SAP AI Core and AI Launchpad Training

SAP AI Core与AI Launchpad实战课程

专为开发者与架构师设计，掌握在SAP BTP上构建、部署和管理企业级AI与大语言模型的完整MLOps流程，含YAML工作流与模型部署实战。

本课程专为 SAP 开发者、数据科学家及技术架构师设计，专注于在 SAP BTP (Business Technology Platform) 平台上构建、部署和管理企业级 AI 与大语言模型（LLM）的完整 MLOps 落地体系。

Published 6/2026
MP4 | Video: h264, 1920×1080 | Audio: AAC, 44.1 KHz, 2 Ch
Language: English + subtitle | Duration: 3h 6m | Size: 1.84 GB

Master SAP AI Core with AI Launchpad, MLOps, YAML workflows, Generative AI Hub, and model deployment.

What you’ll learn
Understand SAP AI Core and AI Launchpad architecture fundamentals.
Learn the differences between AI Core runtime and AI Launchpad management.
Configure SAP AI Core and Launchpad services using SAP BTP Cockpit.
Implement OAuth 2.0 authentication and manage service keys securely.
Understand workspaces, tenants, and resource groups in SAP AI Core.
Apply GitOps principles for AI lifecycle management in SAP.
Connect GitHub repositories with SAP AI Core for version control.
Containerize ML models using Docker for SAP AI deployments.
Manage Docker registries and onboard container images into AI Core.
Create YAML workflows using Argo for AI training pipelines.
Build training and serving workflow templates for ML models.
Register datasets and manage ML artifacts in SAP AI Core.
Execute AI model training and deploy models using AI Launchpad.
Integrate SAP AI Core APIs using Postman and Python SDK.
Consume inference endpoints programmatically with SAP AI SDK.
Deploy and manage Large Language Models using Generative AI Hub.
Create prompt templates and embedding deployments for GenAI use cases.
Monitor AI execution metrics and evaluate model performance.
Troubleshoot deployment failures using logs and monitoring tools.
Manage scaling, quotas, and resource plans in production AI systems.
Simulate model drift and automate retraining pipelines.
Apply end-to-end MLOps and production AI best practices in SAP.

Requirements
Basic understanding of SAP BTP concepts is helpful.
Familiarity with APIs and REST services is beneficial.
Basic programming knowledge in Python is recommended.
Understanding of AI or machine learning concepts is an advantage.
Familiarity with GitHub and version control basics is useful.
Basic knowledge of Docker or container concepts is beneficial.
No prior SAP AI Core experience required.
Access to SAP BTP trial or enterprise account is recommended.
Interest in AI deployment and MLOps practices.
Basic understanding of cloud platforms is helpful.
Willingness to work on hands-on AI implementation labs.
Analytical mindset for debugging and monitoring AI workflows.
Motivation to build expertise in SAP AI technologies.

Description
TheSAP AI Core and AI Launchpad Training course is designed to provide hands-on expertise in building, deploying, monitoring, and managing enterprise AI solutions on SAP Business Technology Platform (BTP). This course helps professionals understand SAP’s AI infrastructure and implement modern MLOps and Generative AI workflows using SAP AI Core and SAP AI Launchpad.

The training begins with thefundamentals of SAP AI architecture, where you will understand the differences between SAP AI Core runtime services and SAP AI Launchpad administration capabilities. You will also learn how to configure workspaces, resource groups, tenants, OAuth authentication, and service keys within SAP BTP .

A major focus of the course is onMLOps and GitOps integration, including connecting GitHub repositories, managing training and serving scripts, and containerizing machine learning models using Docker. You will gain practical experience onboarding repositories and Docker registries into SAP AI Core for scalable AI deployments.

The course further exploresYAML workflow orchestration using Argo, where you will define training and serving workflows, manage datasets and artifacts, and deploy custom-trained machine learning models using SAP AI Launchpad. You will also learn to interact with AI models programmatically through APIs and the SAP AI Core Python SDK.

Advanced modules focus onGenerative AI Hub integration, including orchestration deployments for large language models such as GPT-4o and Claude, prompt template management, and embedding deployments. Additionally, the course coversAI lifecycle management, runtime monitoring, scaling strategies, troubleshooting, model retraining, and production operations.

By the end of this course, learners will be able to implement end-to-end AI and Generative AI workflows using SAP AI Core and AI Launchpad in enterprise environments.

Who this course is for
SAP developers building AI-powered applications on SAP BTP.
AI engineers deploying ML models using SAP AI Core.
SAP consultants implementing enterprise AI and MLOps solutions.
Data scientists operationalizing ML workflows in SAP landscapes.
Developers working with Docker, APIs, and AI orchestration.
SAP BTP professionals exploring Generative AI capabilities.
Technical architects designing AI-driven enterprise systems.
IT professionals managing AI lifecycle and deployment operations.
DevOps engineers implementing GitOps and CI/CD for AI.
Professionals integrating LLMs and Generative AI into SAP systems.
Innovation teams exploring SAP AI Launchpad and AI Core services.
SAP technical consultants expanding into AI and automation domains.
Students aiming to build careers in SAP AI and cloud technologies.
Organizations training teams on SAP AI deployment platforms.
Anyone interested in SAP AI Core, Launchpad, and enterprise AI.