SAP GenAI on BTP with AI Core and AI Launchpad

The SAP Generative AI on BTP with AI Core and AI Launchpad course is a future-ready, enterprise-oriented training program designed to empower SAP professionals to lead innovation in the era of Artificial Intelligence and Generative AI. As SAP continues its rapid transformation toward intelligent, cloud-first architectures, AI is no longer an optional enhancement—it has become a core expectation across SAP S/4HANA and SAP Business Technology Platform (BTP) landscapes.

Modern enterprises are increasingly demanding solutions that go beyond traditional SAP customization. They expect AI-driven automation, contextual intelligence, predictive insights, conversational interfaces, and agent-based workflows that seamlessly integrate with SAP systems. This course is built to address exactly those expectations, equipping learners with the skills required to design, build, deploy, and govern production-ready Generative AI solutions on SAP BTP.

The program is specifically designed for SAP Technical Consultants, Functional Consultants, ABAP Developers, SAP BTP Developers, and Solution Architects who want to remain relevant and future-proof their careers. Rather than focusing on isolated AI theory, the course follows a practical, implementation-first approach, aligned with SAP’s official AI strategy and enterprise best practices.

Learning Philosophy & Structure

This training follows a no copy-paste learning philosophy and emphasizes concept clarity, hands-on development, and real-world enterprise scenarios. The course progresses step-by-step, ensuring that every learner—regardless of prior AI exposure—can confidently transition from foundational programming to advanced enterprise AI implementation.

The learning journey begins with Python fundamentals, ensuring participants have a strong programming base. It then advances into Machine Learning (ML) and Natural Language Processing (NLP) concepts, enabling learners to understand how intelligent systems are trained, evaluated, and consumed. From there, the program dives deep into Generative AI, covering modern frameworks and architectures such as LangChain, LangGraph, Retrieval-Augmented Generation (RAG), and Agentic AI workflows.

A major differentiator of this course is its deep integration with SAP technologies, particularly SAP AI Core, SAP AI Launchpad, SAP HANA Vector Engine, SAP Orchestration Services, and SAP Joule Studio. Learners not only understand how Generative AI works but also how to operationalize it securely, scalably, and governably within enterprise SAP environments.

Enterprise Focus: SAP AI Core & AI Launchpad

A central pillar of this training is SAP AI Core, SAP’s enterprise-grade runtime environment for deploying and managing AI and ML workloads. Learners gain hands-on experience with:

• Deploying AI and ML models on SAP BTP

• Managing model lifecycles

• Handling inference pipelines

• Ensuring scalability, reliability, and performance

Complementing this is SAP AI Launchpad, which provides a centralized interface for:

• Orchestrating AI assets

• Monitoring model performance

• Managing access and governance

• Enabling collaboration between IT, business, and data teams

Together, SAP AI Core and AI Launchpad form the foundation for enterprise-scale AI adoption, and this course ensures learners gain practical mastery of both.

SAP Joule Studio & Agentic AI

The course also introduces SAP Joule Studio, SAP’s latest innovation for building AI agents and skills. Learners explore how to design intelligent agents that can:

• Interact with SAP systems

• Automate repetitive tasks

• Provide contextual recommendations

• Act as copilots within SAP workflows

This positions participants at the forefront of SAP’s evolving AI roadmap and prepares them for next-generation SAP implementations.

Real-World Use Cases & Business Scenarios

Unlike generic AI courses, this program is built around 20+ real-time enterprise use cases, including:

• Intelligent chatbots for SAP systems

• RAG-based knowledge assistants using SAP HANA Vector Engine

• Recommendation systems

• AI-driven APIs and microservices

• Integration with SAP S/4HANA, Fiori, and BTP applications

• Microsoft Teams and enterprise collaboration integrations

These scenarios ensure learners gain practical confidence and can immediately apply their skills in real projects.

