Multimodal AI: Vision, Language & Audio

What you'll learn

• Building and evaluating ML models
• Preparing data for training
• Tuning model performance
• Deploying models to production
• Understand supervised and unsupervised learning
• Understand model training and evaluation

Planned outline shown above (sample metadata). The detailed module and lesson list for this course hasn't been published yet.

Description

Build cutting-edge multimodal AI systems that understand text, images, and audio simultaneously. Work with GPT-4V, CLIP, and Flamingo-style architectures.

What this course covers: Multimodal AI: Vision, Language & Audio works through supervised and unsupervised learning, model training and evaluation, transformers and large language models and neural network architectures.

Skills you will build: tuning model performance, deploying models to production and preparing data for training.

Practical applications: prediction and classification systems, computer vision and NLP applications and AI features inside products.

Who should take this course: developers, data analysts and engineering students moving into machine learning and AI. It is designed for learners with solid experience in machine learning and AI who want advanced, in-depth practice.

Learning outcomes: by the end of the course you should be able to apply supervised and unsupervised learning and tuning model performance to your own work or projects, and know which areas to practise next.

Requirements

• Solid working knowledge of machine learning and AI
• Comfort with intermediate concepts
• A computer with internet access

Your instructor

• P
  Priyanka S. ★★★★★ 5.0/5 Sample review

  Well organised. Revisiting the neural network architectures part a second time really helped it click. The hands-on notebooks made backpropagation finally make sense to me.

• S
  Swathi G. ★★★★★ 5.0/5 Sample review

  Good balance of theory and practice. The model training and evaluation lessons helped me apply deploying models to production in real situations. Loved that model evaluation got as much attention as model building.

• M
  Manish T. ★★★★★ 4.5/5 Sample review

  Multimodal AI: Vision, Language & Audio covered supervised and unsupervised learning in more depth than I expected. The pace was right for my level. The deployment section filled a gap most ML courses skip.

Sample reviews are illustrative demo content, not verified purchases. Ratings from learners will appear here once submitted.