Generative AI Certification Program

Name: Generative AI Certification Program
Price: 1200 GBP
Availability: InStock
Rating: 4.8 (24 reviews)

Learn prompt engineering, GenAI tools, AI copilots, structured outputs, document Q&A, workflow automation, and responsible AI practices in 3 months.

Cohort: Starting Soon

Duration: 3 months

10,000+ Trained

85% Placed

Prompt systems, AI copilots, document Q&A, automation, and responsible AI

Learner Reviews

4.8

Based on 24 first-party learner reviews

These ratings come from learner feedback published on this page and are mirrored in the course structured data for search engines.

Career Outcomes

Target Roles

AI Content Specialist
Prompt Engineer
AI Workflow Executive
AI Productivity Specialist

Average Salary (UK)

£30,000 – £60,000+

Post-completion

Industry Demand

Growing demand across startups, marketing, ops, and product teams

Is This Right Fit For You?

Beginners exploring practical generative AI for work and career growth

Professionals who want to work faster with AI copilots and prompt systems

Founders, operators, marketers, and support teams adopting AI workflows

Anyone searching for a 3-month Gen AI course with practical portfolio projects

Curriculum

The full 12-week Generative AI curriculum is expanded below, including phase-by-phase topics, weekly labs, prompt systems, GenAI tools, workflow projects, and responsible AI outcomes.

View detailed curriculum

Overview

Duration3 months

FormatLive + practical labs

LevelBeginner-friendly

Course Investment

£1,200

EMI Available

Tools Covered

CHChatGPT

CLClaude

GEGemini

PEPerplexity

NONotebookLM

MIMicrosoft Copilot concepts

ZAZapier / Make concepts

GOGoogle Workspace / Microsoft 365

3-month practical certification plan

Generative AI Certification

A twelve-week practical programme for using GenAI tools, prompt systems, copilots, structured outputs, document Q&A, and responsible AI workflows across business, content, operations, research, and productivity roles.

12 weeks48 guided hours6 portfolio projectsPrompting, tools, RAG, responsible AI

Role readiness

AI content, prompt specialist, AI operations, productivity, and workflow support roles

Practical workflows

Learners build prompt libraries, research systems, structured workflows, and document assistants

Responsible use

Every project includes redaction, verification, source awareness, human review, and AI-use declarations

Recommended curriculum balance

Build useful AI habits first, then turn them into repeatable business workflows.

The 3-month structure keeps technical overhead light and focuses on practical prompt systems, tool selection, structured outputs, document assistants, workflow automation, and responsible AI use.

GenAI Foundations

1 week

4 live hours

Core concepts, model limits, safe use, and practical business framing

Prompt Engineering

3 weeks

12 live hours

Reusable prompt systems for research, content, analysis, and operations

GenAI Tools and Copilots

2 weeks

8 live hours

ChatGPT, Claude, Gemini, Perplexity, NotebookLM, and workflow selection

Structured Outputs and Automation

2 weeks

8 live hours

Reliable outputs, prompt libraries, no-code workflows, and business process support

RAG and Knowledge Assistants

2 weeks

8 live hours

Document Q&A, semantic search concepts, citations, and grounded answers

Portfolio and Career

2 weeks

8 live hours

Responsible AI case studies, portfolio proof, interview prep, and role positioning

Detailed syllabus

Five phases from GenAI foundations to portfolio-ready workflows.

Learners progress through safe AI use, prompt engineering, business copilots, multimodal tools, structured outputs, knowledge assistants, governance, and career-ready case studies.

Phase 1

Generative AI Foundations and Safe Use

Understand what GenAI can and cannot do, how modern AI assistants behave, and how to use them safely in professional settings.

Foundations of Generative AI

Week 1

Project: AI Use-Case Map

Generative AI, LLMs, multimodal AI, tokens, context windows, model strengths, model limits, and hallucinations

Common business use cases across research, writing, customer support, operations, marketing, HR, and productivity

Safe AI use, redaction, privacy, bias, accuracy, copyright awareness, and human review checkpoints

Choosing when to use ChatGPT, Claude, Gemini, Perplexity, NotebookLM, or a workflow automation tool

GenAI workflow

Learners create a practical map of where GenAI can save time, where it needs human review, and where it should not be used.

Phase 2

Prompt Engineering and Business Prompt Systems

Move from casual prompting to repeatable prompt systems that produce useful, reviewable outputs for real professional tasks.

