Solving Business Problems using SAP's Generative AI Hub

Course Code: AIG10

Instructor-led2 DaysAdvancedPractice labsCertificate on completion

What you'll learn

Describe how large language models work, including key capabilities, limitations, and enterprise considerations

Identify the SAP's AI Services and Models and explain the role of the Generative AI Hub within it

Navigate the Generative AI Hub interface — Model Library, Chat, Prompt Editor, Prompt Optimizer, Prompt Management, Grounding Management, and Orchestration

Identify the Orchestration Service and explain how it serves as the deployment and workflow layer for LLMs in SAP

Access the Generative AI Hub by provisioning SAP AI Core, configuring resource groups, and deploying LLMs

Join for free

Develop and iterate enterprise prompts using the Prompt Editor, including JSON-structured output for application integration

Manage prompts at scale using the Prompt Registry — templates, versioning, variables, and prompt hardening

Apply prompt engineering techniques — one-shot, few-shot, meta prompting, and system/user/assistant roles

Define key security considerations in prompt engineering and apply prompt hardening methods

Design AI workflows using the Orchestration Service, combining prompt templates, data masking, and content filtering

Use the SAP Cloud SDK for AI to connect applications programmatically to the Generative AI Hub and Orchestration Services

Explain retrieval-augmented generation and implement document grounding using the SAP HANA Vector Engine, including multi-repository patterns

Use the Prompt Optimizer to automatically test and refine prompts against defined quality criteria

Evaluate and select large language models using benchmark data, cost, and context window criteria from the Model Library

Apply SAP AI Core Custom Evaluation to benchmark LLMs against custom test datasets and scoring criteria

Identify SAP's own foundation models — SAP-RPT-1 and SAP-ABAP-1 — and determine when to use tabular AI instead of generative language models

Skills you'll gain

Others

Content

Describing Large Language Models
Discovering SAP's Generative AI Hub
Discovering the Orchestration Service
Getting Started: Access, Deployment, and the Product Lifecycle
Developing and Managing Prompts
Refining Prompts with Engineering Techniques
Designing Workflows with the Orchestration Service
Leveraging SAP Cloud SDK for AI
Improving LLM Performance
Using Advanced AI Techniques — Grounding
Evaluating and Selecting Large Language Models

Audience

Data Analyst
Developer
Data Scientist

Pre-requisite Learning

Essential

None

Recommended

Basic programming experience (Python or similar)
Familiarity with SAP Business Technology Platform concepts