NextGen AI
Intermediate32% off

Multimodal AI: Vision + Language

Combine vision and language AI. Build applications that understand and generate content across multiple data types.

4.7
(3,450)
3,450 studentsEnglish

Created by Marcus Lee · Prompt Engineer & Consultant

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This course includes

  • 15 video lessons
  • 4h 17m of content
  • Downloadable resources
  • Full lifetime access
  • Certificate of completion
  • 30-day money-back guarantee

What you'll learn

  • Grasp the core concepts of multimodal AI and its significance.
  • Understand architectures like CLIP and BLIP for vision-language tasks.
  • Implement image captioning using pre-trained models.
  • Build a visual question answering (VQA) system.
  • Explore text-to-image generation with Stable Diffusion and DALL-E.
  • Learn techniques for cross-modal retrieval.
  • Identify use cases for multimodal AI in various industries.
  • Integrate multimodal capabilities into your own Python projects.

About this course

The next wave of AI isn't limited to text. Multimodal AI bridges the gap between different data formats like images, audio, and text, enabling richer, more intuitive interactions. This course provides a comprehensive introduction to the concepts, architectures, and practical applications of multimodal AI. You'll explore state-of-the-art models and techniques that allow AI to 'see' and 'understand' visual information, then reason about it using natural language. We'll cover key areas such as image captioning, visual question answering (VQA), and text-to-image generation, demonstrating how these capabilities can be integrated into real-world products. Get hands-on experience with leading libraries and APIs. This intermediate-level course is designed for developers and AI enthusiasts eager to build the next generation of intelligent applications that interact seamlessly with the world around us.

Course content

5 modules · 15 lessons · 4h 17m

  • What is Multimodal AI and Why Does it Matter?Preview
    15m
  • Key Concepts: Embeddings and AlignmentPreview
    18m
  • Common Multimodal Tasks and Datasets
    12m

Requirements

  • Intermediate Python programming skills.
  • Familiarity with deep learning concepts and frameworks (e.g., PyTorch, TensorFlow).
  • Basic understanding of natural language processing (NLP).

Your instructor

M

Marcus Lee

Prompt Engineer & Consultant

Marcus builds prompting systems for enterprise teams and has shipped LLM features used by millions.