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SAP BTP AI Foundation & Generative AI Hub Online Training Certification Course Course Overview
SAP BTP AI Foundation & Generative AI Hub Training by Multisoft Systems provides professionals with a structured understanding of SAP's AI capabilities available through SAP Business Technology Platform. The course introduces the architecture and services associated with AI Foundation and progresses into the implementation and operational aspects of enterprise AI solutions.
Participants explore SAP AI Core and SAP AI Launchpad for managing AI workloads and gain practical knowledge of Generative AI Hub for accessing and working with foundation models. The training covers model interaction, prompt engineering, prompt management, APIs and SDKs, embeddings, vector-based retrieval, grounding techniques, and Retrieval-Augmented Generation (RAG).
The program also addresses application integration, security, governance, responsible AI, monitoring, and enterprise implementation considerations. Practical exercises and business scenarios help participants understand how generative AI capabilities can be incorporated into SAP BTP applications and broader SAP landscapes.
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SAP BTP AI Foundation & Generative AI Hub Online Training Certification Course Course curriculum
Curriculum Designed by Experts
SAP BTP AI Foundation & Generative AI Hub Training by Multisoft Systems provides professionals with a structured understanding of SAP's AI capabilities available through SAP Business Technology Platform. The course introduces the architecture and services associated with AI Foundation and progresses into the implementation and operational aspects of enterprise AI solutions.
Participants explore SAP AI Core and SAP AI Launchpad for managing AI workloads and gain practical knowledge of Generative AI Hub for accessing and working with foundation models. The training covers model interaction, prompt engineering, prompt management, APIs and SDKs, embeddings, vector-based retrieval, grounding techniques, and Retrieval-Augmented Generation (RAG).
The program also addresses application integration, security, governance, responsible AI, monitoring, and enterprise implementation considerations. Practical exercises and business scenarios help participants understand how generative AI capabilities can be incorporated into SAP BTP applications and broader SAP landscapes.
- Understand the role and architecture of AI Foundation within SAP BTP.
- Work with SAP AI Core and SAP AI Launchpad for AI workload management.
- Understand and utilize Generative AI Hub capabilities.
- Work with foundation models for enterprise AI scenarios.
- Apply prompt-engineering techniques to improve model responses.
- Interact with generative AI capabilities through APIs and SDKs.
- Understand embeddings, vector search, grounding, and RAG architectures.
- Design generative AI applications for SAP-centric environments.
- Apply security, governance, and responsible AI principles.
- Evaluate and implement practical enterprise generative AI use cases.
Course Prerequisite
- Basic understanding of SAP solutions and enterprise applications
- Familiarity with cloud computing concepts
- Basic awareness of SAP BTP is beneficial
- Understanding of AI, machine learning, and generative AI fundamentals is helpful
- Basic knowledge of APIs and application integration is advantageous
- Programming knowledge is recommended for hands-on API and SDK exercises
- No advanced AI or machine learning experience is mandatory
Course Target Audience
- SAP BTP Developers and Consultants
- SAP Technical and Functional Consultants
- SAP Solution and Enterprise Architects
- Generative AI and AI/ML Professionals
- Application and Cloud Developers
- SAP Integration Consultants
- Data Engineers and Data Professionals
- AI Solution Architects
- SAP Technology Consultants
- Professionals working on SAP Business AI initiatives
- IT professionals involved in enterprise AI transformation and SAP BTP projects
Course Content
- Overview of SAP Business Technology Platform
- SAP BTP architecture and service landscape
- Introduction to SAP Business AI
- Role of AI within SAP's enterprise ecosystem
- Traditional AI vs. generative AI
- AI capabilities across SAP applications
- Enterprise AI scenarios and adoption considerations
- Introduction to SAP BTP AI services
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- Introduction to AI Foundation on SAP BTP
- AI Foundation capabilities and components
- Architecture and service interaction
- AI lifecycle within SAP BTP
- AI Foundation services and development landscape
- Interaction with SAP applications and business data
- AI workloads and runtime considerations
- Understanding AI service consumption
- Enterprise AI architecture patterns
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- Introduction to SAP AI Core
- Role of SAP AI Core in the AI lifecycle
- AI Core architecture and concepts
- Resource groups and workload isolation
- Configurations and executions
- AI scenarios
- Serving AI models
- Deployments and endpoints
- Working with AI Core APIs
- Managing AI workloads
- Execution and deployment lifecycle
- Monitoring AI Core resources
- Troubleshooting common deployment issues
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- Introduction to SAP AI Launchpad
- AI Launchpad architecture and capabilities
