Certified AI Engineering Professional
The Certified AI Engineering Professional Certification equips technology professionals with the knowledge to design, develop, deploy, and optimize AI-powered systems. The program empowers professionals to build intelligent solutions, integrate AI models, automate engineering workflows, and drive scalable AI innovation across modern technology environments.
Learn directly from AI engineering experts, technology leaders, and industry professionals who are building intelligent systems, advanced AI solutions, and next-generation enterprise technologies.
What Sets Our Program Apart?
- Globally Recognized Certification with Self-Paced Learning
- 100+ Live Monthly Sessions via GSDC Studio
- Hands-On Learning with Learn by Doing
- 1-on-1 SME Connect Sessions with Industry Experts
- Career-Ready Support: Capstone project and Job support
100% Money Back Guarantee on One-Click
About AI Engineering certification
Objectives of Certified AI Engineering Professional
- Master the fundamentals of AI engineering, machine learning, Generative AI, and foundation models.
- Develop practical Python skills for building, testing, and maintaining AI applications.
- Build reliable AI data pipelines for collecting, cleaning, transforming, and preparing data.
- Develop and evaluate machine learning models using modern AI engineering practices and tools.
- Build Generative AI applications using LLMs, prompt engineering, context engineering, and function calling.
- Design RAG applications and AI agents using embeddings, vector databases, retrieval, tools, and orchestration.
- Deploy, monitor, optimize, and maintain AI systems using MLOps, cloud infrastructure, and production practices.
- Apply AI security, responsible AI, scalability, and reliability practices to enterprise AI engineering projects.
Benefits of AI Engineering Professional Certification
- Learn at your own pace with self-paced learning designed for working professionals and technology teams.
- Get personalized expert guidance through 3x 1-on-1 SME Connect sessions with industry professionals.
- Prepare with confidence through unlimited practice exam access plus 2 exam attempts, including 1 free retake.
- Earn a globally recognized AI engineering certificate that validates your practical AI development and engineering skills.
- Get lifetime GSDC Studio access with 100+ live monthly expert-led sessions covering AI, ML, Generative AI, MLOps, and emerging technologies.
- Build practical skills through the Learn by Doing approach using AI development, RAG, agents, MLOps, deployment, and monitoring activities.
- Strengthen your career profile with skills relevant to AI engineer, ML engineer, AI developer, MLOps, and AI software engineering roles.
- Stay updated with modern AI engineering practices through expert sessions, practical resources, and continuous learning opportunities.
Exam Syllabus of Certified AI Engineering Professional
1 Foundations of AI Engineering+
•Introduction to AI Engineering
•AI Engineering Lifecycle
•AI and ML Fundamentals
•Generative AI Fundamentals
•Foundation Models
•Large Language Models
•AI Engineering Roles
•AI Development Environments
•AI Engineering Tools
•AI Engineering Best Practices
2 Python & AI Development+
•Python for AI Engineering
•Python Libraries
•NumPy and Pandas
•Scikit-learn
•PyTorch and TensorFlow
•Jupyter Notebooks
•Git and Version Control
•AI Development Environments
•Code Organization
•Testing AI Code
3 Data Engineering for AI+
•AI Data Fundamentals
•Data Collection
•Data Ingestion
•Data Cleaning
•Data Preprocessing
•Feature Engineering
•Data Transformation
•Data Quality
•Data Labeling
•Data Pipelines
4 Machine Learning Model Development+
•ML Problem Definition
•Model Selection
•Supervised Learning
•Unsupervised Learning
•Classification
•Regression
•Clustering
•Model Training
•Hyperparameter Tuning
•Model Evaluation
5 Generative AI Engineering+
•Generative AI Development
•Foundation Model APIs
•LLM Application Development
•Prompt Engineering
•Context Engineering
•Structured Outputs
•Function Calling
•Model Selection
•Model Parameters
•Generative AI Evaluation
6 RAG & Knowledge-Based AI+
•RAG Fundamentals
•RAG Architecture
•Document Processing
•Chunking Strategies
•Embeddings
•Vector Databases
•Retrieval Methods
•Reranking
•RAG Evaluation
•RAG Optimization
7 AI Agents & AI Applications+
•AI Agent Fundamentals
•Agent Architecture
•Agent Workflows
•Tool Calling
•Agent Memory
•Agent Planning
•Agent Orchestration
•Multi-Agent Systems
•Human-Agent Interaction
•Agent Evaluation
8 AI Model Evaluation & Optimization+
•Model Evaluation
•Model Performance Metrics
•Generative AI Evaluation
•LLM Evaluation
•Accuracy and Quality
•Model Bias
•Error Analysis
•Model Optimization
•Inference Optimization
•Cost Optimization
9 MLOps & AI Engineering Pipelines+
•MLOps Fundamentals
•ML Pipelines
•Experiment Tracking
•Model Registry
•Data Versioning
•Model Versioning
•CI/CD for AI
•Pipeline Automation
•Pipeline Orchestration
•Reproducible AI
10 AI Deployment & Infrastructure+
•AI Deployment Fundamentals
•Model Serving
•Real-Time Inference
•Batch Inference
•REST APIs
•Containers for AI
•Docker
•Kubernetes
•GPU Infrastructure
•Cloud AI Platforms
11 AI Monitoring & Operations+
•AI System Monitoring
•Model Monitoring
•Data Drift
•Model Drift
•Performance Monitoring
•AI Observability
•Logging
•Alerting
•Model Retraining
•AI Incident Management
12 AI Security & Responsible Engineering+
•AI Security Fundamentals
•Secure AI Development
•Data Privacy
•Access Control
•Model Security
•AI Vulnerabilities
•Responsible AI
•Fairness and Bias
•Explainability
•Human Oversight
13 Production AI Engineering+
•Production AI Systems
•AI Scalability
•AI Reliability
•High Availability
•Performance Optimization
•AI Cost Management
•Disaster Recovery
•AI Technical Debt
•Production Troubleshooting
•Continual Improvement
14 Enterprise AI Engineering+
•AI Engineering Architecture
•AI Development Standards
•AI Engineering Workflows
•AI Platform Engineering
•AI Governance Integration
•AI Security Integration
•Engineering Documentation
•AI Engineering Metrics
•AI Project Delivery
•Future of AI Engineering
What Comes with a GSDC Certification?
