The programme
14 evenings, in four phases.
Monday to Friday, 7:00 – 9:30 PM GMT, live online. Every evening is hands-on and ends with something on your drive that was not there at seven o’clock.
01
Foundations
Days 1–3Understand the machine before you drive it. By Friday you are generating on your own hardware, and you know why each setting does what it does.
- Diffusion in plain language: noise in, image out, and what the sampler is really doing
- Checkpoints, VAEs, CLIP, LoRAs, ControlNets — the vocabulary you will use every day after this
- Open weights vs closed APIs: what you give up, what you gain, and where the licence lines are
- The landscape as it stands: SD 1.5, SDXL, FLUX, and the current open video models
You leave withA working mental model of the stack, and a written shopping list for your own machine.
- Clean install of ComfyUI on Windows, and the Apple Silicon route for Mac users
- Drivers, CUDA, PyTorch and the four errors that stop 90% of first installs
- Where models live, how to organise 200GB of them, and how to not download the same file twice
- Your first render, start to finish — plus the cloud-GPU fallback if your machine is not ready yet
You leave withA working local install and your first self-generated image.
- Dataset craft: how 15 good images beat 300 bad ones, and how to caption them
- Training a LoRA on a face, a product, a garment or a visual style
- Reading a training run: loss, steps, overfitting, and knowing when to stop
- Testing, versioning and shipping your model so it behaves the same next month
You leave withA trained LoRA of your own subject, saved to your drive.
02
Image
Days 4–7From "an AI picture" to a photograph that survives a client review at full resolution.
- Sampler, scheduler, CFG and steps — what each one costs you and what it buys
- Resolution, aspect and the upscale chain that survives a 4K crop
- Skin, hair, fabric and metal: the four textures that give a fake away
- Hands, eyes, teeth, text — the classic failures and the repair passes that fix them
You leave withTen frames at print resolution that do not read as generated.
- The prompt as a shot list: subject, lens, lighting, grade, film stock
- Negative prompting and weighting — steering instead of begging
- Golden hour, hard key, practicals, rim light — lighting language that the model obeys
- Building a house style you can reproduce on demand, and a prompt library to keep it
You leave withA personal prompt library and a repeatable house look.
- Why hosted tools block swimwear, lingerie, medical, editorial and political work — and why local models do not
- Running uncensored open weights safely on your own machine, offline and private
- Client-safe workflows: brand safety filters you apply yourself, on your terms
- The rules that still apply: consent, likeness rights, Ghana’s data protection law, platform policy, and the categories that are illegal everywhere
You leave withAn unrestricted local pipeline, plus a written personal usage policy.
- IPAdapter and FaceID: locking a face without retraining anything
- Combining a trained LoRA with an identity reference for total consistency
- Cloning yourself: photographing a reference set that actually works, then generating a year of content from it
- Wardrobe, age, expression and angle changes that keep the same person
You leave withA consistent character sheet — your subject in eight different shots.
03
Motion
Days 8–11Stills become footage. Footage becomes an ad, a scene, a music video.
- The open video stack today, and what each model is genuinely good at
- Image-to-video: driving motion from a frame you already approved
- Frame rate, interpolation and length — getting past the three-second look
- Camera moves, physics and the artefacts that betray a generated clip
You leave withYour first generated clips, cut together.
- Reading and building a graph: nodes, sockets, types and execution order
- The production graph — checkpoint, LoRA, IPAdapter, sampler, upscale, video combine
- Reusable sub-graphs, batching and queueing overnight runs
- Debugging a graph that has stopped working, and version-controlling your workflows
You leave withA reusable studio workflow file, yours to keep.
- Anatomy of a UGC ad: hook, problem, product, proof, call to action
- Generating a believable presenter, then keeping them across a whole campaign
- Product fidelity — getting a real client’s bottle, phone or fabric to survive generation
- Voice, captions, pacing and the platform-native edit
You leave withA finished 30-second UGC ad for a real product.
- Storyboarding for generation, and shot coverage that actually cuts together
- Continuity of place, wardrobe, light and colour across a scene
- Grade, grain, aspect and sound design — the finish that hides the seams
- Assembling in an editor, and where generated footage should never go
You leave withA one-minute narrative piece, graded and cut.
04
Distribution & business
Days 12–14A skill nobody sees earns nothing. The last three evenings are about being paid for it.
- Hook structure in the first 1.5 seconds, and why most AI content dies there
- Formats that reliably travel, and the ones the platforms are quietly suppressing
- Disclosure, watermarks and staying on the right side of platform AI policy
- Reading your own analytics and iterating on evidence instead of vibes
You leave withA 30-day content plan built around your own model.
- Batch queues, prompt sheets and overnight renders
- Automating the boring half: naming, cropping, versioning, exporting per platform
- Wiring generation to scheduling tools so posting is not a daily job
- Quality control at volume — the review step you must never automate away
You leave withAn automated pipeline producing a week of content in one run.
- Building a portfolio that shows range and consistency, not luck
- What to charge in Ghana and abroad, per asset and per retainer
- Pitching brands and agencies, and the deliverables they expect
- Contracts, licensing, rights and disclosure when the work is generated
You leave withA live portfolio, a rate card, and a pitch you have already sent.