Use cases

• Data governance use case
  
• Data integration use case
  
• Data Science and MLOps use case
  
• AI governance use case
  
• Data fabric in action

AI governance

• Build and deploy a model
  
• Test and validate the model
  

Data integration

• Integrate data
  
• Virtualize external data
  
• Replicate data
  
• Orchestrate an AI pipeline with data integration
  

Data Science and MLOps

• Orchestrate an AI pipeline with model monitoring
  
• Orchestrate an AI pipeline with data integration
  

Data governance

• Curate high quality data
  
• Protect your data
  
• Consume your data
  
• Govern virtualized data
  

Get started

• Sign up for Cloud Pak for Data as a Service
  
• Create a project
  
• Tour the Resource Hub
  
• Create a catalog and find assets quickly
  
• Collaborate on projects
  

Guided tutorials

• Part 1: Explore and prepare data
  
• Part 2: Build and deploy a machine learning model
  
• Part 3: Build a model in a notebook
  
• Data fabric: Build and deploy a model
  
• Data fabric: Test and validate the model
  

Data connections

• Add platform connections
  
• Add data from a connection to a project
  
• Create a folder asset connection in a project
  
• Manage object storage
  
• Import asset metadata from an external source into a project
  

Notebook basics

• Jupyter notebook basics
  
• Create a Jupyter notebook and custom environment in a project
  
• Load and analyze public data sets
  
• Publish notebooks to GitHub from a project
  

Notebook examples

• Analyze NY restaurant inspections data
  
• Use Spark R to load data and run SQL queries
  
• Analyze precipitation data
  
• Analyze Db2 Warehouse data
  
• Use the SQL-Cloudant connector with Python
  

Build models with AutoAI

• Run a sample AutoAI experiment to create a model
  
• Build a binary classification model
  
• Build a multiclass classification model
  
• Train a multivariate time series model
  
• Run a time series experiment in a notebook
  
• Create a model that evaluates and improves fairness
  
• Perform sentiment analysis on text
  
• Create a pipeline to automate machine learning models
  
• Data fabric: Orchestrate an AI pipeline with model monitoring
  
• Data fabric: Orchestrate an AI pipeline with data integration
  

Build models with SPSS Modeler

• Build and deploy a predictive analytic model to diagnose disease
  
• Build a chi-squared machine learning model
  
• Import an SPSS Modeler flow into a project
  
• Mine data using text analytics
  

Manage models

• Build, deploy, and test a model in a notebook
  
• Test a model using the machine learning APIs
  
• Evaluate a machine learning model
  
• Create a model use with approaches
  
• Track machine learning model asset activities
  
• Provision watsonx.ai Runtime in IBM Cloud
  

Decision optimization

• Run a sample Decision Optimization experiment
  
• Use advanced features in the modeling assistant
  
• Change environments and add Python extensions to your experiment
  
• Create advanced custom constraints with Python DOcplex
  
• Other Decision Optimization videos
  

Federated Learning

• Federated Learning overview
  
• Create a Federated Learning Experiment
  

RStudio

• Overview of RStudio IDE
  
• Load data
  
• Connect to external data sources
  
• Run Shiny applications
  

Get started

• Sign up for Cloud Pak for Data as a Service
  
• Create a project
  
• Tour the Resource Hub
  
• Create a catalog and find assets quickly
  
• Collaborate on projects
  

Guided tutorials

• Part 1: Explore and prepare data
  
• Data fabric: Integrate data
  
• Data fabric: Virtualize external data
  
• Data fabric: Configure a 360 degree view
  
• Data fabric: Explore your customers
  

Data Refinery

• Add connected data from a data source to a project
  
• Shape data
  
• Copy data to a new target
  
• Blend data from multiple sources
  
• Data Refinery operations video series
  

DataStage

• Data fabric: Integrate data
  
• Add connected data from a data source to a project
  
• Create a simple DataStage flow
  
• Import a DataStage flow into a project
  
• Schedule a DataStage flow to run
  
• Create a data definition
  
• Use DataStage to load enterprise data into Snowflake
  
• DataStage connectors and stages video series
  

Data Virtualization

• Data fabric: Virtualize external data
  
• Add virtualized data to a project or catalog
  
• Overview of Data Virtualization
  

Match 360

• Data fabric: Configure a 360 degree view
  

Data Replication

• Data fabric: Replicate data
  

Get started

• Sign up for Cloud Pak for Data as a Service
  
• Create a project
  
• Tour the Resource Hub
  
• Create a catalog and find assets quickly
  
• Collaborate on projects
  

Guided tutorials

• Data fabric: Curate high quality data
  
• Data fabric: Protect your data
  
• Data fabric: Consume your data
  

IBM Knowledge Catalog basics

• IBM Knowledge Catalog overview
  
• Create a catalog and find assets quickly
  
• Use catalog assets in a project
  

Data connections in a catalog

• Add platform connections
  
• Add assets to a catalog
  
• Create a folder asset in a catalog
  
• Import asset metadata from an external source into a project
  

Catalog data governance

• Data policies overview
  
• Organize governance artifacts with categories
  
• Mask data
  
• Track data asset activities
  
• Track machine learning model asset activities
  
• Enable advanced masking options and create a masking flow
  

Account administrators

• Set up basic access groups in IBM Cloud
  
• Invite users to your IBM Cloud account
  
• Set up Cloud Object Storage for administrators
  

Project administrators

• Collaborate on projects