This course covers how to build, scale and operationalize machine learning models on Google Cloud Platform. You build ML models with TensorFlow, an open-source ML package and you can train and deploy them in a serverless way using Cloud ML Engine.

Setting Expectations on Data Science Projects with Kathleen Maley at the 2019 Women in Analytics Conference.

Learn how to share and secure the content you've created within MicroStrategy with other users both inside and outside of the MicroStrategy application.

It's important to have a projection of whether or not you will meet your targets so you can plan around it. In this course, you will learn how to create visual forecasts to help you monitor and share your project performance.

Discover methods for detecting anomalies in datasets using SQL, focusing on query techniques and pattern recognition.

Explore techniques for simple anomaly detection using SQL, focusing on query writing and data analysis for identifying outliers in datasets.

Learn how to fit and interpret linear regression with a single predictor variable

Learn how to fit and interpret linear regression with a single predictor variable

PyCaret is an open-source, machine learning library in Python. We can use it in machine learning tasks, from data preparation to model deployment.

Incorporating machine learning into data pipelines increases the ability to extract insights from data.

Snowflake is a fully managed petabyte-scale data platform solution, compatible across the three main cloud providers: AWS, Google Cloud, and Microsoft Azure. This course covers the concepts, design principles, and tools to help begin adoption.

Snowflake