APIs

This course can also be taken for academic credit as ECEA 5348, part of CU Boulder’s Master of Science in Electrical Engineering degree. M2M and IoT Interface Design and Protocols is the third of three classes in the Embedded Interface Design (EID) specialization, an online version of the on-campus [...]

Getting data into your statistical analysis system can be one of the most challenging parts of any data science project. Data must be imported and harmonized into a coherent format before any insights can be obtained. You will learn how to get data into R from commonly used formats [...]

In this course, you will: • Compare Functional and Sequential APIs, discover new models you can build with the Functional API, and build a model that produces multiple outputs including a Siamese network; • Build custom loss functions (including the contrastive loss function used in a Siamese network) in [...]

This course, API Design and Fundamentals of Google Cloud's Apigee API Platform, is the first in a series of three courses in the Developing APIs for Google Cloud's Apigee API Platform specialization. This course introduces you to API design and the fundamentals of the Apigee platform. The second course [...]

This course teaches you to fetch and process data from services on the Internet. It covers Python list comprehensions and provides opportunities to practice extracting from and processing deeply nested data. You'll also learn how to use the Python requests module to interact with REST APIs and what to [...]

Learner Outcomes: After taking this course, you will be able to: utilize various Application Programming Interface (API) services to collect data from different social media sources such as YouTube, Twitter, and Flickr; process the collected data - primarily structured - using methods involving correlation, regression, and classification to derive [...]

In this course we briefly introduce the DCIC and the various Centers that collect data for LINCS. We then cover metadata and how metadata is linked to ontologies. We then present data processing and normalization methods to clean and harmonize LINCS data. This follow discussions about how data is [...]