Quick Index for the Learning Sessions

Learning sessions are a popular resource in the community. To make them easy to find, we've created this quick index. And, our SMEs are always interested in hearing ideas for new learning sessions! If you have a burning AI/ML/DR topic that you don't see covered already, please click Comment and send it along!

Types of content for learning sessions

AI Success sessions

  • Evaluating an AI Use Case—How to move forward successfully with machine learning use cases. 
  • AI Problem Framing—Properly framed AI use cases are most effective at guiding businesses through current and future decision-making opportunities. This learning session presents considerations for framing effective AI use cases.
  • Change Management in the AI Space—Community DataRobot experts discuss the importance of change management in machine learning, best practices, and more. Join this learning session and learn tips for managing change in your business.
  • Identifying & Qualifying AI Use Cases—How to assess individual use cases and proactively identify and avoid blockers to getting an AI use case from data to business value.
  • AI Practitioner Worksheet #1: The Path to AI Success—Helping AI practitioners develop use cases; provides The Path to AI Success worksheet to help stakeholders collaborate on use cases.

Industry Solutions sessions

Model Building sessions

Data Engineering sessions

  • Code Generation—Predictions with Scoring Code—Exploration of DataRobot's exportable scoring code and several ways you can integrate these models into your data pipelines to achieve real operational value.
  • Scalable Batch Predictions—How to use the Batch Prediction API for scoring datasets, especially large datasets.
  • Interactive Dashboards—Big Data & ML—Ways to generate insights from big data and machine learning, and considerations for a building scoring pipeline for interactive dashboards.
  • Monitoring All Your Models with DataRobot Agents—Do you have machine learning models that are running outside of DataRobot? Is your organization using a set of diverse tools and platforms to deploy models, despite what IT wants? This session introduces DataRobot's MLOps agent framework which allows anyone to monitor models deployed externally, to DataRobot MLOps platform.
  • Model Creation and Scoring from Data—Guidance for using databases (specifically Snowflake) with DataRobot.
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