Free Course — 10 Modules

Fine-Tune Embedding Models for AI Search

Go from foundational concepts to building and fine-tuning your own models. Master vector embeddings, sentence and vision transformers, and CLIP for real-world AI search applications.

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Module 1 of 10

Introduction to Vector Embeddings

Learn about vector embeddings and their role in data retrieval. Master the foundations of semantic search.

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Module 2 of 10

Foundations of Embedding Models

Explore the fundamentals of generating vector embeddings.

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Module 3 of 10

Introduction to Vector Databases

Learn the key concepts behind vector databases and vector search.

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Module 4 of 10

Build Your First Vector Search Application

Build a working vector search application from scratch.

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Module 5 of 10

Introduction to Sentence Transformers

Dive into how sentence transformers actually work.

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Module 6 of 10

Training and Fine-Tuning Sentence Transformers

Learn how to train your own sentence transformers.

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Module 7 of 10

Introduction to Vision Transformers

Discover how computers understand and interpret images.

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Module 8 of 10

Training and Fine-Tuning Vision Transformers

Learn how to fine-tune pre-trained vision transformers for image classification.

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Module 9 of 10

Introduction to CLIP and Multimodal Models

Explore how CLIP connects images and text in a shared embedding space.

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Module 10 of 10

Fine-Tuning CLIP Models

Enhance your CLIP model by fine-tuning it for image-to-text classification.

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Fine-Tune Embedding Models for AI Search

Introduction to Vector Embeddings

Foundations of Embedding Models

Introduction to Vector Databases

Build Your First Vector Search Application

Introduction to Sentence Transformers

Training and Fine-Tuning Sentence Transformers

Introduction to Vision Transformers

Training and Fine-Tuning Vision Transformers

Introduction to CLIP and Multimodal Models

Fine-Tuning CLIP Models

Shape Your Growth With AI-NativeProduct Discovery

Shape Your Growth With AI-Native
Product Discovery