AI Fundamentals#1169
Artificial Intelligence Fundamentals Training Course
Gives leaders a solid grounding in core AI technologies, their practical business applications and the strategic value they can bring to an organization.
5 Days·Classroom
Introduction to Cutting-Edge AI Trends Training Course
Introduces the latest developments in artificial intelligence, their practical business uses and how they are reshaping organisational strategy today.
AIF · AI FundamentalsAll Levels#2645ClassroomEnglish , Arabic
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Free substitution at any time · 30+ days' notice: full refund minus 10%. Cancellation policy
Sectors:Artificial Intelligence & ApplicationsCategories:AI Fundamentals
Course Overview
The Introduction to Cutting-Edge AI Trends Training Course provides a comprehensive introduction to the latest developments in artificial intelligence and their growing influence on business operations, organisational strategy, and digital transformation. The programme explores emerging AI technologies, practical applications, and industry trends, helping participants understand how artificial intelligence is reshaping decision-making, productivity, innovation, and competitive advantage. The course examines key areas of AI advancement, including generative AI, large language models, autonomous AI agents, machine learning, deep learning, multimodal AI, and intelligent automation. Participants explore how these technologies work, where they create practical value, and how organisations can identify relevant opportunities without requiring an advanced technical background. Particular attention is given to the business applications of AI across finance, human resources, customer service, marketing, operations, project management, and strategic planning. Participants learn how AI can support data analysis, content creation, process optimisation, customer engagement, knowledge management, and informed decision-making. The programme also explores the evolving relationship between human expertise and AI-enabled capabilities, highlighting the importance of responsible adoption and effective human oversight. The course addresses the risks and governance considerations associated with emerging AI technologies, including data privacy, cybersecurity, algorithmic bias, intellectual property, transparency, and regulatory compliance. Participants examine practical approaches to evaluating AI solutions, assessing organisational readiness, and establishing appropriate controls to ensure that implementation aligns with business priorities and ethical standards. Through demonstrations, case studies, and practical exercises, participants develop a structured understanding of current AI trends and their potential organisational impact. The programme equips professionals with the knowledge to identify promising AI applications, assess emerging opportunities, and contribute effectively to AI adoption and digital transformation initiatives.
Learning Objectives
- Explain the fundamental concepts and current landscape of artificial intelligence.
- Identify major emerging AI trends and their potential business implications.
- Differentiate between generative AI, machine learning, deep learning, and autonomous AI agents.
- Examine the capabilities and limitations of large language models and multimodal AI systems.
- Identify opportunities to apply AI across business functions and organisational processes.
- Explore how AI supports automation, productivity, innovation, and data-driven decision-making.
- Evaluate AI tools and solutions according to organisational needs and business objectives.
- Develop effective approaches to using generative AI for research, analysis, communication, and content creation.
- Assess the implications of AI adoption for workforce capabilities, roles, and operating models.
- Recognise risks related to data privacy, cybersecurity, bias, reliability, and intellectual property.
- Apply responsible AI principles and governance considerations when evaluating AI initiatives.
- Develop an initial roadmap for identifying and prioritising AI opportunities within an organisation.
Who Should Attend
This course is designed for professionals seeking to understand emerging artificial intelligence technologies and their practical business applications, including:
Senior Executives and Business Leaders.
Department Heads and Functional Managers.
Digital Transformation Managers.
IT Managers and Technology Professionals.
Innovation and Strategy Specialists.
Data Analysts and Business Intelligence Professionals.
Human Resources and Talent Management Professionals.
Finance, Marketing, Sales, and Customer Experience Managers.
Operations and Project Management Professionals.
Risk Management, Compliance, and Governance Specialists.
Learning and Development Professionals.
Business Consultants and Management Advisors.
Entrepreneurs and Business Owners.
Professionals responsible for evaluating or implementing AI initiatives.
Learning Outcomes
- Describe the current AI landscape and distinguish established technologies from emerging developments.
- Explain the capabilities and practical applications of generative AI and large language models.
- Identify potential uses of autonomous AI agents and intelligent automation in business processes.
