Explore a variety of new data science tools available today; the different uses for these tools; and the benefits and challenges in deploying them in this 12-video course. First, examine a data science platform, the nucleus of technologies used to perform data science tasks. You will then explore the analysis process to inspect, clean, transform, and model data. Next, the course surveys integrating and exploring data, coding, and building models using that data, deploying the models to production, and delivering results through applications or by generating reports. You will see how a great data science platform should be flexible and scalable, and it should combine multiple features and capabilities that effectively centralize data science efforts. You will learn the six sequential steps of a typical data science workflow, from defining the objective for the project to reporting the results. Finally, explore DevOps, resources that allow developers and IT to work together in harmony which includes people, processes, and infrastructure; and its typical functionalities including integration, testing, packaging, as well as deployment.
Deploying Data Tools: Data Science Tools