The training itinerary that SAP offers for official certification SAP Certified Associate – SAP Generative AI Developer (C_AIG), encompasses the capabilities of SAP Business AI in a comprehensive approach.

SAP BTP is SAP's cloud-based technology platform that enables the integration, expansion, and creation of intelligent applications. Within the context of SAP Business AI, BTP acts as the foundation on which artificial intelligence models are trained, managed, and deployed.

With SAP AI Core and SAP AI Launchpad, included in BTP, companies can connect large language models (LLM), automate processes, and bring AI directly to business-critical applications such as SAP S/4HANA, SAP Concur, or SuccessFactors. In short, SAP BTP is the bridge that makes SAP AI not just a theory, but a reality applied to business processes.

To help prepare for this Certification, we recommend following these steps:

Study the relevant material

Schedule and take the theoretical exam to obtain your certification

Below is a list of topics that may be covered in the theoretical exam. Please note that this is a guide, not a guarantee: SAP may update the exam content at any time.

Learning Journey – SAP Certified Associate SAP Generative AI Developer (C_AIG_2412)

🔗 Certification Link: SAP Certified Associate – SAP Generative AI Developer

The learning journey combines skills development for extending applications on SAP BTP (Business Technology Platform) with the use of large language models (LLM), employing key tools such as SAP AI Core, SAP AI Launchpad, and the SAP Business AI Generative AI Center.

SAP AI Core:

Step-by-step guide to build, deploy, and manage AI models within SAP BTP, using SAP AI Core and SAP AI Launchpad.

🔗 SAP Learning Link: Learning how to use the SAP AI Core service on SAP Business Technology Platform | SAP Learning

Key points:

SAP AI Core and SAP AI Launchpad Onboarding: introduces the process and steps required to work with both services.

Describe model training operations: explains how to train a Machine Learning (ML) model from customer data.

Describe model inference operations: shows how to deploy a Machine Learning (ML) model to SAP AI Core and use the deployment URL to run inferences.

SAP's Generative AI Hub:

This block presents the use of the Generative AI Hub SAP in BTP. Access and configuration of different language models, the use of the SDK (Software Development Kit), the advanced request methods and the generative AI applications beyond chatbots, in order to show how to take advantage of the LLM (Large Language Models) integrated into SAP AI Launchpad to solve business problems.

🔗 SAP Learning Link: Solving Your Business Problems Using Prompts and LLMs in SAP's Generative AI Hub

Key points:

Creating basic prompts in the Generative AI Hub: introduces the concept of prompts, how to write them effectively, and how to validate them directly on the platform.

Unlocking the power of LLMs using the SDK on the Generative AI Hub: Explains what the SDK is, how to configure and use it to send requests to models, and shows practical integration examples.

Refining AI responses with advanced prompt engineering techniques: addresses the principles of prompt engineering and teaches techniques for fine-tuning and controlling AI-generated responses.

Large Language Model (LLM) Selection on the Generative AI Hub: Provides an overview of the available models and explains how to choose and configure the most appropriate one for each business scenario.

Large Language Models (LLMs):

This section focuses on understanding how SAP applies the LLM (Large Language Models) in business scenarios, addressing their development, optimization, and evaluation. Advanced techniques are included, such as RAG (Retrieval Augmented Generation, which combines information retrieval and text generation) and fine-tuning models, with the aim of obtaining more accurate and useful results in business contexts.

🔗 SAP Learning Link: Navigating Large Language Models Fundamentals and Techniques for Your Use Case

Key points:

SAP Business AI Approach to Large Language Models (LLM): explains how SAP views the use of LLM, its advantages, limitations, and how it is integrated into its business solutions.

Product development with LLM use cases in SAP: describes how applications that leverage language models are designed and implemented, from initial idea to final delivery.

Techniques to maximize the performance of LLMs in use cases: introduces methods to improve the accuracy, relevance and efficiency of models when applied in specific contexts.

Application of RAG (Retrieval Augmented Generation) and fine-tuning strategies to improve LLM performance: teaches how to enrich model results through information retrieval and how to customize them using fine-tuning techniques.

LLM Assessment and Testing: addresses how to measure the quality of the generated results, establish evaluation criteria, and ensure the reliability of models in real-life scenarios.

Advanced AI Techniques with SAP's Generative AI Hub:

This section provides a clear overview of the essential concepts of artificial intelligence and of SAP Generative AI Hub. Prepares the participant to identify business scenarios in which the advanced AI techniques in SAP Business AI to deliver greater impact.

🔗 SAP Learning Link: Using Advanced AI Techniques with SAP's Generative AI Hub

Key points:

Fundamentals of Applied AI: It presents the essential concepts of artificial intelligence and the SAP Generative AI Hub. It prepares participants to identify business scenarios where advanced techniques can be applied.

Orchestration Service Application: Explains how to use the orchestration service to integrate AI models and modules, ensuring security, efficiency, and scalability in workflows.

Document Contextualization with the Generative AI Hub: It illustrates how to apply the contextualization technique (grounding) using company documents and data, in order to enrich AI responses and adapt them to real-life business scenarios.

In conclusion, the training itinerary towards the C_AIG_2412 certification immerses the professional in the practical foundations of SAP Business AI and prepares it for integrate generative AI into SAP processes with a focus diligent and responsible.