Red Hat Certified Specialist in AI (EX267) Related Real-Time Projects
Hands-On Learning for AI/ML Workload Deployment
Our EX267 training program includes industry-focused, real-world projects that prepare you for the Red Hat Certified Specialist in AI exam (EX267) and careers in Artificial Intelligence. These projects simulate enterprise AI scenarios, helping you master data science workflows, model training, and deployment on OpenShift AI.
Guided by expert trainers with 12+ years of experience, our labs help you build a strong portfolio to impress employers like Infosys, TCS, and Wipro. Both classroom and online training options are available with projects tailored for academic and corporate needs.
EX267 Classroom/Online Project List
- AI Model Training: Train and optimize ML models using JupyterHub and TensorFlow on OpenShift AI.
- Model Serving: Deploy machine learning models as RESTful services using Seldon or KFServing.
- Data Pipeline Automation: Automate ETL workflows and feature engineering with Apache Spark on OpenShift.
- GPU Workload Deployment: Run GPU-accelerated AI workloads and optimize performance on OpenShift clusters.
- Model Monitoring: Implement Prometheus/Grafana dashboards for tracking model performance in production.
- Data Security & Governance: Apply encryption, role-based access control (RBAC), and audit logs for AI workloads.
- CI/CD for AI Models: Build continuous integration pipelines for retraining and deploying ML models.
- Multi-Model Deployment: Deploy multiple AI models with versioning and traffic routing using canary releases.
- Edge AI: Deploy AI workloads at the edge using OpenShift Edge capabilities.
- End-to-End MLOps: Implement an MLOps pipeline for data ingestion, model training, deployment, and monitoring.
Note: We also provide customized project support tailored to your college, university, or corporate AI/ML requirements.