- Understand the role of machine learning, deep learning, and multimodal AI in solving business problems.
- Apply structured prompting techniques to improve the quality and relevance of AI-generated outputs.
- Identify opportunities to improve productivity, customer experience, and operational efficiency through AI.
- Assess AI tools based on functionality, reliability, suitability, and organisational requirements.
- Recognise the limitations of AI systems, including inaccurate outputs, bias, and inconsistent performance.
- Evaluate the implications of AI adoption for workforce planning, skills development, and organisational change.
- Identify key governance, privacy, cybersecurity, and intellectual property considerations.
- Establish preliminary criteria for measuring the business value of AI initiatives.
- Prepare an initial action plan for exploring and implementing suitable AI applications.
Course Outline
Artificial Intelligence Fundamentals & The Evolving AI Landscape
- Introduction to artificial intelligence and its evolution.
- Understanding the differences between traditional automation, machine learning, and generative AI.
- Overview of narrow AI, emerging capabilities, and the concept of artificial general intelligence.
- Core principles of machine learning and deep learning.
- Understanding neural networks and the role of training data.
- Introduction to natural language processing and computer vision.
- Overview of current AI adoption across major industries.
- Identifying common AI misconceptions, capabilities, and limitations.
- Understanding the strategic importance of AI for organisational competitiveness.
- Practical Application: Analyse selected business scenarios and identify where AI could create value, considering the business objective, available data, expected benefits, and potential limitations.
Generative AI, Large Language Models & Multimodal Technologies
- Understanding generative AI and how it produces new content.
- Introduction to large language models and their business applications.
- Exploring AI assistants for research, writing, summarisation, and analysis.
- Prompt engineering techniques for improving AI-generated responses.
- Introduction to multimodal AI for processing text, images, audio, and video.
- AI-powered content creation and knowledge management.
- Retrieval-augmented generation and its role in accessing organisational knowledge.
- Understanding model hallucinations, factual verification, and output quality.
- Selecting appropriate AI tools for different business tasks.
- Practical Application: Develop and test prompts for a business scenario involving research, document summarisation, information analysis, or professional communication, then evaluate the accuracy and usefulness of the results.
Emerging AI Trends, Autonomous Agents & Intelligent Automation
- Overview of emerging AI developments and their potential applications.
- Understanding autonomous AI agents and agent-based workflows.
- Differences between conversational assistants and AI agents that execute tasks.
- AI-driven workflow automation and process optimisation.
- Introduction to AI-powered decision support and predictive analytics.
- Exploring AI applications in finance, human resources, marketing, and operations.
- AI-enabled customer service and personalised customer experiences.
- Introduction to AI-assisted software development and technical problem-solving.
- Human oversight, task delegation, and managing AI-generated actions.
- Evaluating the feasibility of AI automation in organisational processes.
- Practical Application: Map a selected business process and develop a preliminary AI-enabled workflow, identifying suitable automation opportunities, required human approvals, expected benefits, and operational risks.
AI Strategy, Responsible Adoption & Risk Management
- Aligning AI opportunities with organisational strategy and business priorities.
- Assessing organisational readiness for AI adoption.
- Developing criteria for evaluating AI tools, platforms, and use cases.
- Data quality, privacy, confidentiality, and information security.
- Understanding algorithmic bias, fairness, and responsible AI practices.
- Managing inaccurate outputs, model limitations, and reliability risks.
- Intellectual property considerations and responsible content generation.
- AI governance, accountability, transparency, and human supervision.
- Understanding relevant regulatory developments and compliance responsibilities.
- Managing workforce implications, employee concerns, and organisational change.
- Practical Application: Conduct a preliminary risk assessment for a proposed AI use case, identifying business value, data requirements, privacy concerns, potential bias, human oversight measures, and governance controls.
AI Implementation Planning, Business Value & Future Readiness
- Identifying and prioritising high-value AI opportunities.
- Evaluating AI initiatives according to feasibility, impact, cost, and risk.
- Developing an initial AI adoption roadmap.
- Establishing pilot projects and testing AI solutions before wider deployment.
