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SAP A.I. (Artificial Intelligence) on S/4 HANA Certification Program

This comprehensive 44-hour course provides in-depth knowledge of integrating Artificial Intelligence into your SAP S/4 HANA environment, preparing you for certification.

Hands-on integration and labs: Practical, scenario-based exercises using SAP S/4 HANA and SAP Business Technology Platform to design, train, and deploy AI/ML models within real S/4 HANA processes. Certification-focused curriculum: Exam-aligned modules, sample questions, and instructor guidance to prepare participants for the SAP A.I. on S/4 HANA certification. End-to-end AI lifecycle & governance: Coverage of data preparation, model selection, deployment, monitoring, and best practices for scalable, production-ready AI solutions in S/4 HANA.
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SAP A.I. (Artificial Intelligence) on S/4 HANA Certification Program
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Earn an industry-recognized credential and get access to mentor-led guidance throughout your learning journey.

4.9/5 Program Rating
1,539 Learners Enrolled
All level Level
44 hrs Total Duration
English,Hindi Language
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Program Overview

Experience a modern, outcome-driven curriculum

Built with industry mentors, this program blends immersive live sessions, simulation projects, and on-demand resources so you can master Mandarin Chinese with confidence.

The SAP A.I. on S/4 HANA Certification Program is designed for professionals looking to enhance their skills in the field of Artificial Intelligence within the SAP ecosystem. This course covers the key concepts, tools, and techniques to effectively implement AI solutions in S/4 HANA environments, and includes practical exercises to solidify learning.

Participants will explore the various AI functionalities that can be integrated into SAP S/4 HANA, understand machine learning models, and learn how to leverage SAP’s cloud platform for AI applications. By the end of this program, you'll be well-equipped to take the certification exam and apply your skills in real-world scenarios.

Why learners love this program

Each element is crafted to accelerate fluency, cultural context, and career readiness.

  • Hands-on integration and labs: Practical, scenario-based exercises using SAP S/4 HANA and SAP Business Technology Platform to design, train, and deploy AI/ML models within real S/4 HANA processes.
  • Certification-focused curriculum: Exam-aligned modules, sample questions, and instructor guidance to prepare participants for the SAP A.I. on S/4 HANA certification.
  • End-to-end AI lifecycle & governance: Coverage of data preparation, model selection, deployment, monitoring, and best practices for scalable, production-ready AI solutions in S/4 HANA.
Lectures
22
Guided Hours
44 hrs.
Program Investment
USD 2,500
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Learning Outcomes

Unlock the capabilities that matter in real-world communication

Every module stacks practical language skills with cultural fluency, so you can speak confidently in professional, academic, and social settings.

Fundamental AI and machine learning concepts and terminology relevant to SAP S/4 HANA
Key AI use cases across S/4 HANA modules (Finance, SCM, Manufacturing, Sales) and how to identify opportunities
Data preparation for AI in S/4 HANA: extraction, cleansing, feature engineering, and data quality best practices
Building and training ML models using SAP tools (SAP AI Core, AI Foundation, SAP BTP) and common ML frameworks
Deploying and integrating ML models into S/4 HANA processes, Fiori apps, and custom extensions
Designing and implementing conversational AI and RPA integrations (e.g., SAP Conversational AI, Intelligent RPA)
Implementing predictive analytics, anomaly detection, and recommendation systems within the SAP landscape
Model lifecycle management: versioning, monitoring, retraining, and CI/CD practices for ML in SAP environments
Model governance, explainability, bias mitigation, and compliance considerations for enterprise AI
Security and privacy best practices for AI solutions in SAP (authentication, authorization, data protection)
Performance tuning and scalability strategies for AI services on SAP BTP and hybrid deployments
Building automated end-to-end AI pipelines and integrating them with existing enterprise workflows
Hands-on development: labs and exercises to apply AI techniques to real-world S/4 HANA scenarios
Preparation for the SAP S/4 HANA AI certification: exam topics, study strategies, and sample question practice
Organizational and change-management aspects of adopting AI in an enterprise context, including ethical and legal considerations
Certificate

Certificate You'll Receive

Earn an industry-recognized certificate upon successful completion of this course.

