Multimodal & Vision-Language Systems

Combine image and text models: captioning, visual question answering, document understanding and OCR-driven pipelines.

⏱ 6 weeks🎚 Advanced🧩 2 projects · Capstone🖥 Any device · our GPUs

Draft syllabus. Timeline and topics are indicative and being finalised with the teaching team — the shape is right, the week-by-week detail may shift.

🎯 Who it's for

Computer-vision or NLP engineers extending into multimodal work.

✅ Prerequisites

Applied Computer Vision or NLP with Transformers
Python fluency
Comfort with transfer learning

Topics covered

Vision-language model families
Image-text embeddings and retrieval
Captioning and visual question answering

Document understanding and OCR pipelines
Evaluation for multimodal systems
Deployment

Expected completion timeline

6 weeks part-time at 8–12 hours per week ≈ 1.4 months. Self-paced learners can go faster; the live cohort keeps this pace.

Wk 1–2

Vision-language foundations

You produce: An image-text retrieval demo.

Wk 3–4

VQA and document understanding

You produce: A working multimodal pipeline on real documents.

Wk 5–6

Evaluate and capstone

You produce: An evaluated system and a documented deployment.

🧭 Where this fits

Advances the Computer Vision / NLP Engineer path toward multimodal roles. See the career & salary map for the full path, the expected pay by region, and the total cost.

💳 Delivery & fees

Available in all four delivery formats. Fees vary by format and are confirmed on your advisor call; instalments available. [Add the fee and the next cohort date here.]

Add this to your plan

Book a call and we'll place this course in a full path toward the role you want.

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