Advanced Hands-On Generative AI Workshop: From Concept to Product
Contact us to book this course
Generative AI
On-Site, Virtual
3 days
This course prepares you to build sophisticated, end-to-end generative AI (GenAI) solutions. It focuses on taking GenAI concepts learned in earlier courses (Introduction to Building Generative AI Applications, Building Generative Chatbot Applications, and Building Generative AI Search Applications) and applying them to real-world use cases. You will architect and implement solutions that integrate multiple GenAI tools and features into a complete solution. The course consists of a series of extended hands-on labs with instructor mentoring.
Learning objectives
After successfully completing this course, you will be able to:
- Apply common GenAI architectural patterns to real-world use cases
- Implement end-to-end GenAI solutions
- Integrate multiple tools and features to enable robust workflows
Who should attend
This course is designed for developers, solution architects, and others who will be involved in the design, development, and operation of GenAI solutions.
Course outline
- The Use Cases
- Categorizing Products
- Generating Product Copy
- Localizing Product Copy
- Generating Product Imagery
- Visual Search
- Architecture
- LLM APIs for Categorization, Generation, Translation,
- Image Model APIs for Categorization, Image Generation, Embeddings
- Vector Database
- Front-End
- Supporting Services
- Human Oversight
- Implementation
- Configuring Backend GenAI Services
- Code for Working with GenAI APIs
- Creating Embeddings
- Implementing and Using the Vector Database
- Setting Up Supporting Services
- Deploying and Testing the Application
- The Use Cases
- Natural Language Q&A Grounded in Company Documentation
- Integration of Customer Account Information and Product Usage Data
- Hands-Free Operation
- Image Classification Using Proprietary Data
- Automated Routing and Escalation as Necessary
- Architecture
- LLM APIs for Categorization, Generation, Translation, Sentiment Analysis
- Custom Vision Model for Categorization
- Universal Speech Model for Speech Recognition and Synthesis
- Chat State Management
- Supporting Services
- Model and Service Monitoring
- Managed Platforms and Advanced Bot Features
- Implementation
- Configuring Backend GenAI services
- Code for Working with GenAI APIs
- Creating and Using an AutoML Vision Model
- Setting Up Supporting Services
- Deploying and Testing the Application
- Monitoring Model Performance
- Student teams bring a real-world use case that they would like to tackle
- Students, with instructor mentoring, develop a Proof-Of-Concept (POC) architecture
- Students, with instructor mentoring, develop a functioning POC
