Ranked in Top 10 MRes in Artificial Intelligence

MRes in Artificial Intelligence

20 Months | No GRE/TOEFL Required

Advance your career in the rapidly growing field of Artificial Intelligence with the MRes in Artificial Intelligence program. Gain cutting-edge skills in machine learning, deep learning, AI ethics, and natural language processing to make impactful decisions in the AI-driven business world. GRE and get exclusive modules on Generative AI, AI in Healthcare, Robotics, and more.

  • You can start the process for just 5000 rupees
  • Post-study work visa for 2 years
  • 90% Placement rate
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Application Closes: August 15

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Start Date

September 2025

Duration

Full-time (12 months)

Application Deadline

August 15

Program Fee

£9000 per year

Apply Now

Key Highlights:

  • 3 Years STEM OPT Visa
  • Quick Application With No Additional Tests
  • Hands-On AI Project Experience
  • Learn in-Person from World-Class Faculty
  • You can start the process for just 5000 rupees
  • Alumni Status From University of Arizona
  • Practical Insights From Industry Experts

#10 Best Business Analytics Program

U.S. News & World Report 2023

#50 in Best Business Schools

U.S. News & World Report 2024

Top 100 Global University

U.S. News & World Report 2021

Top 0.47% Worldwide University

Center for World University Rankings 2022

Skills:

Machine Learning
Deep Learning
Natural Language Processing
Data Science
AI Ethics
Robotics
Computer Vision
Neural Networks

Our alumni work at top companies

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Course Modules

Year 1

Module: 7CS110
Credits: 30
Period: 1
Type: Core
Locations:University: City Campus; University and Blended Learning

This module provides students with a comprehensive introduction to the theory and applications of artificial intelligence (AI). Throughout the module, students will learn the theory behind different AI methods and how to apply them to real-world problems. The latest cutting-edge AI technologies and necessary knowledge acting as a stepping stone to carry out research in AI are also discussed in this module.

Module: 7CS113
Credits: 120
Period: 1
Type: Core
Locations:University and Blended Learning; University: City Campus

The Dissertation is an independent study module in which students will negotiate, plan, manage and execute a programme of research and analysis. In addition, students will develop skills in critical thinking and report writing. Students will complete a research dissertation within their computing discipline.

Module: 7CS112
Credits: 30
Period: 1
Type: Core
Locations:University and Blended Learning; University: City Campus

In order to understand and make predictions researchers need to be able to not only assess, examine and interpret data, but also be able to communicate their findings in ways that conveys empirical rigor and trustworthiness. This module will set learners on the path to scientific success by supporting the development of competencies such as the formulation of research ideas, the design of research studies that enable the collection and analysis of valid data whilst operating within the parameters of ethical principles. Students will develop their analytical literacy, learn how to perform systematic and objective literature searches and reviews, to design robust methodologies and apply appropriate data analyses to test research questions. At the end of the module, students will submit a research proposal which will evidence their competency in designing a research study, and selecting an appropriate method. Students will benefit from knowledge of a number of transferable skills such as decision making, problem solving, data management, critical appraisal of written content and report writing skills.

About MRes in Artificial Intelligence

The MRes in Artificial Intelligence at the University of Arizona is an advanced, in-depth program designed to equip you with cutting-edge AI skills. The program combines online and in-person learning, guided by expert faculty to provide a comprehensive understanding of AI, machine learning, and deep learning applications.

The MRes in Artificial Intelligence is a research-focused master’s program that dives deep into AI concepts, technologies, and applications. This program blends theoretical knowledge with hands-on research experience to prepare you for a career in the rapidly evolving AI field.

The MRes in Artificial Intelligence follows a flexible and comprehensive curriculum covering core topics like machine learning, deep learning, natural language processing, robotics, and AI ethics. The program includes coursework, research opportunities, and project-based learning for practical experience.

This program is ideal for those who are passionate about AI and want to build a career in machine learning, data science, or robotics. It’s also suitable for professionals seeking to upgrade their skills or those with a background in computer science, engineering, or related fields.

  • 3 Years STEM OPT Visa in USA
  • Quick Application Process with No Additional Tests
  • Learn In-Person from World-Class Faculty
  • Research and Project Experience in AI
  • Save up to INR 55+ Lakhs
  • Alumni Status from University of Arizona
  • Practical Insights from Industry Experts

By the end of the program, students will have developed strong analytical and programming skills, enabling them to:

  • Apply machine learning and AI techniques to solve real-world problems.
  • Gain proficiency in tools like Python, TensorFlow, and other AI frameworks.
  • Conduct cutting-edge AI research and development.
  • Contribute to advancements in AI across industries.

