Help & Training

At the conclusion of this course, you will have a deep understanding of how to configure and maintain Anaconda Enterprise. You will practice common configuration tasks, user tasks, and troubleshoot errors.

Conda is a cross-platform package manager. In this course, you’ll learn how to build and maintain packages in any language, upload them to Anaconda Enterprise, and share them with other users. This hands-on course includes best-practices for Python package creation and management.

Learn how to create and share projects on Anaconda Enterprise. Access data in multiple formats and connect to big data storage systems like Spark/HIVE and relational databases. You’ll practice ingesting data from multiple sources to make quick visualizations and predictive models to gain insight from the data using the leading data science packages provided by Anaconda.

Learn how Anaconda Enterprise provides data scientists with unique abilities to create dashboards with as little as two lines of Python code. You’ll deploy the dashboards with one click and share them with your colleagues. This course covers advanced data visualization capabilities of Holoviews and Datashader.

Learn how to take the machine learning pipelines developed on your desktop, train them on Anaconda Enterprise using big data sources, and deploy them to the cluster. You’ll gain hands-on knowledge of how Anaconda Enterprise maintains reproducibility of the entire life-cycle of the model from development and training to production. You’ll practice building machine learning pipelines using leading packages provided by Anaconda.

At the conclusion of this 4-day course you will have a solid understanding of how Anaconda Enterprise and the Python ecosystem work together to help you perform quantitative and qualitative analyses. This course covers the core libraries for data processing and analysis, statistical computation, and an overview of machine learning. You’ll learn how to access tabular data stored in various file formats, relational databases, and big data systems.