- Connecting SAP AI Core
- Resource groups and service connections
- Managing AI scenarios
- Working with configurations
- Monitoring executions
- Managing deployments
- Viewing deployment status and endpoints
- Operational management of AI workloads
- AI lifecycle visibility through AI Launchpad
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- Introduction to Generative AI Hub
- Role of Generative AI Hub within AI Foundation
- Generative AI Hub architecture
- Accessing generative AI capabilities
- Model access and orchestration concepts
- Generative AI Hub integration with SAP AI Core
- Model consumption workflow
- Generative AI Hub SDK concepts
- Generative AI Hub APIs
- Enterprise generative AI scenarios
- Working with generative AI services from applications
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- Understanding foundation models and Large Language Models (LLMs)
- Foundation model capabilities
- Model selection considerations
- Model availability through Generative AI Hub
- Comparing models for enterprise scenarios
- Model parameters and inference settings
- Temperature, tokens, and other generation controls
- Context windows and token management
- Model endpoints
- Model invocation
- Structured and unstructured outputs
- Selecting models based on business requirements
- Cost, performance, quality, and latency considerations
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- Fundamentals of prompt engineering
- Anatomy of an effective prompt
- System, user, and contextual instructions
- Zero-shot prompting
- Few-shot prompting
- Role-based prompting
- Contextual prompting
- Prompt templates
- Structured output generation
- Controlling model responses
- Prompt iteration and optimization
- Handling hallucinations
- Prompt testing and evaluation
- Prompt management concepts
- Reusable prompts for enterprise applications
- Prompt security considerations
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- Understanding Generative AI Hub programmatic access
- Authentication and authorization concepts
- Working with service credentials
- API-based model interaction
- SDK-based model consumption
- Sending prompts programmatically
- Passing model parameters
- Processing model responses
- Handling structured responses
- Error handling and exception management
- Integrating AI calls into application logic
- API testing and debugging
- Designing reusable AI service components
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- Limitations of standalone LLMs
- Introduction to grounding
- Understanding embeddings
- Converting enterprise information into vector representations
- Vector storage concepts
- Similarity and semantic search
- Chunking strategies
- Document preprocessing
- Retrieval techniques
- Introduction to Retrieval-Augmented Generation (RAG)
- RAG architecture
- Retrieval and generation workflow
- Adding business context to prompts
- SAP HANA Cloud vector capabilities – conceptual overview
- Enterprise knowledge grounding
- Improving response relevance
- Reducing hallucination risks
- Designing an enterprise RAG scenario
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- Generative AI application architecture
- Designing AI-enabled SAP BTP applications
- Connecting applications with Generative AI Hub
- Integrating enterprise data with LLM workflows
- Prompt-to-application workflow
- Implementing conversational scenarios
- Document summarization scenarios
- Information extraction
- Classification and content generation
- Business process assistance
- Combining RAG with application logic
- Handling AI responses within applications
- Application error handling
- Designing scalable generative AI solutions
- Integration considerations for SAP landscapes
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- Enterprise AI security principles
- Authentication and authorization
- Role-based access concepts
- Data privacy considerations
- Sensitive business information and LLMs
- Secure prompt and response handling
- AI governance principles
- Responsible AI concepts
- Transparency and explainability considerations
- Bias and fairness considerations
- Human oversight
- Model risk considerations
- Monitoring AI workloads
- Logging and troubleshooting
- Performance considerations
- Token and consumption management
- Operational considerations for production AI solutions
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- Identifying suitable generative AI use cases
- Evaluating business value and technical feasibility
- Enterprise knowledge assistant scenario
- Document question-answering scenario
- Business content summarization
- Information extraction from enterprise documents
- Intelligent business-process assistance
- SAP data-grounded generative AI scenarios
- Designing the end-to-end solution architecture
- Selecting an appropriate foundation model
- Creating and refining prompts
- Incorporating enterprise context
- Implementing a RAG workflow
- Connecting the solution with Generative AI Hub
- Testing generated responses
- Evaluating response quality
- Security and governance review
- Performance and optimization considerations
- Capstone solution walkthrough
- Production-readiness considerations
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SAP Implementation, Migration & Support Experts
End-to-end SAP services across transformation, BTP, HANA, cloud, migrations and managed operations.
