AI268 Developing and Deploying AI/ML Applications on Red Hat OpenShift AI with Exam Course Overview
AI268 Developing and Deploying AI/ML Applications on Red Hat OpenShift AI equips professionals with the skills to build, deploy, and manage AI and machine learning applications in a cloud-native environment. This course benefits data scientists, developers, and IT professionals by providing essential knowledge to leverage OpenShift AI for effective solutions in modern enterprises.
Course outline & what you'll learn
Overview of AI/ML applications
- Importance of Red Hat OpenShift AI
- Understanding OpenShift architecture
- Containerization and orchestration fundamentals
Overview of artificial intelligence and machine learning
- Key concepts: models, training, inference, and deployment
- Installing and configuring OpenShift
- Introduction to OpenShift CLI and web console
- Data preparation and preprocessing
- Selecting appropriate ML algorithms
- Building and training models using popular libraries (e.g., TensorFlow, PyTorch)
- CI/CD principles and practices
- Integrating model training pipelines with OpenShift
- Containerizing AI/ML applications
- Deploying applications on OpenShift
- Managing application lifecycle
- Implementing monitoring solutions
- Scaling applications based on demand
- Performance tuning and optimization
- Best practices for securing AI/ML applications
- Compliance considerations in AI/ML development
- Analyzing successful AI/ML deployments on OpenShift
- Lessons learned and best practices
- Review of key concepts and topics
- Practice exams and study tips
- Final Q&A session
- Resources for further learning and certification paths
Why train with Traincrest
This Red Hat course is delivered by Traincrest's certified instructors, live online or in the classroom, with hands-on labs and a 98% exam success rate. Trusted by 500+ companies and 50,000+ students worldwide.