Who is this course designed for?

<text variant="body1">OpenAI API practitioners seeking to advance their expertise into enterprise-level multimodal functionalities. <text variant="body1">Machine learning specialists and data scientists developing high-scale AI workflows that necessitate mastery of AWS Generative AI frameworks. <text variant="body1">AWS experts and cloud architects pivoting toward the engineering of sophisticated AI applications. <text variant="body1">Technical product leadership requiring a deep comprehension of computer vision capabilities and the strategic implications of various cloud-based GenAI infrastructures.

What will I get if I subscribe to this Specialization?

When you enroll in the course, you get access to all of the courses in the Specialization, and you earn a certificate when you complete the work. Your electronic Certificate will be added to your Accomplishments page - from there, you can print your Certificate or add it to your LinkedIn profile.

Is financial aid available?

Yes. In select learning programs, you can apply for financial aid or a scholarship if you can’t afford the enrollment fee. If fin aid or scholarship is available for your learning program selection, you’ll find a link to apply on the description page.

Vision AI and Advanced OpenAI

This course is part of Generative AI Engineering with OpenAI API and AWS Models Specialization

Instructor: Mumshad Mannambeth

Included with Learn more

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3 modules

Gain insight into a topic and learn the fundamentals.

Intermediate level

Recommended experience

5 hours to complete

Flexible schedule

Learn at your own pace

3 modules

Gain insight into a topic and learn the fundamentals.

Intermediate level

Recommended experience

5 hours to complete

Flexible schedule

Learn at your own pace

What you'll learn

Build DALL-E and CLIP applications using text-to-image architecture to generate and evaluate visual AI outputs.
Use OpenAI and advanced tools—function calling, structured outputs, batching, and moderation—to build scalable enterprise AI solutions.
Explain key generative AI architecture concepts like tokens, embeddings, chunking, and context windows to guide application design.
Assess AWS generative AI infrastructure, lifecycle stages, performance trade-offs, and cost optimisation.

Details to know

Shareable certificate

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See how employees at top companies are mastering in-demand skills

Learn more about Coursera for Business

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Build your subject-matter expertise

This course is part of the Generative AI Engineering with OpenAI API and AWS Models Specialization

When you enroll in this course, you'll also be enrolled in this Specialization.

Learn new concepts from industry experts
Gain a foundational understanding of a subject or tool
Develop job-relevant skills with hands-on projects
Earn a shareable career certificate

There are 3 modules in this course

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.

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.

What's included

12 videos1 reading1 assignment

12 videosTotal 62 minutes

Overview of OpenAi Vision8 minutes
DALL-E: What It Is and How It Works4 minutes
The Evolution of DALL-E: From DALL-E 1 to DALL-E 35 minutes
Understanding DALL-E Text-to-Image Generation6 minutes
Practical Applications of DALL-E in Various Industries7 minutes
Introduction to Contrastive Language-Image Pretraining (CLIP)4 minutes
Project 1: Image Generator6 minutes
Project 2: Image Captioning6 minutes
Fine-Tuning3 minutes
Practical Vision Applications5 minutes
Limitations, Challenges, and Ethical Considerations5 minutes
Future Trends and Innovations in OpenAi Vision3 minutes

1 readingTotal 10 minutes

Hands-On Lab: Creating Your Own Images10 minutes

1 assignmentTotal 30 minutes

Vision30 minutes

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.

What's included

5 videos1 reading1 assignment

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.

What's included

13 videos2 readings1 assignment

13 videosTotal 62 minutes

Basic Concepts of Generative AI - tokens, chunking, embeddings, and more5 minutes
Context Window and Tokens4 minutes
Embeddings, Vectors and Chunking4 minutes
LLMS and Prompt Engineering 5 minutes
Generative AI Use Cases and Applications4 minutes
Foundation Model Lifecycle2 minutes
Foundation Model Lifecycle and Use Case Development6 minutes
Capabilities and Limitations of Generative AI Applications6 minutes
Evaluating LLM Performance 5 minutes
AWS Infrastructure for Building Gen AI Applications4 minutes
Building Enterprise Generative AI on AWS: Tools, Models, and Security 6 minutes
Cost Consideration for AWS Gen AI Services - Redundancy, Availability, Performance, and More Part-15 minutes
Cost Consideration for AWS Gen AI Services - Redundancy, Availability, Performance, and More Part-26 minutes

2 readingsTotal 20 minutes

Game: Match the lifecycle action to the lifecycle stage10 minutes
Game: Match the advantages and disadvantages of GenAI10 minutes

1 assignmentTotal 30 minutes

Fundamentals of Generative AI30 minutes

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Add this credential to your LinkedIn profile, resume, or CV. Share it on social media and in your performance review.

