Prompt Engineering for AI Professionalsin Birmingham

5 daysLive virtual trainingIntermediate

Classroom training and venue arrangements depend on the availability of a suitable conference hall in Birmingham, United Kingdom. Dates, seating capacity, facilities and the final venue are confirmed before booking.

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Birmingham offers a strong professional community, cultural heritage and accessible learning opportunities.

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Explore Prompt Engineering for AI Professionals

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 Birmingham, United Kingdom , 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…

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Learning from Birmingham

Birmingham offers a strong professional community, cultural heritage and accessible learning opportunities.

Course curriculum

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 Birmingham, United Kingdom.
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 Birmingham, United Kingdom.
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 Birmingham, United Kingdom.
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 Birmingham, United Kingdom.
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 Birmingham, United Kingdom.

Exam details

Exam Level: Intermediate – Prompt Engineering Professional
Exam Type: Online computer-based assessment consisting of multiple-choice questions and practical prompt engineering tasks in Birmingham, United Kingdom.
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 Birmingham, United Kingdom.

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Who this course is for

AI and Generative AI Professionals – Suitable for professionals who want to strengthen their prompt engineering capabilities and apply advanced AI interaction techniques in Birmingham, United Kingdom . AI/ML Engineers and Developers – Ideal for developers working with LLMs who want to improve prompt design, context management, structured outputs, and AI application workflows. Data and Business Analysts – Helps analysts use advanced prompting techniques for research, information extraction, analysis, reporting, and AI-assisted workflows in Birmingham, United Kingdom . IT and Technology Professionals – Designed for technology professionals seeking practical knowledge of LLM prompting, AI…

Before you begin

Generative AI Fundamentals – Basic understanding of Generative AI, Large Language Models (LLMs), and AI applications is recommended for learners in Birmingham, United Kingdom . 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…

Learning 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…

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Room facilities / classroom arrangements

General planning information. Availability is confirmed for your selected venue and batch.

Typical classroom arrangements — subject to confirmation for the selected batch: 1. Learning space and seating: A suitable room layout with seating and desk space for course discussions and exercises. 2. Presentation equipment: A display or projector for instructor-led explanations; equipment requirements are confirmed before delivery. 3. Internet and power: Connectivity and charging access where needed for the course’s digital resources or labs. 4. Collaboration tools: A whiteboard or flip chart for group activities, demonstrations and note-taking. 5. Room comfort: Appropriate lighting and ventilation, with breaks included in the agreed training schedule. 6. Access and learner needs: Accessibility, refreshments and any specific accommodation requirements should be discussed with the adviser in advance. This is general planning information. It does not confirm a particular venue, equipment package or included refreshments.

Course 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…

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Insights for Prompt Engineering for AI Professionals

Learning insight 01

Prompt Engineering for AI Professionals: Complete Guide to Advanced Prompting, LLMs, AI Automation & Generative AI

Prompt engineering is an essential skill for professionals working with Generative AI and Large Language Models (LLMs). It involves designing clear, structured, and context-rich instructions that help AI models produce more relevant, accurate, and useful outputs.

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