Very Large Information Systems Lecture & Lab - Adjunct Faculty - Traditional Campus - (Spring 2027) - College of Engineering and Technology

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The College of Engineering and Technology employs faculty and faculty leaders who are passionate about engaging and mentoring students to best prepare them for the continuously changing worlds of IT and Engineering. Our faculty are energetic advisors who are committed to helping our students grow academically, spiritually, and personally. They are experts in their respective fields, in addition to being passionate educators and collaborators who help enhance the college experience for all students.

Join our mission in helping others find their purpose and start your instructor career with GCU. The College of Engineering and Technology offers rewarding opportunities for adjunct faculty to teach part-time, face-to-face instruction at our Phoenix campus. If you are highly motivated and passionate about teaching exceptional quality instruction in modern facilities with smaller class sizes, we’d like to hear from you.

Gcu Traditional Campus – Phoenix, AZ

• Courses are in-person and on-campus for the Spring 2027 Semester (01/04/2027 - 04/23/2027)

Course: Very Large Information Systems Lecture & Lab

This course introduces modern theories of machine learning and design & implementation models for large scale quantitative, image, and text information systems. The machine learning and information retrieval includes methodologies such as Boolean, vector space, probabilistic, inference net, and language modeling.

Students will acquire hands-on experience by implementing models such as clustering algorithms, automatic text categorization, and experimental evaluation. As an introduction to data science theory and techniques, students will experiment with supervised and unsupervised learning algorithms, intelligent text summarization, topic detection, tagging, and tracking.

The laboratory reinforces and expands learning of principles introduced in the lecture. Hands-on activities focus on implementing techniques for efficiently managing and manipulating very large data sets and build machine learning models.

What You Will Do

• Facilitate classroom lecture and discussions
• Engage students in learning course objectives and topics
• Assess student performance and mentor success in the classroom
• Provide a positive example to students by supporting the University’s Doctrinal Statement, Ethical Position Statement, and Mission of Grand Canyon University

What You Will Bring

• Preferred: Master's in Computer Science or Statistics or closely related degree AND experience in Big Data Analytics or Data Science with proficiency in Python.
• Minimum: Bachelor in Statistics or closely related degree AND 5 or more years of experience in Big Data Analytics or Data Science with proficiency in Python.
• All candidates must be proficient in Python programming, with an emphasis on pandas, numpy, matplotlib, scikit, and tensorflow.

Before submitting your application, please attach the following to review:

• Your unofficial transcript reflecting degree earned with 18 graduate credit hours in the areas listed above
• Your unofficial transcripts for any applicable conferred graduate degrees

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