Image 1 of 1
AI+ Prompt Engineer
The AI+ Prompt Engineer Level 1 certification introduces learners from diverse backgrounds and levels of expertise to the fundamental principles of artificial intelligence and prompts engineering.
Covering the history, concepts, and applications of AI, machine learning, deep learning, neural networks, and natural language processing, the program also delves into best practices for designing effective prompts that harness the capabilities of AI models to their fullest potential.
Through a combination of theoretical instruction and practical exercises, including project-based learning sessions, participants acquire the skills needed to create and utilise prompts across various domains and objectives.
What You Will Learn
1. Foundations of AI and Prompt Engineering
Begin with a clear introduction to how AI has evolved, how it works today, and why prompt engineering has become a critical skill. Topics include:
The history and milestones of AI development
Fundamentals of machine learning, deep learning and neural networks
How Natural Language Processing (NLP) enables AI to understand and generate human language
What prompt engineering is and why it determines the quality of AI outputs
2. Principles of Effective Prompting
Learn the core techniques used by professional prompt engineers to maximise AI performance. The module covers:
Writing clear, concise prompts that reduce ambiguity
Structuring and formatting desired outputs
Using examples to guide tone, style, and accuracy
Evaluating and improving AI outputs
Breaking complex tasks into sequential prompt chains
Fixing “failing prompts” and troubleshooting common issues
Participants also practise applying the five core principles of prompting through case studies and hands-on exercises.
3. Understanding AI Tools and Models
Gain an accessible introduction to the leading AI models and how to choose the right tool for the task. This includes:
How generative AI differs from traditional AI systems
How ChatGPT and GPT-4 work, their strengths and limitations
Image generation with tools such as DALL·E 2 and DALL·E 3
Emerging tools including Claude, Stable Diffusion XL, Llama-2, Mistral and Google’s PaLM
Comparing model capabilities and selecting the most appropriate model for real-world applications
The module also explores how organisations use these tools to automate tasks, create content, analyse information, and enhance creativity.
4. Mastering Prompt Engineering Techniques
Develop advanced prompting skills used by professionals to unlock more reliable and creative outputs. Learners explore:
Zero-shot and few-shot prompting
Chain-of-Thought prompting for step-by-step reasoning
Generate-Knowledge prompting to expand idea generation
Prompt chaining for multi-stage workflows
Tree-of-Thoughts for exploring multiple solution paths
Retrieval-Augmented Generation (RAG) to enhance outputs with external data
Graph prompting and interpretation of non-text data
Hands-on exercises help learners apply these techniques across multiple scenarios.
5. Prompting for Image Models
Learn how to guide AI image generation systems for high-quality creative output. The module covers:
Understanding how models like DALL·E and Stable Diffusion interpret prompts
Using style modifiers, quality boosters and weighted terms
Writing effective prompts for realistic, artistic, or brand-consistent imagery
Advanced techniques including inpainting, outpainting, and character consistency
Rewriting and refining prompts for better image results
Real-world examples help learners understand how to direct models with precision.
6. Project-Based Learning
Participants apply their new skills in a guided practical project, selecting either a text-based or image-based AI application. They work through:
Project planning and goal setting
Prompt design and iteration
Integration of text and image models
Evaluating and refining project outputs
7. Ethics, Safety and the Future of AI
The course concludes with a grounding in responsible AI use, including:
Bias and fairness in AI models
Privacy, data protection and safe use of AI tools
Transparency, accountability, and responsible deployment
Environmental considerations and sustainable AI practices
The regulatory landscape and future trends in AI and prompt engineering
Who This Course Is For
This certification is ideal for beginners, professionals, and teams seeking to use AI confidently and responsibly, whether for daily productivity, creative work, analysis, automation, or problem solving.
No coding background is required.
Typical completion time
1 days / 8 hours
Self-paced online learning with videos, podcasts, practical lab activities and Q&A tutor chat.
Coaching option
Includes 2 × 45 minutes live coaching sessions with our AI Certs Certified Trainers to fully prepare student for the certification exam.
