Weekend batches
October 2026
09:00–15:00 · flexible hours
$799per learner
24 Oct 2026
4 of 25 seats available
31 Oct 2026
10 of 25 seats available
Generative AI
Prompt Engineering for AI Professionals in Bulgaria
Prompt Engineering for AI Professionals is a practical, career-focused training course designed to help AI and technology professionals develop advanced skills for designing, testing, and optimizing prompts for Generative AI and Large Language Models (LLMs). Available in Bulgaria , the course explores prompt design, prompt patterns, Chain-of-Thought (CoT) techniques, context engineering, few-shot prompting, structured outputs, prompt evaluation, prompt security, and AI-assisted workflows. Participants learn how to improve model responses by providing effective instructions, relevant context, examples, constraints, and output formats. The training also covers practical approaches for developing reliable prompts for business and technical applications, including content generation, analysis, automation, and AI-powered solutions. Through hands-on exercises and real-world scenarios, learners can strengthen their ability to work effectively with modern AI systems. This course is suitable for AI engineers, developers, analysts, IT professionals, product teams, and other professionals seeking advanced prompt engineering capabilities in Bulgaria and beyond.
5 daysIntermediate4.8 · 1,000 reviews
Training calendar
Upcoming four-month course schedule
A new weekday and weekend batch starts every week. Each batch runs for 5 training days, based on the course duration of 5 days.
Weekend batches
November 2026
09:00–15:00 · flexible hours
$799per learner
07 Nov 2026
25 of 25 seats available
14 Nov 2026
25 of 25 seats available
21 Nov 2026
25 of 25 seats available
28 Nov 2026
25 of 25 seats available
Weekend batches
December 2026
09:00–15:00 · flexible hours
$799per learner
05 Dec 2026
25 of 25 seats available
12 Dec 2026
25 of 25 seats available
19 Dec 2026
25 of 25 seats available
26 Dec 2026
25 of 25 seats available
Weekend batches
January 2027
09:00–15:00 · flexible hours
$799per learner
02 Jan 2027
25 of 25 seats available
09 Jan 2027
25 of 25 seats available
16 Jan 2027
25 of 25 seats available
23 Jan 2027
25 of 25 seats available
30 Jan 2027
25 of 25 seats available
Course curriculum
What you’ll learn
5 daysIntermediate
- Module 1: Introduction to Professional Prompt Engineering
- Understanding prompt engineering and its role in Generative AI applications.
- Exploring LLM capabilities, limitations, and response behavior.
- Understanding prompt components, instructions, context, constraints, and expected outputs.
- Identifying professional applications of prompt engineering in Bulgaria.
- Module 2: Prompt Design Fundamentals
- Creating clear, specific, and goal-oriented prompts.
- Structuring prompts for different professional requirements.
- Using roles, objectives, constraints, examples, and output formats.
- Identifying and correcting common prompt design issues.
- Module 3: Advanced Prompting Techniques
- Exploring zero-shot, one-shot, and few-shot prompting.
- Applying role-based and instruction-based prompting.
- Using Chain-of-Thought and structured reasoning approaches.
- Designing prompts for complex problem-solving and analytical tasks.
- Module 4: Context Engineering
- Understanding the importance of context in LLM interactions.
- Organizing instructions, reference information, examples, and constraints.
- Managing long-context interactions and relevant information.
- Designing context-aware prompts for professional workflows in Bulgaria.
- Module 5: Prompt Optimization and Evaluation
- Evaluating AI responses for accuracy, relevance, clarity, and consistency.
- Iteratively refining prompts to improve output quality.
- Comparing different prompt strategies and response patterns.
- Developing practical approaches for prompt testing and optimization.
- Module 6: Prompt Engineering for Professional Applications
- Creating prompts for content generation, summarization, and research.
- Designing prompts for data analysis and information extraction.
- Developing prompts for software development and technical documentation.
- Applying professional prompting techniques across industries in Bulgaria.
- Module 7: Prompt Security and Safety
- Understanding prompt injection and related security risks.
- Identifying potential data leakage and manipulation scenarios.
- Designing safer prompts for sensitive and business-critical workflows.
- Exploring responsible AI practices for professional prompt engineering.
- Module 8: Structured Outputs and AI Workflows
- Designing prompts for tables, lists, JSON, templates, and other structured formats.
- Controlling response length, tone, style, and formatting.
- Connecting prompt strategies with repeatable AI-assisted workflows.
- Building structured prompting approaches for workplace applications in Bulgaria.
- Module 9: Prompt Engineering with Modern LLMs
- Understanding prompting differences across modern AI models.
- Adapting prompts to different model capabilities and context requirements.
- Exploring model-specific prompt optimization strategies.
- Applying transferable prompt engineering skills across AI platforms.
- Module 10: Advanced Prompt Engineering Project
- Analyzing a real-world professional AI use case.
- Designing, testing, and refining a complete prompt solution.
- Evaluating results and documenting the final prompting approach.
- Presenting a practical prompt engineering workflow relevant to Bulgaria.
