Overview
This two-day foundation course is designed for learners who have little or no prior experience with Artificial Intelligence or Claude. It starts with simple, non-technical explanations of AI, Generative AI and Large Language Models, then progresses into guided use of Claude for everyday workplace tasks.
Participants learn through short explanations, live demonstrations and repeated hands-on practice. The practical flow covers the Claude chat interface, writing clear prompts, refining responses, working with approved files, checking accuracy, recognizing hallucinations, handling information responsibly and applying Claude to realistic business tasks.
The course deliberately keeps technical complexity low. No programming, API knowledge, AI engineering background or data-science experience is required. The goal is practical confidence: participants should be able to use Claude safely and independently for suitable day-to-day work after the course.
Course Objectives
By the end of this course, participants will be able to:
- Explain, in simple terms, what Artificial Intelligence, Generative AI and Large Language Models are.
- Navigate the Claude interface and conduct basic AI conversations independently.
- Write clear prompts using a simple structure of task, context, requirements and output format.
- Improve responses through follow-up instructions and iterative prompting.
- Use Claude to summarize, rewrite, brainstorm, classify, extract and organize information.
- Upload and work with appropriate files supported by the learner's Claude environment.
- Recognize AI limitations, including hallucinations, incomplete information and confident-sounding errors.
- Apply basic responsible AI practices when handling confidential, personal or organizational information.
- Verify important AI-generated information before it is used, shared or relied upon.
- Complete a practical workplace task using Claude from prompt design through final human review.
Module 1: AI and Generative AI Fundamentals
What Artificial Intelligence means in everyday work
Examples of AI in common digital tools
Traditional AI and Generative AI
What a Large Language Model (LLM) is
What Claude is and how conversational AI is used
Suitable uses and common limitations of AI assistants
Essential beginner terminology: prompt, response, context, model, hallucination and source
Module 2: Getting Started with Claude
Accessing Claude through the available training environment
Understanding the chat interface and input area
Starting a new conversation
Understanding chat context and follow-up questions
Starting a fresh chat when the task changes
Basic model/settings awareness where available
Using simple natural-language instructions
Module 3: Prompting Engineering
What a prompt is
A beginner prompt structure: Task -> Context -> Requirements -> Output
Being specific about audience, purpose, tone, length and format
Giving Claude examples when helpful
Breaking a broad request into smaller steps
Asking follow-up questions and refining an answer
Recognizing vague prompts and improving them
Module 4: Working with Files and Information
Uploading supported documents and images in the available Claude environment
Asking questions about a supplied document
Summarizing information for different audiences
Extracting key facts, decisions and action items
Converting unstructured content into a structured table
Asking Claude to work only from supplied material
Recognizing when required information is missing from the source
Module 5: Responsible AI, AI Awareness and Safe Use
What AI hallucination means
Confident-sounding answers can still be wrong
Why important information requires verification
Source checking and human review
Confidential, personal and sensitive information awareness
Following organizational data-handling and acceptable-use policies
Bias awareness and appropriate escalation
Human accountability for decisions and final outputs
Module 6: Better Prompting for Workplace Tasks
Defining the objective before prompting
Providing sufficient context without unnecessary detail
Specifying the audience and intended use
Setting constraints, tone and length
Requesting structured output
Providing examples or reference text
Asking Claude to identify missing information before answering
Using step-by-step instructions for multi-part tasks
Module 7: Accuracy, Verification and Critical Thinking
AI-generated answers versus verified facts
Checking names, dates, numbers and calculations
Recognizing unsupported statements and missing evidence
Asking Claude to identify uncertainty
Checking original sources where available
Using web search where enabled and appropriate
Creating a simple verification checklist for high-impact outputs
Module 8: Organizing Work with Claude Projects
What a Claude Project is
Creating a project
Adding approved project knowledge or files
Using project instructions to guide tone and output preferences
Keeping related chats together
Understanding that context should be deliberately provided for the task
Basic organization and naming practices
Module 9: Practical Workplace Use Cases
Professional communication and rewriting
Summarization and executive briefing
Meeting notes, decisions and action items
Brainstorming and idea generation
Information classification and organization
Turning text into tables or checklists
Explaining unfamiliar concepts in simpler language
Creating first drafts that remain subject to human review
Module 10: Beginner Capstone: Claude as an Everyday AI Assistant
Understanding the task and expected deliverable
Selecting relevant context and approved source material
Writing the first prompt
Refining output through follow-up prompts
Checking important facts against supplied material
Improving structure, tone and clarity
Final human review and responsible-use check
Programme scope, delivery arrangements and suitability are confirmed during enquiry.