OCI Certified Data Science Professional

Learnings:

• OCI Data Science - Introduction & Configuration
  • Discuss OCI Data Science Overview & Concepts
  • Understand the capabilities of Accelerated Data Science(ADS) SDK
  • Configure your tenancy for Data Science
• Design and Set up OCI Data Science Workspace
  • Create and manage Projects and Notebook sessions
  • Create and manage Conda environments
  • Store credentials via OCI Vault
  • Configure and manage source code in Code Repositories (Git)
• Implement end-to-end Machine Learning Lifecycle
  • Discuss ML Lifecycle Overview
  • Access data from different sources
  • Explore and Prepare data
  • Visualize and Profile data
  • Create and train models using OCI and Open source Libraries
  • Create and Use automated ML capability from Oracle AutoML
  • Evaluate models
  • Obtain Global & Local Model Explanations
  • Manage models using Model Catalog
  • Deploy & Invoke a Cataloged Model
• Apply MLOps Practices
  • Understand OCI MLOps Architecture
  • Create & Manage Jobs for custom tasks
  • Scale with OCI Data Science
  • Monitor & Log using MLOps Practices
  • Use Pipelines to automate machine learning workflow
• Use related OCI Services
  • Create and Manage Spark Applications using Data Flow and OCI Data Science
  • Understand OCI Open Data Service
  • Create and Export a Dataset using OCI Data Labeling
  • Use OCI AI Services for ML Solutions

Course Link: https://education.oracle.com/oracle-cloud-infrastructure-data-science-2023-professional/pexam_1Z0-1110-23