The programme has been approved by the HRDA as Vital Importance. Enterprises/organisations participating with their employees who satisfy HRDA's criteria, are entitled to subsidy.
Webinar's Overview
Practical AI & Analytics for Business Management provides managers and senior executives with hands-on experience in using Artificial Intelligence, business analytics and Generative AI tools in real organisational settings.
The programme focuses on the practical and technical aspects that managers need in order to work effectively with AI-enabled tools and analytical outputs. Participants will learn how to structure and prepare business data, define measurable KPIs, perform exploratory and diagnostic analysis, develop and evaluate basic predictive models using no-code/low-code tools, interact effectively with Generative AI applications, and assess the reliability of AI-generated outputs.
Through live demonstrations, guided exercises and business cases, participants will work with practical examples involving business datasets, predictive analytics, AI assistants and workflow automation. Particular emphasis is placed on understanding how AI tools actually process business information, how their outputs should be interpreted and validated, and how managers can identify technical, operational, privacy and governance risks before introducing them into organisational processes.
By the end of the programme, participants will have practical experience in moving from business data and operational problems to analytical outputs, AI-assisted workflows and structured implementation plans.
Webinar's Goals
By the end of the webinar, participants will be able to:
- Structure business problems so that they can be addressed using AI and analytics tools.
- Prepare and organise business data for analytical use and identify common data-quality problems.
- Define and calculate relevant business KPIs and interpret patterns, trends and anomalies in business datasets.
- Apply no-code/low-code analytics tools to develop basic predictive models for business applications.
- Interpret model outputs and understand fundamental concepts such as training and testing data, prediction accuracy and model limitations.
- Use Generative AI tools to analyse information, summarise business data, generate structured outputs and support operational tasks.
- Design and test effective prompts for different managerial and analytical tasks.
- Verify AI-generated outputs and identify hallucinations, incomplete responses and potentially unreliable results.
- Map business processes and identify activities where AI-assisted automation can be technically and operationally feasible.
- Assess AI applications in terms of data requirements, privacy, security, bias, reliability and human oversight.
- Develop a structured implementation plan for introducing an AI or analytics use case within their organisation.
Participants*
The programme is intended for managers and senior executives who are involved in strategic decision-making, operational management and organisational development.
Suitable participants include:
- Chief Executive Officers (CEOs),
- Managing Directors,
- General Managers,
- Department Managers,
- Operations Managers,
- Strategy Managers,
- Innovation Managers,
- IT Managers,
- Finance Managers,
- HR Managers and
- Business Unit Leaders.
The programme is also suitable for business owners and senior professionals who participate in planning, performance monitoring, digital transformation initiatives or innovation projects.
Participants should have responsibility for improving organisational performance, introducing new technologies, managing risks or leading change initiatives within their organisations. Places are limited and will be allocated based on availability.
All participants should be currently employed.
*The number of participants is restricted to 28.
**The maximum number of participants, eligible for HRDA subsidy, per company is 3.
Agenda
Day 1
1. Business Data Preparation, KPI Analysis and AI Readiness From a business problem to an analytical problem: defining inputs, outputs and measurable objectives (3 h)
- Understanding business datasets: variables, records, data types and data sources
- Data preparation for AI and analytics applications
- Identifying missing values, duplicates, inconsistent records and outliers
- Defining and calculating business KPIs
- Exploratory analysis: distributions, trends, correlations and anomalies
- Translating analytical findings into operational insights
- Case study
- Workshop
- Discussion
2. Predictive Analytics and No-Code AI Modelling (3 h)
- Understanding predictive analytics through practical business examples
- From historical business data to prediction: features, target variables and outcomes
- Predictive Analytics
- Introduction to AutoML and no-code/low-code modelling environments
- Demonstration of internationally used tools
- Explanation of how such tools can reduce decision-making time in international companies
- Case study
- Workshop
- Discussion
Day 2
3. Generative AI, Prompt Engineering and Workflow Automation (3 h)
- Introduction to Generative AI
- Demonstration of widely used Generative AI and GPT-based tools
- Explanation of productivity gains achieved internationally
- Prompt Engineering: designing and testing effective prompts
- Mapping business processes and identifying opportunities for AI-assisted workflow automationAI limitations: Hallucinations
- Case study
- Workshop
- Discussion
4. AI Implementation, Technical Controls (3 h)
- Selecting an appropriate AI use case: business value, data availability and technical feasibility
- Mapping the data required for an AI application
- Identifying systems and processes that need to interact with the AI solution
- Understanding APIs, integrations and data flows at managerial level
- Human-in-the-loop design and approval points
- AI output validation and quality-control mechanisms
- Privacy and confidential business information when using AI tools
- Security considerations when connecting organisational data to AI applications
- Bias, transparency and traceability of AI-generated outputs
- Defining performance indicators for an AI implementation
- Monitoring AI performance after deployment
- Case study
- Workshop
- Discussion
Follow-up Consultation Session
Please note that this is a compulsory follow-up consultation session for all participants who need to attend at least 90% to be eligible for the HRDA subsidy. This 4h follow-up workshop session will be held on a mutually agreed date with each participating company, within 4 months following the last day of the training. The session must be held at the registered address of the company’s premises. During the in-house session, the trainers will follow a structured consulting approach to understand each participating organization and company and identify opportunities for practical application of the methodologies presented during the institutional (theoretical) part of the program. Initially, the trainer will collect information about the organizational structure, reporting lines, decision-making processes and the roles of key departments. This will help identify how strategic and operational decisions are currently made and how data is utilized within the organization.