Prompt Engineering Foundations

Weeks 2-3

Project: Business Prompt Library

Prompt structure, role, context, task, constraints, examples, tone, audience, and output format

Prompt patterns for summarisation, rewriting, ideation, classification, extraction, research, and decision support

Few-shot examples, prompt variables, reusable templates, prompt versioning, and quality rubrics

Prompt debugging, hallucination reduction, fact-checking, citation checks, and evaluation loops

GenAI workflow

Learners build a tested prompt library with inputs, expected outputs, review criteria, and examples for repeatable business work.

Writing, Research and Communication Workflows

Week 4

Project: AI Research and Writing Workflow

Research brief creation, source comparison, note synthesis, meeting summaries, and stakeholder update drafting

Email, proposal, report, social content, learning notes, and executive summary workflows

Using AI to adjust tone, audience, structure, clarity, and action orientation without inventing claims

Human-in-the-loop editing, verification, source tracking, and final quality review

GenAI workflow

Learners build an end-to-end workflow that turns a research question into notes, draft content, checked claims, and a final business-ready output.

Phase 3

GenAI Tools, Multimodal Workflows and Copilots

Learn the practical tool stack for modern GenAI work, including text, images, documents, presentations, spreadsheets, and personal productivity systems.

AI Tools and Copilots

Weeks 5-6

Project: Productivity Copilot Setup

ChatGPT, Claude, Gemini, Perplexity, NotebookLM, Microsoft Copilot concepts, and tool selection by task

Document summarisation, spreadsheet support, presentation drafting, meeting notes, and personal knowledge workflows

Image generation literacy, visual prompt writing, slide/storyboard support, and multimodal input review

AI tool comparison, privacy settings, workspace rules, team adoption, and repeatable productivity playbooks

GenAI workflow

Learners create a practical copilot setup for their role, with tool choices, prompt templates, review rules, and workflow examples.

Phase 4

Structured Outputs, Automation and Knowledge Assistants

Turn GenAI from a chat tool into controlled workflows that extract information, produce structured outputs, and answer from trusted documents.

Structured Outputs and Workflow Automation

Weeks 7-8

Project: Structured AI Workflow

Structured outputs, tables, JSON-style responses, checklists, scorecards, templates, and validation rules

Lead triage, support classification, content calendar planning, report drafting, HR screening support, and operations checklists

No-code workflow thinking with tools such as Zapier, Make, forms, spreadsheets, and AI assistants

Error handling, review queues, approval steps, audit trails, and when to keep a human decision point

GenAI workflow

Learners build a workflow that turns messy inputs into a structured, reviewed business output with clear approval checkpoints.

RAG, Document Q&A and Knowledge Assistants

Weeks 9-10

Project: Knowledge Assistant Prototype

RAG concepts, embeddings, semantic search, document chunks, metadata, answer grounding, and citations

NotebookLM-style document workflows, policy assistants, training Q&A, internal knowledge support, and research copilots

Good source selection, document hygiene, conflicting evidence, outdated information, and low-confidence answers

Evaluation sets, golden answers, citation review, prompt injection awareness, and escalation rules

GenAI workflow

Learners create a grounded assistant over a controlled document set and test whether answers are accurate, cited, and useful.

Phase 5

Responsible AI, Portfolio and Career Acceleration

Package GenAI skills into a credible portfolio with case studies, governance notes, interview stories, and role-ready communication.

Responsible AI and Governance

Week 11

Project: Responsible AI Playbook

Accuracy, transparency, fairness, bias, data minimisation, privacy, copyright awareness, and security basics

AI-use declarations, redaction rules, source tracking, human verification, and final accountability

Business risk assessment, stakeholder sign-off, approval workflows, and when not to use GenAI

Policy writing, team guidelines, prompt library governance, and practical AI adoption checklists

GenAI workflow

Learners create a responsible AI playbook that documents safe usage rules, review steps, and risk controls for a team or role.

Portfolio, Interview Prep and Professional Use Cases

Week 12

Project: Generative AI Portfolio Pack

Portfolio case studies, before-and-after workflow examples, prompt libraries, tool comparisons, and result summaries

LinkedIn, CV, GitHub or Notion portfolio, role positioning, interview answers, and project walkthroughs

Use-case based interviews for AI content, AI operations, prompt specialist, productivity, and workflow roles

Final presentation, feedback, refinement, and next-step learning plan

GenAI workflow

Learners use AI to improve portfolio narratives and interview answers while keeping claims accurate, specific, and evidence-backed.

Week-by-week teaching plan

Saturday concepts, Sunday labs, portfolio progress every week.

Each weekend turns GenAI concepts into a visible workflow, so learners finish the course with case studies rather than loose tool familiarity.