The AI+ Prompt Engineer Level 1 certification introduces learners from diverse backgrounds and levels of expertise to the fundamental principles of artificial intelligence and prompts engineering.
Covering the history, concepts, and applications of AI, machine learning, deep learning, neural networks, and natural language processing, the program also delves into best practices for designing effective prompts that harness the capabilities of AI models to their fullest potential.
Through a combination of theoretical instruction and practical exercises, including project-based learning sessions, participants acquire the skills needed to create and utilise prompts across various domains and objectives.
What You Will Learn
1. Foundations of AI and Prompt Engineering
Begin with a clear introduction to how AI has evolved, how it works today, and why prompt engineering has become a critical skill. Topics include:
The history and milestones of AI development
Fundamentals of machine learning, deep learning and neural networks
How Natural Language Processing (NLP) enables AI to understand and generate human language
What prompt engineering is and why it determines the quality of AI outputs
2. Principles of Effective Prompting
Learn the core techniques used by professional prompt engineers to maximise AI performance. The module covers:
Writing clear, concise prompts that reduce ambiguity
Structuring and formatting desired outputs
Using examples to guide tone, style, and accuracy
Evaluating and improving AI outputs
Breaking complex tasks into sequential prompt chains
Fixing “failing prompts” and troubleshooting common issues
Participants also practise applying the five core principles of prompting through case studies and hands-on exercises.
3. Understanding AI Tools and Models
Gain an accessible introduction to the leading AI models and how to choose the right tool for the task. This includes:
How generative AI differs from traditional AI systems
How ChatGPT and GPT-4 work, their strengths and limitations
Image generation with tools such as DALL·E 2 and DALL·E 3
Emerging tools including Claude, Stable Diffusion XL, Llama-2, Mistral and Google’s PaLM
Comparing model capabilities and selecting the most appropriate model for real-world applications
The module also explores how organisations use these tools to automate tasks, create content, analyse information, and enhance creativity.
4. Mastering Prompt Engineering Techniques
Develop advanced prompting skills used by professionals to unlock more reliable and creative outputs. Learners explore:
Zero-shot and few-shot prompting
Chain-of-Thought prompting for step-by-step reasoning
Generate-Knowledge prompting to expand idea generation
Prompt chaining for multi-stage workflows
Tree-of-Thoughts for exploring multiple solution paths
Retrieval-Augmented Generation (RAG) to enhance outputs with external data
Graph prompting and interpretation of non-text data
Hands-on exercises help learners apply these techniques across multiple scenarios.
5. Prompting for Image Models
Learn how to guide AI image generation systems for high-quality creative output. The module covers:
Understanding how models like DALL·E and Stable Diffusion interpret prompts
Using style modifiers, quality boosters and weighted terms
Writing effective prompts for realistic, artistic, or brand-consistent imagery
Advanced techniques including inpainting, outpainting, and character consistency
Rewriting and refining prompts for better image results
Real-world examples help learners understand how to direct models with precision.
6. Project-Based Learning
Participants apply their new skills in a guided practical project, selecting either a text-based or image-based AI application. They work through:
Project planning and goal setting
Prompt design and iteration
Integration of text and image models
Evaluating and refining project outputs
7. Ethics, Safety and the Future of AI
The course concludes with a grounding in responsible AI use, including:
Bias and fairness in AI models
Privacy, data protection and safe use of AI tools
Transparency, accountability, and responsible deployment
Environmental considerations and sustainable AI practices
The regulatory landscape and future trends in AI and prompt engineering
Who This Course Is For
This certification is ideal for beginners, professionals, and teams seeking to use AI confidently and responsibly, whether for daily productivity, creative work, analysis, automation, or problem solving.
No coding background is required.
Typical completion time
1 days / 8 hours
Self-paced online learning with videos, podcasts, practical lab activities and Q&A tutor chat.
Coaching option
Includes 2 × 45 minutes live coaching sessions with our AI Certs Certified Trainers to fully prepare student for the certification exam.