- Defining performance indicators for productivity, quality, efficiency, and user adoption.
- Measuring business value and evaluating the outcomes of AI initiatives.
- Building AI awareness and developing workforce capabilities.
- Integrating AI into existing workflows and organisational systems.
- Establishing monitoring, feedback, and continuous improvement mechanisms.
- Reviewing future AI developments and preparing for evolving capabilities.
- Final Workshop: Develop and present an initial AI adoption proposal for a selected organisation or business function, covering the identified opportunity, proposed AI application, expected business benefits, implementation priorities, risk controls, human oversight, success indicators, and recommended next steps.
Upcoming Dates
Selected date
Doha · 9 – 13 Nov 2026 · Classroom
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| City | Dates | Price per Participant | Early Bird | |
|---|---|---|---|---|
DammamScheduled | 2 – 6 Nov 2026 | €4,800 | — | |
DohaScheduled | 9 – 13 Nov 2026 | €4,700 | — | |
DubaiScheduled | 15 – 19 Nov 2026 | €4,700 | — | |
FrankfurtScheduled | 16 – 20 Nov 2026 | €6,200 | — | |
CairoScheduled | 22 – 26 Nov 2026 | €3,800 | €3,420until 2 Nov | |
GenevaScheduled | 23 – 27 Nov 2026 | €7,300 | €6,570until 2 Nov | |
HamburgScheduled | 30 Nov – 4 Dec 2026 | €6,200 | €5,580until 9 Nov | |
IstanbulScheduled | 7 – 11 Dec 2026 | €5,300 | €4,770until 16 Nov | |
JeddahScheduled | 13 – 17 Dec 2026 | €4,800 | €4,320until 23 Nov | |
Cape TownScheduled | 14 – 18 Dec 2026 | €7,700 | €6,930until 23 Nov | |
Kuala LumpurScheduled | 21 – 25 Dec 2026 | €4,700 | €4,230until 30 Nov | |
LondonScheduled | 28 Dec 2026 – 1 Jan 2027 | €5,800 | €5,220until 7 Dec | |
LisbonScheduled | 28 Dec 2026 – 1 Jan 2027 | €6,000 | €5,400until 7 Dec | |
CasablancaScheduled | 28 Dec 2026 – 1 Jan 2027 | €4,700 | €4,230until 7 Dec | |
MadinahScheduled | 4 – 8 Jan 2027 | €4,800 | €4,320until 14 Dec | |
MadridScheduled | 11 – 15 Jan 2027 | €6,000 | €5,400until 21 Dec | |
ErbilScheduled | 17 – 21 Jan 2027 | €4,000 | €3,600until 28 Dec | |
MakkahScheduled | 18 – 22 Jan 2027 | €4,800 | €4,320until 28 Dec | |
ManamaScheduled | 25 – 29 Jan 2027 | €5,300 | €4,770until 4 Jan | |
MarbellaScheduled | 1 – 5 Feb 2027 | €6,000 | €5,400until 11 Jan | |
KigaliScheduled | 8 – 12 Feb 2027 | €7,700 | €6,930until 18 Jan | |
MarrakeshScheduled | 8 – 12 Feb 2027 | €4,700 | €4,230until 18 Jan | |
MunichScheduled | 15 – 19 Feb 2027 | €6,000 | €5,400until 25 Jan | |
MilanScheduled | 15 – 19 Feb 2027 | €7,000 | €6,300until 25 Jan | |
MuscatScheduled | 22 – 26 Feb 2027 | €6,300 | €5,670until 1 Feb | |
OnlineScheduled | 28 Feb – 4 Mar 2027 | €2,700 | €2,430until 8 Feb | |
SalalahScheduled | 1 – 5 Mar 2027 | €6,300 | €5,670until 8 Feb | |
ParisScheduled | 8 – 12 Mar 2027 | €6,700 | €6,030until 15 Feb | |
AmmanScheduled | 14 – 18 Mar 2027 | €4,000 | €3,600until 22 Feb | |
Sharm El-SheikhScheduled | 22 – 26 Mar 2027 | €5,300 | €4,770until 1 Mar |
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