AI253 Creating Machine Learning Models with Python and Red Hat OpenShift AI Course Overview
The AI253 course, "Creating Machine Learning Models with Python and Red Hat OpenShift AI," equips professionals with essential skills to build and deploy machine learning models. Ideal for data scientists, developers, and IT professionals, this course emphasizes practical applications and best practices, empowering participants to harness AI technologies effectively in real-world scenarios.
Course outline & what you'll learn
- Understanding AI and its applications
Overview of machine learning concepts
- Importance of cloud-native AI solutions
- Setting up the Python environment
- Key Python libraries for machine learning (NumPy, Pandas, Scikit-learn, etc.)
- Data manipulation and preprocessing techniques
Overview of OpenShift and its architecture
- Setting up OpenShift for AI applications
- Managing containers and deployments
- Selecting the right algorithm for the problem
- Training and testing models
- Evaluating model performance
- Best practices for deploying models in production
- Using OpenShift for scalable model deployment
- Continuous integration and continuous deployment (CI/CD) for ML models
- Techniques for model monitoring
- Handling model drift and retraining
- Ensuring ethical AI and compliance considerations
- Real-world applications of machine learning in various industries
- Hands-on projects utilizing Python and OpenShift
- Group discussions and presentations on projects
- Summary of key takeaways from the course
- Discussion on the future of AI and machine learning
- Resources for continued learning and development in AI
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.