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.
Language models such as GPT are presented in the broader context of artificial intelligence and machine learning. The section explains how these models operate, how conversational models differ from other generative AI tools, and where their capabilities end. It also maps typical applications in knowledge-based and creative work.
Business use of AI is examined through concrete process areas such as text handling, data analysis and reporting across sales, marketing, HR, finance, administration and customer service. Participants identify where AI can improve daily operations while also considering implementation benefits, operational limits and associated risks.
Effective communication with AI depends on how clearly the request defines context, intention, goal and constraints. This part explains what a prompt is, how to ask for more accurate answers, and why precision matters. It also contrasts strong and weak prompt examples and highlights common communication mistakes.
Complex tasks are handled more effectively when prompts are built in stages instead of as single, broad instructions. Participants learn to define roles, provide input data, specify expected outputs and shape response formats such as tables, lists or reporting structures. Iterative refinement is used to improve precision and usability.
Writing with AI involves more than drafting text, because the real value often lies in revision, transformation and adaptation. This section covers emails, reports, notes and summaries, as well as shortening, expanding and rewriting content for different audiences. It also includes proofreading, error correction and longer-form materials.
Tables, text files and business documents often require extracting signals rather than reading everything line by line. Here the focus is on generating summaries, comparisons and interpretations, identifying key information, and formulating questions for source materials. Result verification and quality control are treated as part of the workflow.
Planning everyday work becomes easier when AI helps structure information and turn inputs into usable outputs. Participants practice building plans, schedules and checklists, producing meeting notes and task lists, and organizing knowledge. The section also addresses decision support, procedures, instructions and work templates.
Presentations, visual materials and communication assets can be drafted faster with AI support across writing, research and editing. The section also covers concepts for simple animations and video, along with generating quizzes, tests and educational materials. Attention is given to designing marketing, educational and internal content.
Starting from participants’ own job-related cases, the workshop develops prompts suited to specific professional objectives. It includes improving existing instructions, comparing working patterns and consolidating reusable solutions. The outcome is a practical prompt library that can be applied after the training.
AI agents extend beyond classic chatbots by handling multi-step tasks, connecting with tools and supporting business workflows. Participants examine business use cases, the shift from Agent Builder toward Agents SDK and ChatGPT workplace agents, plus the role of integrations, human oversight, safety and quality control.
Working with AI in an organizational setting requires clear rules for data protection, accountability and output validation. This part addresses GDPR-aligned handling of personal and confidential information, fact-checking and hallucination control, as well as risks tied to automated decisions, transparency, copyright and manipulation.
AI can be embedded into documents, forms, team processes and routine tasks to reduce manual work and improve consistency. The section focuses on selecting automation candidates, assessing business value, and defining team standards. It also outlines longer-term directions such as agents, model collaboration and process automation.
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.