SAP A.I. (Artificial Intelligence) on S/4 HANA Certification Program — Course Certificate
Personalised guidance

Book a discovery call with our program specialists

Get tailored advice on learning paths, certification journeys, and industry opportunities before you enroll.

In a focused 20-minute consultation we map your current proficiency, clarify where you want to get to, and suggest the quickest route to fluency with milestones we can help you hit.

  • Understand the skill gaps holding you back and the modules that can close them in the next cohort.
  • Get a personalised cohort recommendation based on availability, trainer profile, and your weekly bandwidth.
  • Discover global project work and certification add-ons that enhance Mandarin credentials on your CV.

Reserve your slot

Share your details and we will connect within 24 hours to set up a personalised walkthrough.

Curriculum Architecture

Structured modules that build fluency session after session

Explore the complete roadmap—from foundational vocabulary to advanced professional expressions—crafted with practical immersion in mind.

What is AI?
Define artificial intelligence and identify its primary goals in enterprise contexts.
1.00 hrs
History and evolution of AI
Summarize the development of AI technologies and major milestones that shaped the field.
1.00 hrs
AI use cases in enterprise
Describe common AI use cases and their business value in modern organizations.
1.50 hrs

Ethics and responsible AI
Explain ethical considerations and principles for responsible AI deployment.
1.00 hrs
Key components of AI systems
Identify the essential components of AI systems including data, models, and infrastructure.
1.00 hrs

S/4 HANA system architecture
Describe the architecture of SAP S/4 HANA and how it supports real-time processing.
1.00 hrs
Core modules and data model
Explain core S/4 HANA modules and the underlying data model used for analytics and transactions.
1.50 hrs

In-memory computing and performance
Describe the impact of in-memory computing on application performance and analytics.
1.00 hrs
Extensibility and integration points
Identify extensibility options and integration points for connecting external services to S/4 HANA.
1.00 hrs
SAP Cloud Platform and services
Summarize relevant SAP cloud services that complement S/4 HANA for AI workloads.
1.00 hrs

Machine learning basics
Define machine learning and contrast supervised, unsupervised, and reinforcement learning.
1.00 hrs
Neural networks and deep learning
Explain the basics of neural networks and when deep learning techniques are appropriate.
1.00 hrs
Data preprocessing and feature engineering
Describe common data preprocessing steps and feature engineering techniques for model readiness.
1.50 hrs

Natural Language Processing
Summarize key NLP concepts and typical enterprise NLP use cases.
1.00 hrs
Computer Vision overview
Explain core computer vision techniques and scenarios where they apply in business processes.
1.00 hrs

APIs and service-based integration
Identify API-driven integration patterns for connecting AI services to S/4 HANA.
1.00 hrs
Event-driven and batch integration
Compare event-driven and batch integration approaches and their trade-offs for AI workflows.
1.00 hrs

Data pipelines and connectivity
Describe how to design data pipelines for reliable data flow between S/4 HANA and AI systems.
1.00 hrs
Data governance and quality
Explain the importance of data governance and methods to ensure high data quality for models.
1.50 hrs
Security and compliance considerations
Identify security controls and compliance requirements relevant to AI integrations in SAP.
1.00 hrs

Predictive maintenance example
Analyze a predictive maintenance case study and extract lessons relevant to implementation.
1.00 hrs
Finance and procurement use cases
Examine AI applications in finance and procurement and their measurable benefits.
1.00 hrs

Change management and adoption
Discuss strategies to drive user adoption and manage organizational change for AI projects.
1.00 hrs
Scaling AI solutions
Identify technical and operational challenges in scaling AI solutions across the enterprise.
1.00 hrs

Supervised learning algorithms
Describe common supervised algorithms and their appropriate problem types.
1.00 hrs
Unsupervised learning algorithms
Explain unsupervised techniques and how they are used for clustering and anomaly detection.
1.00 hrs
Reinforcement learning overview
Summarize core concepts of reinforcement learning and potential SAP use cases.
1.50 hrs

