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University of Maryland Global Campus — Artificial Intelligence

ARIN 320: Artificial Intelligence Applications

A complete guide to UMGC's ARIN 320: Artificial Intelligence Applications — what this course covers, typical assignments, and where to get expert help when a deadline is close.

Undergraduate 3 Credits UMGC

Artificial Intelligence Applications is a hands-on, no-programming-required course using real datasets from AWS and Microsoft to solve problems across business, science, and communications.

What ARIN 320 covers

(No programming or math background required.) An interactive, hands-on study of current artificial intelligence (AI) applications spanning multiple disciplines and domains, including business, science, communications, and computing. The goal is to use datasets with AI and machine learning applications from leading cloud vendors, including Amazon and Microsoft.

Projects and laboratory exercises demonstrate how AI can be used to solve problems across a wide variety of disciplines.

Typical ARIN 320 assignments

Expect a hands-on lab exercise requiring you to use a specific AWS or Microsoft AI/ML dataset tool to solve a problem in a given discipline.

Key topics in ARIN 320

Writing tips for ARIN 320

Follow the assignment instructions and rubric line by line

UMGC assignments for ARIN 320 are graded against a specific rubric or grading criteria your instructor provides — every requirement has to be visibly addressed. Skipping a requirement because it seems minor is one of the most common reasons a strong submission loses points.

Ground AI concepts in a specific, real application

Artificial Intelligence courses like ARIN 320 rarely reward describing AI capabilities in the abstract — evaluators want to see a specific application, dataset, or business problem the AI concept is actually being applied to, with the reasoning shown.

Address ethics, bias, or regulation explicitly where relevant

Both the AI and drone tracks at UMGC consistently grade whether ethical, bias, privacy, or regulatory considerations are addressed explicitly — a technically sound solution that ignores these dimensions is one of the most common ways students lose points.

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Why students seek help with ARIN 320

Students sometimes describe AI application possibilities without the hands-on dataset/tool work the lab specifically requires — the rubric typically wants that hands-on lab evidence shown, not conceptual description alone.

How GradeEssays helps with ARIN 320

Share your lab assignment and rubric, and your writer will help document the hands-on AWS/Microsoft AI tool work your lab requires.

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Prerequisites and course context

ARIN 320 has no prerequisites and requires no programming or math background. Note: students may receive credit for only one of ARIN 320 or CMSC 307.

Related courses

Frequently asked questions

Do I need a programming background for ARIN 320?

No — the catalog explicitly states no programming or math background is required, since the course is a hands-on, applied study of AI applications using existing cloud-vendor tools.

Can another course substitute for ARIN 320?

Students may receive credit for only one of ARIN 320 or CMSC 307, since they cover the same AI applications content.