 Artificial Intelligence Management Systems and ISO/IEC 27001 Information Security Management Systems programmes.
At ACDF 2026, Remi will lead the PECB/Lynsec CAIP® Intensive Training, combining academic knowledge, professional certification and practical industry experience to help participants understand AI technologies, manage emerging risks and support the secure, ethical and responsible adoption of artificial intelligence.
Workshop Itinerary
Day 1 [MORNING]:
SOC Foundations — Mission, Governance, Operating Model & Telemetry Strategy
We begin with the strategic foundations of the SOC: its institutional mandate, governance structure, and daily operating model, followed by a detection-driven approach to telemetry collection.
- Welcome and workshop overview
- SOC mandate, institutional role, and constituency mapping
- Governance structure, steering committee, and regulatory monitoring alignment
- Tiered SOC structure, roles, responsibilities, and escalation workflows
- Detection-driven telemetry strategy and identity-first monitoring
- Log onboarding prioritization, data quality, and normalization
- Hands-on: Draft SOC mission and charter; design escalation matrix; build phased telemetry onboarding roadmap
DAY 1 [AFTERNOON]:
Threat-Driven Detection Engineering & Detection Quality
The afternoon focuses on the full detection lifecycle — from threat-informed design through validation, deployment, tuning, and continuous improvement.
- Threat-informed detection strategy and coverage modeling with ATT&CK Navigator
- Detection engineering lifecycle: design, validation, deployment, tuning, improvement
- Detections-as-code concepts: versioning, testing, auditability
- Threat intelligence as input to detection development and enrichment
- Alert classification (True Positive / False Positive / Benign Positive / Undetermined) and outcome tagging
- Detection tuning methodology and the continuous improvement loop
- Hands-on: Map an attack scenario to detection logic and telemetry requirements; alert classification and tuning simulation
DAY 2 [MORNING]:
Triage, Investigation & Incident Response Integration
Day two moves into the operational heart of the SOC: structured triage, hypothesis-driven investigation, and integrated incident response.
- Alert prioritization models and investigation methodology
- Hypothesis-driven analysis, structured decision-making, and case documentation standards
- Coordination with digital forensics and specialized investigation functions
- Incident response lifecycle: containment, eradication, recovery
- Playbook design principles and post-incident improvement cycle
- Hands-on: Investigation decision-tree walkthrough with case documentation; build a phishing or credential-compromise response playbook
Day 2 [Afternoon]:
Resilient & Future-Ready SOC — Metrics, AI Augmentation & Capability Roadmap
The final session addresses modern SOC challenges, AI-augmented operations, performance measurement, and consolidates all workshop outputs into a phased capability roadmap.
- Encrypted traffic visibility limitations; cloud and identity-centric attacks
- AI-enabled threats, attacks targeting SOC tooling, and monitoring the monitoring systems
- AI-assisted investigation, automation vs augmentation, and phased AI adoption
- SOC metrics: MTTD, MTTR, detection performance, analyst workload, executive KPIs
- Advanced capability expansion: threat hunting, threat intelligence, purple teaming, digital forensics
- Hands-on: Identify controls to secure SOC infrastructure; identify 3 safe AI augmentation opportunities; build SOC KPI framework and phased 90-day / 12-month capability roadmap
- Wrap-up: consolidating workshop artifacts and next steps