The faculty for the MRes in Artificial Intelligence includes experienced researchers and practitioners from top academic and industry backgrounds, specializing in machine learning, robotics, computer vision, and AI applications across various sectors.

Applicants should have a strong background in mathematics, computer science, or engineering. A bachelor’s degree in a related field is typically required, though specific prerequisites may vary.

Yes, the MRes in Artificial Intelligence is a STEM-designated program, which offers up to three years of Optional Practical Training (OPT) for international students.

Do I Need a Technical Undergraduate Degree to Start the Program?

Discover Chandler, your academic destination

  • Regarded as one of the most financially stable cities in the United States.
  • Chandler is home to high-profile global companies, offering excellent career opportunities for graduates.
  • The city’s fast-growing workforce and proximity to major tech players provide a conducive environment for innovation and networking.
  • Chandler is ranked as one of the best cities for first-time home buyers, making it a great location for students and professionals alike.
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Curriculum

Pursue a Master of Research (MRes) in Artificial Intelligence at the University of Arizona without the need for GRE/GMAT. The program curriculum includes foundational courses, core courses, and specialized AI elective courses, preparing you for cutting-edge research and practical applications in Artificial Intelligence. The MRes in AI is ideal for gaining advanced knowledge in AI and applying for up to a 3-year STEM OPT visa, making it an excellent study abroad opportunity.

AI Foundation (6 units)

The “AI Foundation” courses provide essential knowledge in key AI concepts and foundational skills. This section prepares you to understand the broader context in which AI and machine learning operate. Here’s an explanation of each course in this section:

  1. Introduction to Machine Learning (2 units)
    This course covers the fundamentals of machine learning. You will explore key techniques such as supervised learning, unsupervised learning, classification, regression, and clustering. By the end of this course, you will understand how to apply machine learning algorithms to real-world data problems.

  2. Introduction to Deep Learning (2 units)
    In this course, you will learn about the architecture and algorithms used in deep learning, including neural networks, convolutional neural networks (CNNs), and recurrent neural networks (RNNs). Deep learning is one of the most powerful techniques in AI and this course provides a strong foundation for exploring complex AI models.

  3. AI Ethics and Social Implications (2 units)
    This course focuses on the ethical considerations of AI. You will study issues such as bias in AI, privacy, accountability, and the societal impact of AI technologies. Understanding these ethical challenges is crucial for developing responsible AI solutions.

AI & Data Science Foundation (6 units)

The “AI & Data Science Foundation” courses provide a technical and analytical base. These courses will equip you with the necessary data science skills for AI research and applications.

  1. Statistical Methods for AI (2 units)
    This course covers the statistical methods and techniques used in AI and machine learning, including probability distributions, hypothesis testing, and statistical inference. You will learn how to apply these methods to analyze and interpret complex data sets, which is a key skill in AI research.

  2. Python for AI Programming (2 units)
    In this course, you will be introduced to Python programming, focusing on its applications in AI and machine learning. You will learn to work with libraries such as TensorFlow, PyTorch, and Scikit-learn to implement AI algorithms and models.

  3. Data Structures and Algorithms for AI (2 units)
    This course provides you with a strong foundation in data structures and algorithms, which are essential for designing efficient AI systems. Topics include linked lists, trees, graphs, sorting algorithms, and more. You will learn how to choose and apply the right data structures and algorithms in AI problem-solving.

Core AI Courses

In addition to the foundational courses, the MRes in Artificial Intelligence includes core courses that cover advanced AI topics. These courses are designed to deepen your knowledge in areas like machine learning, deep learning, natural language processing, and computer vision.

  1. Advanced Machine Learning (3 units)
    This course focuses on advanced machine learning techniques, including ensemble methods, reinforcement learning, and model optimization. You will explore the practical applications of these techniques and their potential in solving real-world problems.

  2. Natural Language Processing (3 units)
    This course covers techniques for working with natural language data, such as text processing, sentiment analysis, and language models. You will learn how to apply AI to analyze and generate human language, an important application of AI.

  3. Computer Vision (3 units)
    This course focuses on the methods and technologies used in computer vision, including image processing, object detection, and facial recognition. You will gain hands-on experience with popular computer vision tools and techniques used in AI.

AI Electives

The program also includes specialized elective courses where you can explore specific areas of AI, such as robotics, AI for healthcare, and ethical AI.

  1. AI for Robotics (3 units)
    This elective covers the use of AI in robotics, including autonomous robots, perception systems, and reinforcement learning for robotics. You will learn to develop intelligent robotic systems capable of performing tasks autonomously.

