The Oracle Cloud Infrastructure Data Science Certified Professional certification is intended for data scientists and other professionals responsible for building data science solutions and managing the complete lifecycle of machine learning models. The certification validates a candidate’s ability to effectively identify OCI services used for implementing machine learning solutions for specific business use cases. It also validates a candidate’s ability to incorporate machine learning best practices.
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The Oracle Cloud Infrastructure Data Science Certified Professional certification is intended for data scientists and other professionals responsible for building data science solutions and managing the complete lifecycle of machine learning models. The certification validates a candidate’s ability to effectively identify OCI services used for implementing machine learning solutions for specific business use cases. It also validates a candidate’s ability to incorporate machine learning best practices.
The OCI Data Science exam focuses on key areas essential for leveraging Oracle Cloud Infrastructure in machine learning workflows. It begins with foundational knowledge, including an overview of OCI Data Science and configuration of the tenancy and ADS SDK (10%). Candidates must also be able to design and set up the Data Science workspace, manage projects, notebook sessions, Conda environments, credentials, and source code repositories (15%). A major portion of the exam emphasizes implementing the end-to-end machine learning lifecycle (45%), covering data sourcing, exploration, preparation, visualization, modeling (using both OCI and open-source tools), AutoML, model evaluation, explanations, and deployment through the Model Catalog. It also includes emerging technologies such as generative AI integration, LangChain deployment, and AI Quick Actions. MLOps practices (20%) are another critical area, requiring knowledge of OCI MLOps architecture, job management, autoscaling, monitoring, and pipeline automation. Finally, candidates should understand the use of related OCI services (10%) like Data Flow for Spark applications, the Open Data Service, and Data Labeling for dataset creation and export.
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