Domino for Practitioners
Course summary: Learn about the full data science lifecycle within Domino. Learn how to connect to data sources and integrate with git, work with large data, and develop your model in an interactive environment with easy access to the tools you prefer. Then deploy the model using a model API, scheduled reports, and an interactive dashboard. Lastly, learn how to work with Domino programmatically.
Duration: Half-day
What you’ll learn:
- Collaboration, reproducibility, and tracking work in Domino
- How to create interactive dashboards, model APIs, and self-service web forms in Domino
- Using Domino datasets to work with large data
- Git integration and connecting to data sources
- Setting up environments to get access to the newest tools
- Using Domino programmatically through the API and command line interface
Introduction to Machine Learning
Course summary: Learn about each step in the data science workflow while using Python to clean real-world data and develop a machine learning model. We’ll cover the basics of both supervised and unsupervised models, how to determine the efficacy of your analysis, and how to improve your models. Throughout this course, we’ll see how Domino can speed up experiments and help you share and collaborate with your colleagues.
Duration: Full day
What you’ll learn:
- The basics of supervised and unsupervised machine learning models
- Various metrics for evaluating model performance
- How to improve a model through hyperparameter tuning, feature engineering and cross-validation
- Deploying your model for use in an interactive dashboard