Services
Our services include:
- Digital training materials, including presentations, examples, case studies, exercises, and additional notes, where applicable.
- Provision of relevant course materials and resources in electronic format.
- Professional webinar platform and technical support to facilitate smooth delivery.
- Interactive online training environment.
- Certificate of Completion.
Registration & Contact
If you wish to register for the webinar, please complete the registration form.
Once your registration is submitted, you will receive an email stating how to proceed with your HRDA registration through the Ermis platform. Upon completion of this step, you will receive a confirmation email which will include the participation fee, including any discounts, if applicable. Kindly note that the payment should be settled at least two days prior to the webinar’s date for your registration to be confirmed.
The programme has been approved by the HRDA. Enterprises participating with their employees who satisfy HRDA’s criteria, are entitled to subsidy. Please note that there are limited seats available, therefore enroll in this seminar as soon as possible.
If you do not receive our confirmation e-mail regarding your registration, your participation cannot be guaranteed.
Cost
€1600 + VAT (19%) for all participants who are not eligible for the HRDA subsidy. Special discounts may apply.
100% subsidised by HRDA as a “Vital Importance Training” and offered free of charge for all eligible participants.
Participants should only proceed with settlement of payment if they are aware, prior to the training, that they are not eligible.
If, after the subsidy claim stage, the HRDA refuses to grant the subsidy for any participant—due to reduced attendance hours, de minimis limits, or any other reason—then the cost must be covered by those participants.
Participants who are not eligible for the subsidy are kindly asked to reach out to the Academy on +357 22 207 460 or at academy@kpmg.com.cy
HRDA Note
All individuals who wish to attend our HRDA approved training courses, should not only fill out our registration form, but also complete the registration process through the ERMIS platform in order to be approved by the HRDA. Regardless of whether they are claiming the HRDA subsidy or not, each participant will need to complete their registration through ERMIS as a physical person and then register to our training in order to be able to attend (either as an employee whose company is claiming the subsidy or as an individual who is not claiming the subsidy). Please reach out to the HRDA Ermis officers on 22 390 300 for more details regarding the registration as a physicalperson.
In accordance with the new requirements of the Human Resource Development Authority of Cyprus (HRDA), participants should be prepared to turn on their cameras during webinars, as unannounced attendance checks may be conducted at any time during the session.
Eligibility of self‑employed individuals: The Schemes are open to any natural person who is registered as self‑employed with the Social Insurance Registry and carries out their activities in areas controlled by the Republic of Cyprus.
Contact
For any queries, please contact KPMG Academy on +357 22 207 460 or at academy@kpmg.com.cy
CPD
This webinar may contribute to Continuing Professional Development requirements. At the end of the webinar participants will be given a certificate of attendance confirming the total number of training hours (16 CPD).
Trainer
Prof. Sotirios Bersimis,
Department of Business Administration, University of Piraeus
Prof. Sotirios Bersimis combines academic excellence in statistics, artificial intelligence and business analytics with extensive senior management experience in healthcare, digital transformation and strategic decision-making. His expertise spans industrial and health statistics, business analytics, process monitoring, innovation, organizational change and data-driven management. His academic work includes more than sixty publications in international scientific journals, five books and over seventy presentations at international conferences, while his teaching covers areas including Business Analytics, Industrial Statistics and Health Statistics.
Beyond academia, Prof. Bersimis has held major executive and public-sector leadership positions. He served as President and CEO of the Hellenic Organization for Health Care Services Provision (EOPYY), one of Europe’s largest social security organizations, responsible for healthcare services for approximately 11 million citizens and an annual budget of €5.5 billion. He also served as President of the European Healthcare Fraud and Corruption Network and as Managing Director of Bioiatriki Healthcare Group. Across these roles, he applied statistics, real-world evidence, process reengineering and digital transformation to improve organizational performance, quality and decision-making.
For his professional contribution, he received the 2018 Best Manager Award from the European Network for Business and Industrial Statistics (ENBIS), recognising his advancement of statistics in management. His distinctive combination of academic rigor, executive leadership and hands-on experience in analytics-driven transformation enables managers and organisations to translate complex data into practical strategic decisions.