Key Areas You’ll Focus On

Throughout the training, learners develop deep expertise across the complete AI lifecycle on SAP BTP:

1. Python Foundation to Advanced Development

2. Machine Learning and NLP Implementation

3. LangChain, LangGraph, and Agentic AI Architecture

4. Retrieval-Augmented Generation (RAG) with SAP HANA Vector Engine

5. SAP AI Core and SAP AI Launchpad Mastery

6. Knowledge Graphs and Multi-Modal AI

7. Enterprise Integration and Orchestration

8. End-to-End Deployment, Monitoring, and Governance

Course Content – Detailed Unit-Wise

Unit 1 – SAP BTP Introduction (Demo Session)

This unit introduces SAP BTP and the overall AI development ecosystem. Learners set up development tools using VS Code, install Python, Git, and essential plugins, and create their first Python program. Core concepts such as variables, user inputs, and multi-line strings establish the programming foundation.

Unit 2 – Introduction to Python Basics

Participants build strong Python fundamentals, covering advanced data structures (lists, tuples, dictionaries), arithmetic and logical operations, functions, loops, conditional statements, JSON handling, and modular programming. Emphasis is placed on clean, reusable code design.

Unit 3 – Python Advanced Development

This unit introduces real-world Python development using the Pandas library. Learners work on practical exercises, debug code in VS Code, and integrate Python applications with cloud-hosted PostgreSQL databases using Aiven. Topics include environment variables, connection strings, and reusable database functions.

Unit 4 – Implementing Python Use Case with UI

Learners design interactive user interfaces using Streamlit, integrating business logic with database workflows. The unit covers form handling, inputs, buttons, icons, messaging, orchestration of data flow, and PDF generation—mirroring real enterprise application requirements.

Unit 5 – Working with Machine Learning

This unit introduces Machine Learning fundamentals, types of ML, classification and regression problems, and the ML modeling lifecycle. Learners implement Logistic Regression, evaluate models using confusion matrices, and understand key metrics such as accuracy, sensitivity, and specificity.

Unit 6 – Real-Time Machine Learning Implementation

Participants implement a real-world ML scenario such as heart disease prediction, covering training, validation, service creation, UI consumption, and deployment on SAP BTP. This unit provides complete end-to-end ML exposure.

Unit 7 – Real-Time NLP Implementation

Learners dive into NLP fundamentals, text preprocessing, feature extraction, stemming, lemmatization, TF-IDF calculation, embeddings, vectorization, cosine similarity, and step-by-step NLP implementation for business use cases.

Unit 8 – Introduction to Transformers

This unit introduces transformer architectures through a chatbot use case. Learners build and deploy an NLP-based chatbot on SAP BTP, gaining hands-on experience with modern AI models.

Unit 9 – LangChain Architecture & LLM Consumption

Participants explore Generative AI fundamentals, neural networks, LLM concepts, prompt engineering, temperature and token controls, and integrate LLMs such as GPT, Claude, Groq, and open-source models using LangChain.

Units 10–21 – Advanced Enterprise GenAI Implementation

These advanced units cover LangGraph and Agentic AI, SAP GenAI Hub, enterprise GenAI implementation, RAG systems, CAP LLM plugins with RAP, SAP orchestration services, knowledge graphs, dynamic OData APIs, recommendation systems, Microsoft Teams integration, SAP Joule Studio, and building AI agents and skills. Learners complete enterprise-grade, production-ready deployments aligned with governance and security best practices.

Training Outcome & Career Impact

By the end of this 40-hour intensive program, participants will have the skills and confidence to:

• Architect enterprise-grade Generative AI solutions on SAP BTP

• Deploy and govern AI models using SAP AI Core and AI Launchpad

• Build AI agents using SAP Joule Studio

• Integrate AI with SAP S/4HANA, Fiori, and BTP applications

• Deliver real business value through intelligent automation

This course positions learners for high-impact SAP AI roles, future-proofing their careers as SAP continues to embed AI deeply into its ecosystem.