Entry requirements and prerequisites
- Generative AI Fundamentals – Basic understanding of Generative AI, Large Language Models (LLMs), and AI applications is recommended for learners in Bulgaria.
- AI Tool Familiarity – Prior experience using tools such as ChatGPT, Google Gemini, Microsoft Copilot, or similar AI assistants is beneficial.
- Basic Technical Knowledge – Familiarity with software development, data analysis, APIs, or technology workflows can help participants understand advanced prompting concepts.
- Prompting Experience – Basic experience creating and experimenting with AI prompts is recommended before attending the course.
- Professional Experience – The course is particularly suitable for AI engineers, developers, analysts, IT professionals, product teams, and other technology professionals in Bulgaria.
- No Advanced Programming Required – Advanced programming expertise is not mandatory, although basic technical knowledge can support practical learning.
Career value
Reasons to choose this course
Master Professional Prompt Engineering
Develop advanced skills for designing effective prompts for professional AI workflows in Bulgaria.
Learn Context Engineering
Understand how to structure context, instructions, examples, and information to improve AI model performance.
Explore Advanced Prompting Techniques
Apply techniques such as Chain-of-Thought, role prompting, few-shot prompting, and structured prompting for complex tasks.
Build AI-Ready Problem-Solving Skills
Learn to translate business and technical requirements into precise AI instructions and workflows in Bulgaria.
Understand Prompt Security
Identify prompt injection, data leakage, manipulation, and other security considerations when working with AI systems.
Apply Prompts to Real-World Workflows
Practice prompt engineering for content, analysis, automation, development, research, and business applications.
Advantages
Turn learning into practical capability
Improve AI Response Consistency
Learn methods for creating repeatable prompt structures that produce more predictable and useful outputs across different tasks.
Optimize Complex AI Tasks
Develop approaches for breaking down sophisticated requirements into manageable AI-driven tasks and workflows.
Strengthen Context Management
Learn how to organize and provide relevant information so AI models can better understand complex professional requirements.
Enhance AI Workflow Design
Discover how prompts can be incorporated into structured workflows for analysis, documentation, decision support, and automation in Bulgaria.
Develop Cross-Platform Prompting Skills
Build adaptable prompt engineering knowledge that can be applied across different LLMs, AI assistants, and Generative AI platforms.
Support AI Career Growth
Build specialized knowledge that can complement existing technical, analytical, product, marketing, or business expertise and support AI-focused opportunities in Bulgaria.
Exam format & assessment
- Exam Level: Intermediate – Prompt Engineering Professional
- Exam Type: Online computer-based assessment consisting of multiple-choice questions and practical prompt engineering tasks in Bulgaria.
- Number of Questions: 40 questions
- Exam Duration: 90 minutes
- Passing Score: 70% (28 out of 40)
- Question Format: Multiple-choice questions covering prompt design, advanced prompting techniques, context engineering, prompt optimization, structured outputs, and prompt security.
- Practical Assessment: Candidates complete scenario-based tasks involving prompt creation, refinement, evaluation, context management, and professional AI workflows.
- Key Exam Topics: Prompt engineering fundamentals, zero-shot and few-shot prompting, Chain-of-Thought, context engineering, prompt evaluation, structured prompting, AI workflows, and prompt security.
- Prerequisites: Basic familiarity with Generative AI and Large Language Models (LLMs) is recommended.
- Assessment Platform: Online assessment through the StepMerit platform.
- Certification: Successful candidates receive a StepMerit Course Completion Certificate.
- Exam Preparation: Practical exercises, case studies, and prompt engineering projects help learners prepare for the assessment in Bulgaria.
Bring your learning together
Course conclusion
Prompt Engineering for AI Professionals provides a structured learning experience for professionals who want to develop advanced skills in designing, optimizing, and evaluating prompts for modern Generative AI and Large Language Models (LLMs). The course covers advanced prompting techniques, context engineering, prompt optimization, structured outputs, AI workflows, and prompt security, enabling learners to approach complex AI tasks with greater structure and precision. Through practical exercises and real-world scenarios, participants can apply prompt engineering techniques to content generation, research, software development, data analysis, documentation, and business workflows. Learners in Bulgaria can build transferable AI skills that complement existing technical, analytical, creative, product, and business expertise. The course also provides a foundation for exploring advanced areas such as LLM application development, AI agents, RAG, AI automation, and enterprise Generative AI. By completing this training, professionals can strengthen their understanding of effective human-AI interaction and develop practical capabilities for AI-enabled work environments.
Target audience
- AI and Generative AI Professionals
- AI/ML Engineers and Developers
- Data and Business Analysts
- IT and Technology Professionals
- Product Managers and Product Teams
- Project and Program Managers
- Marketing and Content Professionals
- AI Consultants and Solutions Professionals
- Researchers and Knowledge Professionals
- AI Enthusiasts and Career Professionals
Verified learning evidence
Expertise, recognition and learner outcomes
Course-specific expertise
- Professional & Training Experience: 5+ Years
- Course Training Experience: 120+ Hours of training focused on Prompt Engineering, Generative AI, LLMs, AI tools, context engineering, prompt optimization, and practical business applications.
