Avila University MS in Tech Management with Machine Learning Degree

Program Overview

Graduate Studies

The Master of Science in Technology Management: Artificial Intelligence program at Avila University Arizona is designed for full-time students seeking to master AI technologies and leadership skills. The program blends on-campus learning with online convenience. Students can complete this 30-credit degree in as few as 16 months, with start dates available in August, January, and May.

Machine Learning Component of the Program

Tprogram has a strong machine learning (ML) focus, integrated throughout its coursework and project-based experiences.

Key courses like AI 630 – Neural Networks and Deeper Learning and AI 661 – AI and Machine Learning provide comprehensive instruction on ML theory and practical applications. Students learn to design, implement, and evaluate ML models for tasks like pattern recognition and intelligent decision-making.

The curriculum also includes AI 615 – Natural Language Processing and AI 620 – Principles of Computer Vision, where students apply ML techniques to real-world scenarios like sentiment analysis and object detection.

AI 600 – Intro to Artificial Intelligence establishes foundational ML concepts, while AI 640 – AI Strategy and Applications connects ML applications to strategic business solutions.

Through hands-on projects, students use tools like TensorFlow and PyTorch to build ML models and apply algorithms such as convolutional neural networks, recurrent networks, and deep learning methods. These experiences ensure that graduates are skilled in applying ML technologies to solve complex problems across industries, making this degree a robust and comprehensive choice for those seeking advanced ML expertise.

Curriculum and Courses

Core courses focus on organizational behavior, project management, leadership, and innovation. Concentration courses cover topics like AI Strategy and Applications, Natural Language Processing, Principles of Computer Vision, and Neural Networks & Deeper Learning. Students also explore Ethical AI Design & Policy and gain real-world experience through an Applied Research Project or Internship.

Core classes include:

BU 601 – Behavior, Well-being, and Ethics
BU 601 explores individual and group behavior within organizations, emphasizing stress management, well-being, and ethical responsibilities. The course covers topics such as emotions, diversity, job satisfaction, virtual communication, and negotiation. Students develop skills for ethical leadership and effective management in today’s business environment.

OD 655 – Innovation & Creativity
OD 655 examines the role of creativity and innovation in leadership and organizational development. Students learn to apply these concepts to problem-solving, human resources, team dynamics, and diversity initiatives. The course helps students enhance organizational effectiveness and adaptability by fostering creative thinking and innovation.

OD 688 – Leadership & Influence Processes
OD 688 provides a deep dive into leadership theories and models. It examines the impact of organizational structures, followers, and change processes on leadership effectiveness. Students develop their own leadership principles and apply theoretical knowledge to organizational dynamics.

PM 672 – The Practice of Project Management
PM 672 gives students a thorough understanding of project management approaches, metrics, and methodologies, including IPECC, agile, and scrum. The course balances technical and interpersonal skills, emphasizing project lifecycle planning and conflict management. It prepares students for project success and PMP certification.

MG 695 – Applied Research Project
MG 695 is the capstone project for the program, requiring students to integrate theory and practice in a faculty-approved project. Students conduct research, develop proposals, and recommend actions based on data analysis, demonstrating professional competence and readiness for advanced roles.

BU 695 – Internship
BU 695 offers hands-on learning through internships, allowing students to apply academic knowledge in real-world settings. The course focuses on workplace skills such as teamwork, problem-solving, and communication. Students gain valuable experience and build networks for career development.

AI 600 – Intro to Artificial Intelligence
AI 600 introduces students to AI technologies like machine learning, natural language processing, and computer vision. It covers both the history and practical applications of AI, with a focus on ethical and societal impacts. Students gain foundational skills to design and apply AI solutions responsibly.

AI 605 – Ethical AI Design and Policy
AI 605 addresses the ethical challenges of AI development and deployment. Students explore concepts like fairness, accountability, transparency, and privacy while designing ethical AI systems and crafting policy recommendations. The course bridges technology, ethics, law, and policy for responsible AI innovation.

AI 615 – Natural Language Processing
AI 615 covers theoretical and practical aspects of NLP, including syntax, semantics, and pragmatics. Students explore applications like sentiment analysis and named entity recognition, using tools like NLTK and spaCy. Ethical issues in NLP, such as fairness and privacy, are also discussed.

AI 620 – Principles of Computer Vision
AI 620 teaches students the fundamentals of computer vision, including image processing and object detection. The course combines traditional techniques with machine learning algorithms for visual information interpretation. Ethical considerations, including privacy and bias, are key discussion points.

AI 630 – Neural Networks and Deeper Learning
AI 630 focuses on the architecture and training of deep learning models, including CNNs and RNNs. Students learn to apply these techniques to tasks like computer vision and NLP using frameworks such as TensorFlow and PyTorch. Ethical and bias considerations in deep learning are also explored.

AI 640 – AI Strategy and Applications
AI 640 connects AI technologies with business goals to drive innovation. The course covers AI strategies and applications across industries, emphasizing alignment with organizational objectives. Ethical and societal impacts of AI in business are discussed alongside practical project management.

AI 661 – AI and Machine Learning
AI 661 covers core AI and machine learning concepts and applications, including deep learning and reinforcement learning. Students gain hands-on experience with tools like TensorFlow and PyTorch to solve real-world problems. The course also addresses ethical considerations in AI applications.

Tuition

The total estimated program cost is about $27,365, including tuition, fees, and insurance costs for international students. Domestic and international students benefit from the university’s competitive rates and financial aid opportunities.

Admissions and Requirements

To apply, students must hold a bachelor’s degree from an accredited institution and meet a minimum GPA of 2.75 (or provisional admission for a 2.50–2.74 GPA).

Those with 15+ credits in computer science, cybersecurity, or business analytics may have introductory courses waived. Additional documents include transcripts, proof of English proficiency, and letters of recommendation.

Who Should Apply

This program suits aspiring AI specialists, data scientists, engineers, and project managers seeking to integrate AI solutions in diverse industries. It’s a strong fit for professionals looking to develop technical and strategic skills in AI applications.

Program Outcomes and Flexibility

Graduates are prepared for roles like AI consultant, NLP engineer, or chief AI officer, equipped with expertise in responsible AI use and ethical decision-making. The program’s STEM designation makes it OPT-eligible for international students, supporting career advancement in the U.S. and globally.