Instructor

Mumshad Mannambeth

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Frequently asked questions

OpenAI API practitioners seeking to advance their expertise into enterprise-level multimodal functionalities.

Machine learning specialists and data scientists developing high-scale AI workflows that necessitate mastery of AWS Generative AI frameworks.

AWS experts and cloud architects pivoting toward the engineering of sophisticated AI applications.

Technical product leadership requiring a deep comprehension of computer vision capabilities and the strategic implications of various cloud-based GenAI infrastructures.

No prior AWS or cloud experience is required. The AWS content in this course is conceptual and architectural — designed to prepare you for hands-on AWS deployment in AWS GenAI: RAG, AI Agents & Responsible AI of the Generative AI Engineering with OpenAI API and AWS Models Specialization. Familiarity with the OpenAI API (from Generative AI: OpenAI API and Prompt Engineering or equivalent) is recommended.

You'll build two vision AI applications — an image generator and an image captioning pipeline using DALL-E and CLIP. You'll also complete a batch processing lab and implement function calling in a practical application, with skills validated through a graded assignment.

This course builds job-ready skills across three high-demand areas.

Vision AI: text-to-image generation, image captioning, DALL-E (v1–3), CLIP-based language-image understanding, multimodal prompting, and cross-industry applications.

Advanced OpenAI API engineering: function calling, structured outputs, batch processing, content moderation, and enterprise-grade usage patterns.

Generative AI architecture: tokens, embeddings, chunking, context management, foundation model lifecycle, model architectures, AWS GenAI infrastructure, LLM performance evaluation, and AI cost optimization.

Together, these skills prepare you to move from API consumer to AI systems designer.

Rather than treating image generation in isolation, this course integrates vision AI directly into production-grade engineering workflows. Its curriculum is founded on three strategic pillars: merging multimodal AI (DALL-E, CLIP) with sophisticated enterprise features such as function calling and structured outputs; creating a technical bridge from OpenAI development to AWS-native architecture through the expert application of tokens and embeddings; and prioritizing practical proficiency via graded, hands-on projects. This structured educational journey provides a clear transition for learners moving from intricate API patterns to robust AWS systems.

To access course materials, assignments, and earn a Certificate, you'll need to purchase the Certificate experience when you enroll in a course. Eligible learners may also have the option to start with a Free Trial. Some courses may also offer a Full Course, No Certificate option. This lets you access course materials, submit required assessments, and receive a final grade, but you won't be able to earn or purchase a Certificate.

Vision AI and Advanced OpenAI

Vision AI and Advanced OpenAI

What you'll learn

Details to know

See how employees at top companies are mastering in-demand skills

Build your subject-matter expertise

There are 3 modules in this course

Vision (DALL-E, CLIP, Image Generation)

What's included

12 videosTotal 62 minutes

1 readingTotal 10 minutes

1 assignmentTotal 30 minutes

Features (Function Calling, Structured Outputs, Batch Processing)

What's included

5 videosTotal 27 minutes

1 readingTotal 10 minutes

1 assignmentTotal 30 minutes

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

What's included

13 videosTotal 62 minutes

2 readingsTotal 20 minutes

1 assignmentTotal 30 minutes

Earn a career certificate

Instructor

Offered by

Explore more from Machine Learning

Generative AI: OpenAI API and Prompt Engineering

AWS GenAI: RAG, AI Agents and Responsible AI

Why people choose Coursera for their career

Felipe M.

Jennifer J.

Larry W.

Chaitanya A.

Unlock access to 10,000+ courses with a subscription

Advance your career with an online degree

Join over 4,700 global companies that choose Coursera for Business

Frequently asked questions

More questions

Vision AI and Advanced OpenAI

Vision AI and Advanced OpenAI

What you'll learn

Details to know

See how employees at top companies are mastering in-demand skills

Build your subject-matter expertise

There are 3 modules in this course

Vision (DALL-E, CLIP, Image Generation)

What's included

Features (Function Calling, Structured Outputs, Batch Processing)

What's included

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

What's included

Earn a career certificate

Instructor

Offered by

Explore more from Machine Learning

Generative AI: OpenAI API and Prompt Engineering

AWS GenAI: RAG, AI Agents and Responsible AI

Why people choose Coursera for their career

Felipe M.

Jennifer J.

Larry W.

Chaitanya A.

Unlock access to 10,000+ courses with a subscription

Advance your career with an online degree

Join over 4,700 global companies that choose Coursera for Business

Frequently asked questions

Who is this course designed for?

Do I need prior AWS experience for Vision AI & Advanced OpenAI: DALL-E to AWS?

What hands-on projects will I complete in this course?

More questions