  2. AI for Healthcare (3 units)
    In this course, you will explore the application of AI in healthcare, including predictive modeling for diseases, medical image analysis, and personalized medicine. You will learn how AI is revolutionizing the healthcare industry.

  3. Reinforcement Learning (3 units)
    This elective covers reinforcement learning, a key area of AI that involves training models to make decisions based on rewards and penalties. You will learn about algorithms such as Q-learning and deep reinforcement learning.

The curriculum is designed to provide a balanced combination of theoretical knowledge and practical skills, preparing you for a successful career in AI research and development.

 
 

Advanced Machine Learning (3 units)

This course focuses on advanced machine learning techniques, including ensemble methods, reinforcement learning, and deep learning optimization. You will gain hands-on experience applying these methods to real-world problems, helping you build more sophisticated AI models.

AI in Robotics (3 units)

In this course, you will explore how artificial intelligence is applied in robotics. Topics include autonomous robots, robot perception, reinforcement learning for robotics, and the integration of AI systems into physical machines. This course will prepare you to design and develop intelligent robotic systems.

Natural Language Processing (3 units)

This course will delve into the AI techniques used to process and understand human language. You will study methods like sentiment analysis, text classification, and language modeling, learning how to build systems that can interact with and analyze human language.

Deep Learning for AI (3 units)

This course provides a deep dive into deep learning algorithms, covering neural networks, convolutional neural networks (CNNs), and recurrent neural networks (RNNs). You will learn how to build and train deep learning models for complex tasks like image recognition, time-series prediction, and language generation.

Elective Courses

AI for Healthcare (3 units)

This elective explores how AI is transforming the healthcare industry. You will learn about predictive modeling in healthcare, medical image analysis using AI, and personalized medicine applications. This course will equip you with the knowledge to implement AI solutions that improve healthcare outcomes.

Reinforcement Learning (3 units)

In this elective, you will explore reinforcement learning (RL), a key area of AI that focuses on teaching models to make decisions based on rewards and penalties. Topics include Q-learning, policy gradient methods, and deep reinforcement learning. You will apply RL techniques to problems like game playing and autonomous systems.

AI Ethics and Responsible AI (3 units)

This course focuses on the ethical implications of AI technologies. You will study issues like bias in AI models, privacy concerns, accountability in AI systems, and the broader social impact of AI. By the end of this course, you will understand how to develop responsible AI systems that align with ethical guidelines.

AI in Business Analytics (3 units)

This elective focuses on the application of AI techniques in business analytics. You will learn how to leverage AI for tasks such as predictive analytics, customer segmentation, and demand forecasting. This course will prepare you to use AI to drive data-driven business decisions.

Practical Application Courses

AI Research Project (3 units)

In this capstone course, you will apply your knowledge to a real-world AI research project. Working alongside faculty, you will address a specific AI challenge, employing techniques from machine learning, deep learning, and reinforcement learning. This project will allow you to demonstrate your research abilities and contribute to the advancement of AI technology.

AI Business Consulting Project (3 units)

This course will enable you to apply your AI and machine learning knowledge in a business consulting context. You will work on a real-world project where you provide AI-driven insights to help solve business challenges, showcasing your ability to integrate AI tools into business decision-making.

This curriculum ensures you not only gain in-depth technical knowledge of AI but also practical experience in applying AI methods to real-world challenges across various industries. Whether your focus is on healthcare, robotics, or business analytics, the MRes in Artificial Intelligence program will prepare you for an impactful career in AI research and application.

 

The MRes in Artificial Intelligence syllabus includes specialized elective courses, giving you the flexibility to tailor your learning to your specific career goals and interests. Choose from a list of elective courses that allow you to dive deeper into advanced AI topics and specialized applications of artificial intelligence.

Elective Courses in AI

Optimization for AI Systems

This elective focuses on optimization techniques applied to artificial intelligence systems. You will learn strategies to improve the efficiency and performance of AI models, focusing on methods like linear programming, convex optimization, and evolutionary algorithms. This course equips you with the skills to enhance the decision-making and predictive capabilities of AI systems.

AI in Economics and Machine Learning

In this course, you will explore the synergy between econometrics and machine learning. Learn how to apply machine learning techniques to economic data to solve complex problems. Topics include predictive modeling, time-series forecasting, and economic modeling using AI methods. This elective is ideal for those interested in data-driven decision-making in economics or policy research.

AI for Business Applications

This elective gives you the option to focus on AI’s applications in various business functions, such as marketing, finance, and operations. You will learn how to leverage AI for predictive analytics, customer segmentation, fraud detection, and financial forecasting. This course will help you use AI to drive business strategies and optimize operational performance.

