Prompt Engineering and Advanced Prompt Design Training Course

Prompt Engineering and Advanced Prompt Design Training Course

Introduction

Prompt Engineering and Advanced Prompt Design Training Course provides a practical, hands-on pathway for professionals seeking to master Generative AI, Large Language Models (LLMs), AI productivity, prompt optimization, AI-assisted decision-making, and intelligent automation. As organizations increasingly integrate tools such as conversational AI, enterprise copilots, and AI agents into daily workflows, the ability to communicate precisely with AI systems has become a critical digital competency. This course moves beyond basic prompting to explore structured prompts, role prompting, contextual prompting, few-shot learning, chain-of-thought alternatives, prompt chaining, reasoning frameworks, multimodal prompting, retrieval-augmented generation (RAG), and AI workflow design. Participants learn how to transform vague requests into precise, reliable, context-aware instructions that generate higher-quality and more actionable outputs.

The course also develops advanced prompt design capabilities for real-world organizational applications, including research, content creation, analysis, customer service, business intelligence, programming, reporting, knowledge management, and strategic planning. Through practical exercises and industry-focused case studies, participants learn how to test, evaluate, refine, version, and govern prompts while addressing hallucinations, ambiguity, bias, data privacy, security, and responsible AI considerations. By the end of the training, learners will be equipped to build reusable prompt libraries, prompt templates, AI workflows, evaluation frameworks, and advanced AI-assisted solutions that improve productivity, consistency, creativity, and operational efficiency.

Course Duration

5 days

Course Objectives

By the end of the course, participants will be able to:

1. Master prompt engineering fundamentals and core Generative AI concepts. 
2. Design high-quality structured prompts for diverse professional use cases. 
3. Apply role prompting, context engineering, and instruction hierarchy effectively. 
4. Use zero-shot, one-shot, and few-shot prompting to improve AI outputs. 
5. Develop advanced prompt chaining and workflow orchestration techniques. 
6. Apply reasoning-oriented prompting frameworks without relying on unsupported assumptions. 
7. Optimize prompts for accuracy, relevance, consistency, and task completion. 
8. Design prompts for multimodal AI, including text, images, documents, and structured data. 
9. Build reusable prompt templates, libraries, and standardized prompt assets. 
10. Apply prompt evaluation, testing, benchmarking, and iterative optimization. 
11. Reduce AI hallucinations, ambiguity, bias, and unreliable outputs through better prompt design. 
12. Integrate prompting with RAG, AI agents, automation, and enterprise AI workflows. 
13. Implement responsible AI, privacy, security, governance, and human-in-the-loop controls. 

Target Audiences

1. Business leaders and executives. 
2. AI and digital transformation professionals implementing enterprise AI solutions. 
3. Managers and team leaders looking to improve AI-enabled productivity. 
4. Data analysts, researchers, and business intelligence professionals working with AI-assisted analysis. 
5. Content creators, marketers, and communications professionals using Generative AI. 
6. Software developers, product managers, and technology professionals designing AI-powered applications. 
7. Consultants, trainers, educators, and knowledge workers integrating AI into professional workflows. 
8. Entrepreneurs and innovation professionals developing AI-enabled products and services. 

Course Modules

Module 1: Foundations of Prompt Engineering

• Understanding Generative AI, LLMs, tokens, context windows, and model behavior
• Principles of effective AI-human interaction
• Anatomy of a high-performance prompt 
• Instructions, context, constraints, inputs, and desired outputs 
• Identifying common prompting mistakes and failure patterns 
• Case Study: Transforming an unclear business request into a structured AI prompt that produces a consistent executive report.

Module 2: Core Prompt Design Techniques

• Zero-shot, one-shot, and few-shot prompting 
• Role and persona prompting 
• Contextual prompting and task decomposition 
• Output formatting and constraint specification 
• Prompt specificity, clarity, and precision 
• Case Study: Designing prompts that enable an AI assistant to classify and respond consistently to customer-service inquiries.

Module 3: Advanced Prompt Engineering Frameworks

• Advanced reasoning and decomposition strategies
• Step-by-step task structuring without exposing private reasoning 
• Prompt chaining and sequential workflows 
• Self-checking and verification instructions 
• Multi-stage prompting for complex tasks 
• Case Study: Building a multi-stage prompt workflow that converts raw research material into an executive-ready briefing.

Module 4: Context Engineering and Knowledge Grounding

• Context engineering for reliable AI interactions 
• Managing long-context information 
• Grounding outputs in supplied source material 
• Introduction to Retrieval-Augmented Generation (RAG)
• Handling conflicting, incomplete, or outdated information 
• Case Study: Creating a knowledge-grounded AI assistant that answers organizational policy questions using approved internal documents.

Module 5: Advanced Prompt Optimization and Evaluation

• Prompt testing and A/B experimentation
• Measuring accuracy, relevance, consistency, and completeness 
• Prompt iteration and optimization 
• Building prompt evaluation frameworks
• Prompt versioning and performance monitoring 
• Case Study: Comparing multiple prompt designs for generating financial summaries and developing an evaluation scorecard based on predefined criteria.

Module 6: Multimodal and Structured Prompting

• Prompting with text, images, documents, tables, and structured data
• Designing prompts for document analysis 
• Extracting structured information from unstructured content 
• Combining multiple inputs and instructions 
• Designing AI workflows for multimodal applications 
• Case Study: Creating a multimodal workflow that extracts key information from business documents and converts it into a structured management dashboard.

Module 7: Prompt Engineering for AI Agents and Automation

• Designing prompts for AI agents and autonomous workflows
• Tool-use instructions and workflow orchestration 
• Prompt chaining across multiple AI tasks 
• Integrating prompts with business process automation 
• Human-in-the-loop design and escalation mechanisms 
• Case Study: Designing an AI-powered workflow that receives a customer request, categorizes it, generates a response, and escalates complex cases for human review.

Module 8: Responsible AI, Security, and Enterprise Prompt Governance

• Managing hallucinations, bias, prompt injection, and adversarial inputs
• Data privacy and sensitive-information protection 
• Responsible AI and human oversight 
• Enterprise prompt governance and standardization
• Building organizational prompt libraries and governance frameworks 
• Case Study: Developing an enterprise prompt governance framework covering approved prompts, data handling, testing, version control, access, and human review.

Training Methodology

• Interactive lectures and presentations.
• Group discussions and brainstorming sessions.
• Hands-on exercises using real-world datasets.
• Role-playing and scenario-based simulations.
• Analysis of case studies to bridge theory and practice.
• Peer-to-peer learning and networking.
• Expert-led Q&A sessions.
• Continuous feedback and personalized guidance.

Register as a group from 3 participants for a Discount

Send us an email: info@datastatresearch.org or call +254724527104 

Certification

Upon successful completion of this training, participants will be issued with a globally- recognized certificate.

Tailor-Made Course

 We also offer tailor-made courses based on your needs.

Key Notes

a. The participant must be conversant with English.

b. Upon completion of training the participant will be issued with an Authorized Training Certificate

c. Course duration is flexible and the contents can be modified to fit any number of days.

d. The course fee includes facilitation training materials, 2 coffee breaks, buffet lunch and A Certificate upon successful completion of Training.

e. One-year post-training support Consultation and Coaching provided after the course.

f. Payment should be done at least a week before commence of the training, to DATASTAT CONSULTANCY LTD account, as indicated in the invoice so as to enable us prepare better for you.