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Vision AI and Advanced OpenAI

KodeKloud via Coursera

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Details

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Provider

Coursera
Pricing

Paid Course
Languages

English
Certificate

Certificate Available
Effort

3 weeks, 2 hours a week
Sessions

Self-Paced
Level

Intermediate
Subtitles

Arabic, German, English, French, Spanish

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Overview

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Once you can build with text, the next step is multimodal AI and enterprise-scale capabilities. This course advances your OpenAI skills into image generation, advanced production API features, and the foundational AWS architecture knowledge you need to design serious generative AI systems. You'll start with OpenAI's vision capabilities: how DALL-E generates images from natural language prompts, the evolution from DALL-E 1 to DALL-E 3, and how CLIP connects visual and language understanding. You'll build a working image generator and an image captioning pipeline, and examine the ethical challenges and future trends shaping AI vision technologies. Next, you'll implement OpenAI's most powerful production features — function calling, structured outputs, batch processing, and content moderation — the capabilities that separate prototype applications from scalable, enterprise-grade systems. The course closes with a critical knowledge bridge into AWS: tokens, embeddings, chunking, context windows, the foundation model lifecycle, AWS GenAI infrastructure design, and cost optimisation principles — preparing you for AWS-native deployment. Designed for learners who have OpenAI API experience. Basic programming knowledge is recommended.

Syllabus

Vision (DALL-E, CLIP, Image Generation)

In this module, you'll explore OpenAI's cutting-edge vision capabilities, focusing on DALL-E and CLIP. You’ll learn how DALL-E’s text-to-image generation works, the evolution of DALL-E versions, and its practical applications across various industries. Hands-on projects will guide you through creating your own images and fine-tuning models, while discussions on ethical considerations and future trends will prepare you for challenges in AI-driven vision technologies.

Features (Function Calling, Structured Outputs, Batch Processing)

This module dives into the advanced features of OpenAI, including structured outputs, function calling, and batch processing. You’ll learn how to manage and scale AI solutions, applying advanced usage techniques to create robust applications. Through hands-on labs, you’ll practice batch processing and explore moderation techniques to ensure ethical use of AI.

Fundamentals of Generative AI (Tokens, Embeddings, Foundation Model Lifecycle)

This module introduces the core concepts of generative AI, including tokens, chunking, and embeddings. You’ll explore the lifecycle of foundation models, their capabilities, and limitations in real-world applications. Additionally, you’ll gain insights into the AWS infrastructure for building generative AI solutions and the cost considerations for optimizing performance, availability, and redundancy.