ESSCA Certificate - Generative AI for Human Resources: from AI fundamentals to practical implementation

Participants will learn to:

• Understand the fundamentals of generative AI.
• Become familiar with the use of generative AI tools.
• Write effective prompts to guide generative AI models and improve the relevance of outputs.
• Apply different prompting techniques, including:
  • Chain-of-Thought Prompting
  • Chain-of-Density Prompting
  • OPRO (Optimization by Prompting)
  • Few-Shot Prompting

Understanding artificial intelligence

• Introduction to Artificial Intelligence, Machine Learning and Deep Learning.
• Distinguishing between narrow AI, general AI and automation.
• Overview of AI applications in organisations and HR.
• Addressing common misconceptions about AI.

Mapping AI use cases in HR

• Review AI tools used in recruitment, learning and talent management.
• Identify opportunities and challenges associated with different HR use cases.
• Consider ethical and operational implications.

AI in recruitment: applications and challenges

• How CV screening and matching tools work.
• Recruitment chatbots and interview automation.
• Case studies illustrating the use of AI in recruitment.
• Practical exercise using an AI-based CV screening tool.

Algorithmic bias and regulation

• Understanding algorithmic bias through practical examples.
• Legal and regulatory considerations, including GDPR and algorithmic transparency.
• Analysis of a real-world case involving AI-related discrimination.
• Approaches to reducing bias in recruitment processes.
• Developing guidelines for the ethical use of AI in HR.

AI for learning and development

• Adaptive learning and personalised training.
• Skills monitoring and learning analytics.
• Designing AI-supported learning pathways.
• Developing a training plan incorporating AI tools.

Performance management and workforce planning

• The impact of AI on jobs and organisational functions.
• Identifying roles that may be transformed by AI.
• Mapping future skills needs within an organisation.
• Developing competency frameworks for emerging roles.

Why collect HR data?

• Supporting recruitment and internal mobility.
• Monitoring employee performance and engagement.
• Anticipating workforce changes and supporting workforce planning.

Collecting HR data

• Internal sources: HR information systems, surveys, feedback and talent management tools.
• External sources: benchmarking, professional networks and labour market trends.
• Challenges related to data quality, bias and GDPR compliance.

Identifying and structuring data

• Identifying relevant data for specific HR use cases, such as turnover prediction.
• Ensuring the reliability and usability of data.

Using data to support decision-making

• Compiling and analysing HR data.
• Using tools and methods to structure HR data.
• Creating and interpreting HR performance indicators and dashboards.
• Introduction to predictive analytics and machine learning in HR.

Building a data-driven HR dashboard

• Using a sample dataset to create visualisations and dashboards.