- Candidates Trained: 180+ candidates, including AI professionals, developers, analysts, business professionals, product teams, IT professionals, and AI enthusiasts.
- Training Delivery Experience: Experienced in instructor-led online and classroom training with practical demonstrations, interactive exercises, assignments, case studies, and hands-on activities.
- Prompt Engineering Expertise: Practical knowledge of role-based prompting, zero-shot prompting, few-shot prompting, chain-of-thought techniques, structured prompting, prompt templates, and instruction design.
- Context Engineering: Experience in preparing relevant context, defining requirements, adding constraints, managing reference information, and improving AI response quality.
- LLM & Generative AI Expertise: Strong understanding of LLMs, tokens, context windows, AI-generated content, model interactions, response generation, and AI application workflows.
- AI Tools Experience: Hands-on experience with platforms such as ChatGPT, Gemini, Microsoft Copilot, and other Generative AI tools for professional and business use cases.
- Gold Business Use Cases: Practical training experience applying prompt engineering to market research, customer support, product content, business analysis, FAQs, sales communication, and information summarisation.
- Prompt Evaluation & Optimization: Experience evaluating AI outputs for accuracy, relevance, consistency, completeness, clarity, and usefulness, followed by iterative prompt refinement.
- Prompt Security & Responsible AI: Training experience covering prompt injection, sensitive information handling, hallucinations, bias, responsible AI usage, and human validation.
- Hands-On Project Guidance: Experience guiding learners through practical prompt engineering projects, business scenarios, AI workflows, prompt libraries, and real-world implementation activities.
- Assessment Experience: Experienced in evaluating learners through quizzes, assignments, practical prompt-building exercises, scenario-based activities, and project demonstrations.
Documented learner outcomes
- Problem Statement – A gold business handles large volumes of customer enquiries, product information, market updates, pricing-related questions, sales content, and internal business data. Employees may spend significant time researching information, preparing customer responses, analysing market trends, and creating business content. Poorly structured AI prompts can also produce inconsistent, incomplete, or inaccurate outputs. The challenge is to develop effective prompt engineering practices that enable AI tools to support gold business operations while maintaining accuracy, consistency, security, and human oversight.
- How We Overcame the Problem – Learners analysed common business requirements and designed structured prompts using clear roles, context, instructions, constraints, examples, and expected output formats. They experimented with different prompting techniques, evaluated AI responses, refined prompts, and introduced human validation to improve the reliability and usefulness of generated outputs.
- Overall Implementation – Learners implemented an AI-assisted gold business workflow covering business requirement → context preparation → prompt design → AI processing → response evaluation → prompt refinement → human validation → final business output.
- Market Research Prompting – Learners designed prompts to organise and summarise approved gold-market information, helping business teams quickly understand relevant trends and developments.
- Customer Query Assistance – Learners created structured prompts for generating consistent responses to customer enquiries related to gold products, jewellery, services, and general business information.
- Product Content Generation – Learners used prompt engineering techniques to generate product descriptions, promotional content, campaign ideas, FAQs, and customer-facing communication.
- Business Analysis – Learners developed prompts for summarising business information, comparing product characteristics, identifying trends, and producing structured analytical outputs.
- Role-Based Prompting – Learners configured AI roles such as market research assistant, customer support assistant, sales content specialist, and business analyst to improve task-specific responses.
- Context Engineering – Learners learned to provide relevant business context, reference information, constraints, and output requirements so that AI models could produce more useful and focused responses.
- Prompt Evaluation and Refinement – Learners compared different prompts, analysed generated responses, identified gaps, and iteratively refined instructions to improve accuracy, relevance, consistency, and completeness.
- Structured Output Generation – Learners designed prompts that produced information in predefined formats such as tables, bullet points, summaries, reports, FAQs, and business recommendations.
- Prompt Security and Responsible AI – Learners addressed risks such as prompt injection, sensitive-data exposure, misleading outputs, bias, hallucinations, and inappropriate AI-generated recommendations.
- Human-in-the-Loop Validation – Learners implemented review steps in which business users verify AI-generated market information, customer communication, and analytical outputs before they are used operationally.
- Evidence of Learning – Learners produced prompt templates, before-and-after prompt comparisons, AI-generated business content, market research outputs, customer-response examples, evaluation criteria, refined prompts, and workflow documentation as evidence of their practical prompt engineering capabilities.
- Overall Learner Outcome – By completing the implementation, learners demonstrated the ability to analyse AI use cases, design effective prompts, provide relevant context, apply advanced prompting techniques, evaluate and refine AI outputs, address prompt security risks, and develop responsible AI-assisted workflows for a realistic gold business scenario.
Helpful answers for planning your training
Frequently asked questions
It is an intermediate-level course focused on designing, optimizing, evaluating, and securing prompts for LLMs and Generative AI applications in Bulgaria.
AI professionals, developers, analysts, product managers, consultants, marketers, researchers, and technology professionals can benefit from this training.
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