AI Course Artificial Intelligence and GPT in Practice. Prompt Engineering

Training process

Training needs analysis

If you have specific requirements regarding the training programme, we will carry out a training needs analysis for you. This will guide us on which aspects of the programme should receive greater emphasis, so that the training programme meets your specific needs.

What will you gain?

Confident AI use - You will understand how GPT models work and how they differ from other AI tools, so you can choose the right solution for each task and avoid unrealistic expectations.

Stronger prompting - You will learn to write precise prompts with clear goals, context, and output formats, helping you get useful results faster and reduce the number of revisions in daily work.

Faster content editing - You will speed up writing emails, reports, descriptions, and summaries, and learn how to shorten, expand, and adapt tone so your text fits the audience and business purpose.

Document and data analysis - You will learn how to use AI to extract key information from documents, tables, and text files, create concise summaries, and prepare structured overviews and interpretations faster.

Better work organization - You will use AI to build plans, checklists, schedules, meeting notes, and task lists, making it easier to organize information and move from ideas to concrete actions more efficiently.

AI-assisted materials - You will discover how to use AI to prepare presentation content, quizzes, visual assets, and simple multimedia materials, making your work outputs more engaging and easier to produce.

Safer AI usage - You will learn to spot risks related to hallucinations, personal data, copyright, and responsibility for generated content, so you can use AI more carefully and in line with good practice.

Practical AI adoption - You will see how to embed AI into daily processes, document work, and task automation, so you can save real time and build practical use cases for your team or organization.

Training programme

1. Introduction to artificial intelligence and language models

what is artificial intelligence and machine learning?
how do GPT-type language models work?
differences between conversational models and generative AI tools,
capabilities and limitations of language models,
areas of AI application in intellectual and creative work.

2. Applications of AI in business practice

automation of tasks related to text processing, data analysis and reporting,
support for the work of departments: sales, marketing, HR, finance, administration and customer service,
examples of AI applications in everyday company processes,
benefits, limitations and risks associated with implementing AI in the organization,
identification of tasks that can be improved with the help of AI.

3. Fundamentals of Prompt Engineering – how to effectively communicate with AI

what is a prompt and how to formulate it correctly?
the role of context, goal, intention and precision of the instruction,
how to ask questions to obtain more accurate answers?
examples of effective and ineffective prompts,
the most common mistakes in communication with AI.

4. Creating advanced prompts step by step

breaking down complex tasks into stages,
creating roles and personas in prompts,
providing input data and specifying the expected result,
formatting responses: tables, lists, summaries, reporting structures,
iterative improvement of prompts and refining results.

5. Editing and transforming content with the help of AI

writing and editing texts: emails, reports, descriptions, summaries, notes,
creating alternative versions, shortening and expanding content,
adapting the style and tone of expression to the recipient,
language proofreading, correcting errors and optimizing messages,
generating longer text forms: articles, scripts, reports and informational materials.

6. Data and document analysis

working with tables, text files and documents,
generating compilations, summaries and interpretations,
extracting key information from documents,
creating questions for data and documents,
verification of the correctness of answers and quality control of results.

7. Work organization and information management

creating plans, checklists and schedules,
generating notes, meeting summaries and task lists,
organizing information and creating knowledge structures,
AI support in decision-making and generating proposed solutions,
preparing instructions, procedures and work templates.

8. AI-supported resource and multimedia creators

creating content for presentations, graphic materials and visualizations,
preparing concepts for simple animations and video materials,
generating tests, quizzes and teaching materials,
AI support in writing, information retrieval and content editing,
designing communication, educational and marketing materials with the help of AI.

9. Prompting workshops

creating prompts for the specific professional goals of the participants,
optimizing existing prompts,
workshop-based work on participants' examples,
building a library of ready-to-use prompts for use after the training,
discussion of good practices and work patterns with AI.

10. Ethics, safety and law in the use of AI

what are AI agents and how do they differ from classic chatbots?
examples of AI agents' applications in business: information analysis, process handling, preparation of materials, decision support and automation of repetitive tasks,
current changes in the ecosystem of agent tools – Agent Builder is being phased out, and its place is being taken by Agents SDK and ChatGPT workplace agents,
Agents SDK as a tool for building, orchestrating and developing AI agents performing multi-step tasks,
ChatGPT workplace agents, i.e. agents operating in the ChatGPT work environment, supporting the automation of repetitive workflows, work with company tools and execution of team tasks,
the role of integration with documents, applications, data sources and business processes,
safety, human oversight and quality control in working with AI agents.

11. Integration of AI with daily work

protection of personal data and confidential information – good practices compliant with GDPR,
responsibility for content generated by AI,
fact verification and limiting so-called hallucinations,
risks associated with decision automation,
ethical challenges: transparency, manipulation, copyright,
safe use of AI tools in the organizational environment.

12. Integration of AI with everyday work

integration of AI with documents, forms, processes and everyday tasks,
designing simple automation scenarios,
creating standards for the use of AI in the team,
selection of tasks for automation and assessment of their profitability,
directions of AI technology development: agents, model collaboration, process automation and long-term applications in the organization.

What are the prerequisites for participating in the training?

Basic computer skills - You should be comfortable using a computer, web browser, and text editor so you can work smoothly with AI tools, files, and written content throughout the training.

Text work experience - You should have experience writing or editing emails, notes, reports, or descriptions, because the training focuses on practical content creation and transformation with AI.

Office workflow basics - You should understand typical office tasks such as preparing summaries, plans, lists, and documents, so you can easily apply the exercises to your own daily work.

Readiness to experiment - You should be willing to test different prompt versions and review AI responses on your own, because the training includes hands-on prompt improvement using real examples.