University of Maryland Global Campus 3 credits ARIN
(Formerly DATA 655) Prerequisite: DATA 645. A practical exploration of the fundamental concepts, architectures, and applications of deep learning in the field of artificial intelligence. The goal is to develop deep learning models and apply them to solve real-world problems in a wide range of domains, such as healthcare, finance, marketing, and cybersecurity. Topics include backpropagation, convolutional networks, recurrent networks, and generative adversarial networks, and their applications. Students may receive credit for only one of the following courses: DATA 655 or ARIN 655.
Our subject experts help with essays, research papers, case studies, discussion posts, and capstone projects for these programs β written from scratch to your course requirements.
Program and course information is reproduced from each university's published academic catalog for informational purposes and may change. Always confirm current requirements with your university. We are an independent academic support service and are not affiliated with or endorsed by the universities listed.
Expert guides on essay writing, citation styles, study skills, and academic success.
View All Articles
Learn how to write a good research question for a paper. Narrow your topic, identify a research problem, and create a focused question with practical examples.
Learn how to choose a research topic you can actually research. Discover how to narrow broad ideas, find reliable sources, and develop a focused research question.
Learn how to cite sources in a research paper using APA, MLA, and Chicago styles, with in-text citation examples and reference-list tips.