S/4HANA Transformation
Greenfield, Brownfield and Selective Data Transition to S/4HANA with readiness assessments, conversion planning and smooth business cutover.
- Greenfield Implementation
- Brownfield System Conversion
- Selective Data Transition
- S/4HANA Readiness Assessment
SAP BTP & Integration
Integration Suite, side-by-side extensions, Build Apps, automation and analytics on a clean-core model for modern SAP landscapes.
- BTP Foundation Setup
- Integration Suite
- Extension & Clean Core
- Data & Analytics
HANA & Database
HANA administration, performance tuning, tenant management, backup, recovery and HA/DR design to keep the SAP core stable and fast.
- HANA Administration
- Performance & Tuning
- HA/DR Design & Build
- Backup, Recovery & Refresh
Cloud & Infrastructure
RISE with SAP, hyperscaler landing zones, sizing, monitoring, security, IaC and FinOps for scalable SAP cloud operations.
- RISE with SAP Advisory
- Hyperscaler Landing Zone
- Sizing & Capacity Planning
- Monitoring & FinOps
Migrations & Upgrades
Low-risk SAP migrations, OS/DB moves, release upgrades, Unicode conversion and datacenter relocation with rehearsed cutovers.
- OS/DB Migration
- Release & EHP Upgrades
- Unicode Conversion
- Datacenter / Cloud Migration
Managed Services / AMS
24×7 L1–L3 SAP support, Basis operations, incident management, system refresh and continuous improvement under SLA governance.
- Application Management L1–L3
- Basis Operations
- System Refresh
- Continuous Improvement
Explore Course Resources
Strengthen your learning with useful resources designed to help you prepare, practice, and evaluate your understanding.
SAP BTP AI Foundation & Generative AI Hub Training (MCQ) Assessment
This assessment tests understanding of course content through MCQ and short answers, analytical thinking, problem-solving abilities, and effective communication of ideas. Some Multisoft Assessment Features :
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- Secure login and authentication measures to protect data
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- Time limits and countdown timers to manage duration.
SAP BTP AI Foundation & Generative AI Hub Corporate Training
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Why SAP BTP AI Foundation & Generative AI Hub Online Training Certification Course for Your Professional Growth
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SAP BTP AI Foundation & Generative AI Hub Online Training Certification Course Trainer Profile
19+ Years Experienced
Our SAP BTP AI Foundation & Generative AI Hub Corporate & Certification Program trainers bring 13+ years of proven industry expertise, delivering practical insights aligned with real project environments.
Trained 3950+ Professionals
Our expert trainers have successfully trained 3350+ professionals through structured, real-time training programs designed for industry readiness and career growth.
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SAP BTP AI Foundation & Generative AI Hub Online Training Certification Course FAQ's
This training focuses on AI capabilities within SAP BTP, including AI Foundation, SAP AI Core, SAP AI Launchpad, Generative AI Hub, foundation models, prompt engineering, RAG, APIs, and enterprise AI integration.
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