Introduction to Red Hat OpenShift AI provides students with the basics of using Red Hat OpenShift AI for their AI/ML workloads. This course helps students build core skills such as describing the Red Hat OpenShift AI architecture, and organizing, executing and testing AI/ML code through hands-on experience. These skills can be applied in all versions of Red Hat OpenShift AI.
Course objectives:
Identify the main features of Red Hat OpenShift AI and describe the architecture and components of Red Hat AI.
Organize code and configuration by using data science projects, workbenches, and data connections.
Use Jupyter notebooks to execute and test code interactively.
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3 vidéos3 lectures
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3 vidéos•Total 24 minutes
Course Introduction•1 minute
Introduction to Red Hat OpenShift AI•12 minutes
Architecture•11 minutes
3 lectures•Total 30 minutes
Course Layout•10 minutes
Introduction to Red Hat OpenShift AI•10 minutes
Architecture•10 minutes
Data Science Projects
Module 2•2 heures à terminer
Détails du module
Inclus
6 vidéos4 lectures
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6 vidéos•Total 50 minutes
Data Science Projects•6 minutes
Sample Exercise: Data Science Projects•4 minutes
Workbenches•17 minutes
Sample Exercise: Workbenches•7 minutes
Data Connections•9 minutes
Sample Exercise: Data Connections•8 minutes
4 lectures•Total 40 minutes
Data Science Projects•10 minutes
Sample Exercise Context•10 minutes
Workbenches•10 minutes
Data Connections•10 minutes
Jupyter Notebooks
Module 3•1 heure à terminer
Détails du module
Inclus
4 vidéos2 lectures
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4 vidéos•Total 59 minutes
Introduction to Jupyter Notebooks•22 minutes
Sample Exercise: Introduction to Jupyter Notebooks•7 minutes
Collaboration with Jupyter Notebooks•25 minutes
Sample Exercise: Collaboration with Jupyter Notebooks•6 minutes
2 lectures•Total 20 minutes
Introduction to Jupyter Notebooks•10 minutes
Collaboration with Jupyter Notebooks•10 minutes
Comprehensive Review
Module 4•1 heure à terminer
Détails du module
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1 devoir
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