Prompt Engineering Course

Prompt engineering is fast becoming a core workplace skill rather than a niche one. Being able to brief a model precisely, control the format of its output and check the quality of its answers is what separates people who get consistent value from AI from those who do not, and it lifts productivity across writing, analysis, development and support roles.

With Logitrain you learn by doing with a skilled trainer, keep the digital course material, and every course carries the price beat guarantee. Train in person in Melbourne, Sydney and Brisbane, or live online in real time anywhere in Australia, with full-time and part-time schedules to suit your work.

There are no formal prerequisites for this course. You should be comfortable using a computer and web applications, and it helps to have used a tool such as ChatGPT at least once. The LangChain, vector database and agent sessions are easier if you have some basic Python, though this is not required to attend.

There is no certification exam associated with this course.

Prompt Engineering Course material in digital format, covering every module from the five principles of prompting through to building AI-powered applications, so you can revisit the techniques and code examples after class.

• Apply the five core principles of effective prompting
• Explain how large language models generate text from a prompt
• Structure prompts that return lists, hierarchies and clean JSON
• Extract specific features and data from text with language models
• Manage context windows by chunking text and counting tokens
• Use role prompting, meta prompting and least to most techniques
• Build prompt templates and chains with LangChain
• Retrieve relevant context using embeddings and vector databases such as FAISS and Pinecone
• Implement retrieval augmented generation for grounded, accurate answers
• Create autonomous agents that use memory and external tools
• Design few-shot prompts and save reusable prompt templates
• Generate images with Midjourney using positive and negative prompts
• Produce and refine images with Stable Diffusion, upscaling and SDXL
• Build a complete AI-powered application from prompt to output
• Evaluate prompt quality and troubleshoot failing prompts

This course suits beginners through to experienced technical staff, with the later modules pitched at a more technical level.

• Content writers, marketers and copywriters using generative AI
• Software developers and engineers adding AI features to products
• Data analysts and data scientists
• Product managers and business analysts
• Consultants and technical professionals adding AI to their toolkit
• Career changers moving into prompt engineering and AI roles
• Founders and small business owners automating work with AI

• The five principles of prompting
  • Give clear direction in a prompt
  • Specify the output format
  • Provide examples to guide the model
  • Evaluate the quality of responses
  • Divide labour across steps
• Large language models for text generation
  • How vector representations encode language
  • Transformer architecture and contextual relationships
  • Probabilistic text generation and decoding
  • OpenAI generative pretrained transformer models
  • Comparing model capabilities
• Standard practices for text generation with ChatGPT
  • Generating lists and hierarchical lists
  • Producing structured JSON output
  • Asking for context and unbundling text style
  • Extracting textual features with language models
  • Summarising within context window limits
  • Chunking text and estimating token usage with tiktoken
  • Role prompting and meta prompting
  • Building a simple classification model
• Advanced text generation with LangChain
  • Introduction to LangChain and chat models
  • Streaming responses and multiple generations
  • Prompt templates and the LangChain Expression Language
  • Function calling and extracting structured data
  • Creating few-shot prompt templates
  • Saving and loading prompts
  • Text splitters and prompt chaining
• Vector databases with FAISS and Pinecone
  • Introduction to embeddings
  • Retrieval augmented generation
  • Memory retrieval with FAISS
  • Retrieval augmented generation with LangChain
  • Hosted vector databases with Pinecone
• Autonomous agents with memory and tools
  • Building agents and using language models as an API
  • Agent toolkits and custom agents in LCEL
  • Long-term and short-term memory
  • Memory types in LangChain
  • Plan-and-execute agents and token counting
• Diffusion models for image generation
  • How diffusion models create images
  • Introduction to Stable Diffusion
  • Text to video and model comparison
• Image generation with Midjourney
  • Reverse engineering prompts
  • Negative prompts and prompting with an image
  • Prompt rewriting and prompt analysis
• Advanced image generation with Stable Diffusion
  • Running Stable Diffusion
  • Upscaling images
  • Segment Anything Model
  • Stable Diffusion XL Refiner
• Building AI-powered applications
  • Generating an outline and text for a project
  • Producing images for the application
  • Assembling a complete AI-powered workflow

• AI Essentials training course is the ideal starting point for using generative AI and effective prompting in a business role, with the BCS certificate included.
• AI Foundation certification course gives you a solid grounding in AI and machine learning concepts, terminology and risks.
• PCEI Certified Entry-Level AI Specialist with Python course is a natural next step for a recognised AI certification and applying AI logic with Python.
• AI-102 Azure AI Engineer course suits developers who want to build and deploy generative AI apps and agents on Microsoft Azure.
• Artificial Intelligence Job Ready Program combines training, certifications and local work experience for people targeting a career in AI.
• AI and machine learning courses lists the full range so you can pick the right level.

Got a team to train? Logitrain can deliver the Prompt Engineering Course in house at your premises anywhere in Australia, with the same skilled trainer, course material and hands-on exercises as the public courses. It suits teams who want everyone building consistent, high quality prompts together on dates that suit the business.

What is a prompt engineering course?

A prompt engineering course teaches you to design clear, effective prompts so large language models and generative AI tools return accurate, useful results. This course takes you from the core principles through to building with tools such as ChatGPT, LangChain and image models.

Is an exam included in the prompt engineering course?

No. This is a training course with a Certificate of Attendance, so there is no certification exam to sit. You focus fully on practical skills you can apply at work.

Do I need coding experience for the prompt engineering course?

No coding experience is required to attend. Some basic Python makes the LangChain, vector database and agent sessions easier to follow, but the trainer guides you through the examples step by step.

Which AI tools and models does the course cover?

You work across large language models such as the GPT family through ChatGPT, the LangChain framework, vector databases including FAISS and Pinecone, and image models including Midjourney and Stable Diffusion.

How long is the prompt engineering course?

The course runs for 2 days full time, or 2 weeks part time if you choose weeknight or weekend classes. Each full-time day maps to one part-time week.

Where can I take the prompt engineering course?

You can train in person in Melbourne, Sydney, Brisbane, Adelaide, Perth and Canberra, plus live online across Australia, all delivered live in real time with a trainer.

Should I take AI Essentials or the prompt engineering course first?

If you mainly want to use AI well in a business role, start with the AI Essentials training course. If you want to design prompts and build with language models, this Prompt Engineering Course is the right fit.