You will receive a globally recognized GSDC Certified AI Engineering Professional certificate that validates your ability to build, deploy, and manage modern AI systems. The certificate demonstrates your knowledge of AI and ML fundamentals, Python development, data engineering, machine learning, Generative AI, LLM applications, prompt engineering, RAG, AI agents, model evaluation, MLOps, AI deployment, monitoring, security, and production AI engineering.
Learn from Experts
Learn from experienced practitioners and industry leaders who bring real-world expertise and practical insights to the program.
Maxim Salnikov
MICROSOFT
DIGITAL AND APP INNOVATION BUSINESS LEAD, WESTERN EUROPE
Hayk Hakobyan
INSIGHTGENIE
CO-FOUNDER
Artus Phee
AGILEASIA
CHIEF OPERATING OFFICER
Suvarsha Rai
AMAZON
SR. TECHNICAL PRODUCT MANAGER
Ziggy Rafiq
CAPGEMINI
SOFTWARE ENGINEERING LEAD
Trevor Wiseman
THE CIRCUIT
VP OF TECHNOLOGY & AI GOVERNANCE
Caleb Jephunneh
BRICKLABSAI
CEO | GLOBAL AI SPEAKER
Swathi Adimulam
ORACLE
OCI CLOUD & AI ARCHITECT
Leela VenkataSatish Kolla
LTIMINDTREE
DIRECTOR PROGRAM PROJECT MANAGEMENT
Baris Dirim
CULTUREASY
HUMAN SYSTEMS ARCHITECT
Enrollment Options
Single Access
Gain full access to our complete resource library and earn a globally recognized certification.
1 Certificate Programs
Bundle Access
Unlock exclusive bundle savings on premium resources and earn globally recognized credentials.
3 Certificate Programs
For Teams
Enable teams with GSDC certification pathways and customized learning journeys aligned with business priorities.
7 Day Money-Back Guarantee
Target Audience for Certified AI Engineering Professional
Pre-Requsities for AI Engineering Professional Certification
There are no mandatory prerequisites for the Certified AI Engineering Professional certification. A basic understanding of AI, programming, software development, or machine learning concepts is beneficial, but no formal technical or AI engineering background is required. The program builds from AI fundamentals and focuses on practical AI engineering, model development, intelligent systems, implementation, and AI solution deployment.
Exam Details Of Certified AI Engineering Professional
Exam Questions
40
Exam Format
Multiple choice
Language
English
Passing Score
65%
Duration
90 min
Open Book
No
Certification Validity
5 Years
Complimentary Retake
Yes
Sample Certification
About Certified AI Engineering Professional
The GSDC Certified AI Engineering Professional is a globally recognized professional credential designed for professionals who want to build, deploy, and manage production-ready AI systems. The program covers AI and ML fundamentals, Python for AI development, data engineering, machine learning, Generative AI, LLM application development, prompt engineering, RAG, AI agents, model evaluation, MLOps, AI deployment, monitoring, security, and enterprise AI engineering.
This AI engineering professional certification is ideal for AI engineers, ML engineers, software engineers, data engineers, Generative AI professionals, AI developers, MLOps professionals, cloud professionals, and technology professionals who want to build practical AI engineering capabilities. Learners develop skills to work with AI models, build RAG applications and AI agents, create ML pipelines, deploy AI systems, optimize model performance, monitor production environments, and apply secure and responsible AI engineering practices.
When you enroll, you'll receive comprehensive study materials, self-paced learning, 3x 1-on-1 SME Connect sessions, unlimited practice exam access, 2 exam attempts with 1 free retake, a globally recognized AI engineering professional certificate, and lifetime GSDC Studio access with 100+ live monthly expert-led sessions. You also get the Learn by Doing approach, Job Support Program, LinkedIn Enhancer, Resume Builder, and complimentary GSDC Membership to help you build practical AI engineering skills and advance your career as an AI engineering professional.