Learn how to automate your entire pipeline using an automation tool. In this course students will learn how to programatically author, schedule and monitor their workflows. Students will also learn how to create an environment to containerize, replicate and deploy a pipeline.
A course that teaches a learner to write server-side code using Express. It walks learners through features required for effective web and mobile application development. By the end of this course students will be able to create a simple web server application with Express.
A course that teaches foundational knowledge of Node.js to leverage your understanding of JavaScript to create new and powerful applications.
A course that teaches foundational knowledge of Python language specifically for backend.
An introduction to GraphQL, what it is good for and how to use it to query or change data.
A theoretical course covering topics on how to handle data at scale and the different tools needed for orchestrating big data systems and manage the workflow. Learners will be able to dive into the vast world of data and computing at scale and get a comprehensive overview of the distributed resource management ecosystem.
A course that introduces learners to build tools for JavaScript, specifically linters and formatters. Learn how to use linters and formatters when building a React app.
A course that introduces you to build tools for JavaScript, specifically module bundlers. Learn about some popular module bundlers and how to use a module bundler when building a React app.
A course that introduces learners to build tools for JavaScript, specifically task runners. The courses covers popular task runners and what works best for JavaScript.
Discover how to quickly build and deploy production quality conversational AI applications with real-time transcription and natural language processing capabilities.
An introduction to the concept of web application scalability and the approaches used to scale an application.
Explore the fundamental tools and techniques for building highly effective recommender systems, as well as how to deploy GPU-accelerated solutions for real-time recommendations.
Learn how to optimize your code and to speed up current data processing using PySpark. In this course, students will work through best practices of how and when to use PySpark. They will explore what they can do with PySpark and how to use distributed computing within PySpark.
Explore how to use Transformer-based natural language processing models for text classification tasks, such as categorizing documents. You will also explore how to leverage Transformer-based models for named-entity recognition (NER) tasks and analyze various model features, constraints, and characteristics to determine which model is best suited for a particular use case―based on metrics, domain specificity, and available resources.
A course that goes over different types of caching and their use cases on client and server side.
A course that teaches continuous integration and continuous deployment to modernize and improve the software development lifecycle.
This course covers the clustering concepts of natural language processing, equipping learners with the ability to cluster text data into groups and topics by finding similarities between different documents.
An introduction to the concepts of Containerization and Virtualizations, and understanding the differences between them.
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