Additional Electives in AI

In addition to the core and specialized electives, you can choose additional courses covering a broad range of AI topics. Options include deep learning for computer vision, reinforcement learning for autonomous systems, and natural language processing for business applications. These electives give you the freedom to explore specific AI subfields aligned with your career goals, whether in healthcare, robotics, finance, or other industries.

By selecting electives that suit your professional aspirations, you can create a personalized AI learning path that aligns with your research interests and career trajectory.

 
 
 
 
 

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Master the top in-demand data and business analytics tools that companies are looking for.

Get The MRes Artificial Intelligence Advantage

On-Campus Experience

Engage with world-class faculty and a diverse peer group at the university campus, immersing yourself in an interactive and innovative environment. Experience cutting-edge research and real-world AI applications while networking with students and experts globally.

AI Mentor Network

Gain exclusive access to the online directory of MRes Artificial Intelligence alumni. Utilize features like job boards, mentorship opportunities, and peer networking to enhance your professional journey.

AI Mentorship Society

Join a transformative mentorship program designed to foster professional relationships. Get personalized guidance from experienced mentors in the AI industry to navigate your career path and gain valuable insights.

Graduate Center

A dedicated resource center for graduate students, offering tailored support to enhance both your academic and professional success. Take advantage of workshops, career services, and networking events.

Career Lab

Personalized career support to guide you in refining your resume, writing compelling cover letters, optimizing LinkedIn profiles, and preparing for interviews, ensuring you stand out in the competitive AI job market.

Handshake

Gain exclusive access to the official job board and interview system, providing you with hiring opportunities, career preparation resources, and a thriving AI community.

Get the Great Learning Advantage

Sessions with industry experts

Great Learning organizes interactive sessions with industry leaders, offering students the opportunity to gain practical, real-world knowledge of artificial intelligence trends and applications.

Application assistance

Our team will guide you through every step of the application process, offering personalized support in filling out your application form and submitting the necessary documents.

Statement of purpose review

We offer students expert guidance on crafting a compelling Statement of Purpose (SOP), ensuring it effectively highlights their aspirations and suitability for the program.

Visa Assistance and Process

Our team provides detailed assistance in obtaining the necessary documents for securing an I-20, as well as help in scheduling Visa appointments and preparing for interviews to ensure a smooth visa process.

Program Fee

Program Fees:

Mode: Full-time Distance Learning
Fee: £9000 per year
Year: 2025-26

Apply Now

Application process

Our admissions close once the requisite number of students is enrolled in the upcoming cohort. Apply early to secure your place.

1. Apply Online

Fill out the online application form. No additional tests or prerequisites required.

2. Pre-Screening

Our program team will contact you to confirm your eligibility.

3. Application Assessment

If selected, you will be offered a seat in the upcoming cohort. Pay the fee to secure your seat

4. Join the program

Once accepted, you will receive an official offer letter with instructions on how to pay and join the program. Limited Seats Availa

Limited seats available

Apply today and become a Analytics Expert

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Frequently asked questions

The Master of Science in Business Analytics program at the University of Arizona offers both online and in-person learning options. Students can choose to pursue the program through flexible online classes or attend in-person sessions on campus, depending on their preferences and location.

Yes, upon completion of the Master of Science in Business Analytics program, you will gain Alumni status from the prestigious Eller College of Management at the University of Arizona. This will provide you access to the college’s alumni network, which includes valuable resources, job boards, and mentorship opportunities.

Yes, the MS in Business Analytics at the University of Arizona is considered a study abroad course if you are enrolling from outside the USA. Students from various countries can join this program and experience studying in the U.S. with opportunities for networking, hands-on experience, and career advancement in a global setting.

After completing an MS in Business Analytics, you will have access to various job opportunities in the U.S., particularly in sectors such as technology, finance, healthcare, consulting, and e-commerce. Companies highly value data-driven professionals with strong analytical skills, and you can find roles such as Data Analyst, Business Intelligence Analyst, Data Scientist, or Business Consultant. With the STEM OPT extension, you can stay and work in the U.S. for up to 36 months after graduation.

Yes, pursuing a Master of Science in Business Analytics can be highly beneficial. The home to numerous leading tech companies, startups, and industries that highly value advanced skills in data analytics. Graduating from a U.S. institution like the University of Arizona offers not only quality education but also exposure to a global job market. The hands-on experience, networking opportunities, and potential for high-paying roles make it a worthwhile investment for your career.

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Application Closes: August 15

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