Build a Multimodal Generation Pipeline for a Tourism Operator
Overview
What this challenge is about.
Extract frames, generate captioned images and multilingual captions, and suggest hashtags for a tourism operator. Earn a verifiable certificate.
The scenario
The operator (around 25 people, around 600 group experiences per month) currently spends about 6 hours of marketing-team time per week assembling social posts; pushing the first pass to the field would shift the marketing team to higher-leverage work.
The Brief
What you'll do, and what you'll demonstrate.
Build a multimodal generation pipeline that turns a 30-second tour video into a publish-ready social post bundle in EN/PT/ES.
Earning criteria — what you'll demonstrate
- Compose a multimodal generation pipeline from open models
- Apply vision-language models to a real product use case
- Evaluate multilingual generation against brand and SEO criteria
- Communicate a generative pipeline as an operational tool
Program Fit
Where this fits in your program.
Sharpens the same skills your degree expects you to demonstrate.
Generative AI
Master · Generative Ai
Strong alignment
This challenge maps to Generative AI at the Master level. It sharpens the same practical skills your coursework expects — but in a real industry context with actual constraints and deliverables.
Skills
Skills you'll demonstrate.
Each one shows up on your verified credential.
- Multimodal Generation
Apply multimodal generation to solve real industry problems and demonstrate production-level capability.
- Vision Language Models
Apply vision language models to solve real industry problems and demonstrate production-level capability.
- Llm Inference
Apply llm inference to solve real industry problems and demonstrate production-level capability.
- Huggingface
Apply huggingface to solve real industry problems and demonstrate production-level capability.
- Prompt Engineering
Apply prompt engineering to solve real industry problems and demonstrate production-level capability.
- Evaluation
Apply evaluation to solve real industry problems and demonstrate production-level capability.
Careers
Career paths this challenge builds toward
Completing this challenge demonstrates skills that transfer directly to these roles:
AI Engineer
Composing a multimodal pipeline into an operational tool a non-engineer can run is exactly the day-one work of an AI engineer at any consumer-AI or content-tech firm.
This challenge sharpens
- multimodal-generation
- vision-language-models
- llm-inference
NLP Engineer
Multilingual caption generation under length constraints with brand rules is core NLP-engineer work in content and marketing-AI tools.
This challenge sharpens
- llm-inference
- prompt-engineering
- evaluation
AI Product Designer
Designing the per-language output contract and writing the guide-facing playbook is the AI product-designer craft of building tools real operators trust.
This challenge sharpens
- prompt-engineering
- evaluation
- multimodal-generation