Model evaluation metrics
Define common evaluation metrics and how to choose them based on the business objective.
1.00 hrs
Monitoring and model drift
Explain methods to monitor models in production and detect drift over time.
1.00 hrs

AI Core capabilities
Describe the capabilities of SAP AI Core and how it supports model lifecycle management.
1.00 hrs
AI Foundation services and tools
Summarize AI Foundation services and tools available for building and operating AI solutions.
1.00 hrs

Model deployment workflows
Outline typical model deployment workflows and deployment considerations on SAP platforms.
1.00 hrs
CI/CD and MLOps practices
Explain CI/CD and MLOps best practices to ensure reliable model delivery and maintenance.
1.50 hrs

Data preparation and feature stores
Describe how to prepare data and use feature stores for reproducible model training.
1.00 hrs
Training and validation pipelines
Explain design of training and validation pipelines including cross-validation techniques.
1.00 hrs
Model optimization and tuning
Identify techniques for hyperparameter tuning and model optimization to improve performance.
1.00 hrs

Emerging AI technologies
Discuss emerging AI technologies and their potential impact on SAP ecosystems.
1.00 hrs
Implications for enterprise strategy
Analyze how future trends may influence enterprise strategy and technology roadmaps.
1.00 hrs

Key topic revision
Review core topics from the course and reinforce critical concepts for the exam.
1.00 hrs
Practice exams and time management
Practice exam questions under timed conditions and learn effective time management techniques.
1.00 hrs
Exam-day strategies and next steps
Learn practical exam-day strategies and recommended next steps after certification.
1.00 hrs
Upcoming Batches

Pick a schedule that fits your routine

We run multiple live cohorts so you can line up a batch with your goals, weekly bandwidth, and preferred mode of learning.

New cohorts are being planned

Share your interest and we will notify you as soon as the next batch opens.

Learner Voices

Stories from professionals who accelerated with SkillsBiz

Hear how learners leveraged mentor feedback, immersive projects, and certification support to reach their Mandarin goals.

N
Navpreet Kaur Bhatia
Learning SAP AI improved my understanding of intelligent workflows. Applying AI concepts inside SAP felt natural and business-focused.
S
Shikha Mathur
SAP AI concepts felt simple once they were connected to real workflows. Seeing predictions and insights in action made learning exciting.
N
Neha Malhotra
SAP AI helped me understand how artificial intelligence supports business decisions. Learning through real SAP use cases made the concepts easy to relate to.
I
Irfan Sabir
Understanding how AI models integrate with SAP workflows was very useful. The examples made it easy to see how decisions become faster and smarter.
R
Rohit Kaul
Learning how SAP uses AI for forecasting and decision support changed my perspective. Hands-on examples made it clear how businesses gain value from intelligent insights.
A
Amitabh Saran
SAP AI helped me understand how artificial intelligence fits into real business processes. Working with intelligent scenarios inside SAP made automation and predictions feel practical, not theoretical.
Frequently Asked Questions

Your questions, answered in one place

Everything you need to know before you commit—from certification timelines to support during the program.

The course duration is 44 hours.
The course is priced at INR 149999.
A basic understanding of SAP and programming concepts is recommended.
You will receive a certification on SAP A.I on S/4 HANA upon successful completion.
The course is conducted in English.
Yes, you will have lifetime access to the course materials.
Yes, the course includes several hands-on projects to enhance practical understanding.
Absolutely! There will be opportunities to ask questions during live sessions.
Yes, we offer a 30-day money-back guarantee if you are not satisfied.
You can reach out to our support team via email or chat on our website.

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We are trusted by leading accreditation bodies, ensuring your certificate is respected by employers worldwide.

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Awards & Recognitions

Celebrated for excellence in outcome-driven education

Our pedagogy, learner outcomes, and mentor network have been acknowledged by industry councils and global education forums.

Ready to fast-track your SAP A.I. (Artificial Intelligence) on S/4 HANA Certification Program mastery?

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