Week

Saturday class

Sunday class

Project milestone

Week 1

GenAI landscape, LLMs, multimodal AI, model limits

Safe use, redaction, privacy, bias, use-case mapping

Submit AI Use-Case Map

Week 2

Prompt structure, context, constraints, examples

Summarisation, rewriting, classification, extraction patterns

Start Business Prompt Library

Week 3

Few-shot prompting, prompt variables, quality rubrics

Prompt debugging, hallucination checks, evaluation loops

Improve prompt library

Week 4

Research, writing, meetings, proposals, reports

End-to-end AI research and writing workflow

Submit AI Research and Writing Workflow

Week 5

ChatGPT, Claude, Gemini, Perplexity, NotebookLM

Tool selection, privacy settings, productivity playbooks

Start Productivity Copilot Setup

Week 6

Documents, spreadsheets, presentations, images, multimodal review

Role-specific copilot setup and workflow testing

Submit Productivity Copilot Setup

Week 7

Structured outputs, tables, JSON-style responses, templates

Validation rules, scorecards, review queues

Start Structured AI Workflow

Week 8

No-code automation thinking, forms, spreadsheets, approvals

Build and test structured workflow with human review

Submit Structured AI Workflow

Week 9

RAG, embeddings, chunks, metadata, semantic search

Document preparation and Q&A assistant design

Start Knowledge Assistant Prototype

Week 10

Grounding, citations, conflicting sources, low-confidence answers

Evaluation set, golden answers, prompt injection checks

Submit Knowledge Assistant Prototype

Week 11

Responsible AI, transparency, fairness, privacy, copyright

AI-use declarations, team guidelines, risk controls

Submit Responsible AI Playbook

Week 12

Portfolio case studies, CV, LinkedIn, interview stories

Final presentation, feedback, and role positioning

Submit Generative AI Portfolio Pack

Portfolio outcomes

Six projects that prove practical GenAI capability.

Each submission shows workflow thinking, prompt design, tool choice, output quality, review steps, and responsible AI controls.

AI Use-Case Map

Choose practical GenAI use cases with clear boundaries

Workflow map, use-case shortlist, value-risk score, and safe-use notes

Business Prompt Library

Create reusable prompt systems instead of one-off chat outputs

Prompt templates, examples, expected outputs, review rubric, and version notes

AI Research and Writing Workflow

Use GenAI to support high-quality communication without inventing claims

Research brief, source notes, draft output, verification log, and final polished deliverable

Structured AI Workflow

Turn messy inputs into reviewable business outputs

Input examples, structured output template, validation checklist, and approval process

Knowledge Assistant Prototype

Build grounded document Q&A workflows with citations

Document set, Q&A examples, citation checks, evaluation notes, and failure-mode list

Generative AI Portfolio Pack

Present GenAI skills credibly for business and AI workflow roles

Case studies, prompt library, tool comparison, responsible AI playbook, and interview walkthrough

Required submission pattern

Business use case

Input examples

Prompt or workflow design

Tool selection

Output examples

Human review steps

Risk controls

AI-use declaration

Make AI useful

Learners focus on repeatable workflows that save time, improve communication, and produce reviewable outputs.

Show the evidence

Every portfolio piece includes examples, review notes, risk controls, and a clear before-and-after workflow story.

Keep humans in charge

The course trains learners to design AI workflows with verification, approval, escalation, and accountability built in.

Simple course promise

Turn GenAI from casual tool use into repeatable professional workflows, with prompt systems, document assistants, structured outputs, governance habits, and a portfolio that shows exactly how the learner uses AI responsibly.

Career guides

Read before choosing this programme

These Brit Institute guides explain the UK roles, salaries, tools, and learning path connected to this course.

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Hands-On Projects

AI Use-Case Map
Business Prompt Library
AI Research and Writing Workflow
Structured AI Workflow
Knowledge Assistant Prototype
Generative AI Portfolio Pack

Career Support

Generative AI portfolio guidance
Prompt library and workflow case-study review
Use-case based interview prep and role positioning

Learner Reviews

4.8 / 5 average from 24 published learner reviews

Lauren Smith

Published 18 Mar 2026

4.9 / 5

The prompting frameworks were immediately useful in my day-to-day work. I now have repeatable workflows instead of experimenting from scratch every time.

Omar Khan

Published 3 Feb 2026

4.8 / 5

I wanted a practical introduction to generative AI, and this delivered exactly that. The business use cases made it much easier to apply what I learned.

Neha Verma

Published 21 Dec 2025

4.7 / 5

The labs and feedback sessions gave me a clear way to improve. I came away with prompts and systems I can actually reuse across projects.

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