Micro-Master in Artificial Intelligence

  • Total # of Credit hours
    12

Program Overview

Overview

Micro-Master in Artificial Intelligence program offered by Ajman University is the first of its kind in the country. We will be one of the leading Universities in the region to offer Micro-Master in Artificial Intelligence. Artificial Intelligence (AI) is the newest trend in computer science nowadays. Although (AI) is not new as science, it is recently attracting the attention of business leaders, industry, military, and governments from all over the world. The component of mimicking the human ability that AI has, such as; inference, deduction, knowledge aggregation, learning, recognition and even expressing emotions make AI based technology of great interest. It is extremely important nowadays for our community and organizations to be at the leading edge of technologies such as AI. This will empower all organizations of the nation, and make them at the top niche of advancement and development.

Program Mission

The mission of the Micro-Master in Artificial Intelligence is to prepare graduates with well-rounded education in the different areas of Artificial intelligence (AI). The graduates will be able to develop AI technologies and fulfill the local and regional market’s needs. The program will motivate scientific research in this field in collaboration with internal and external entities.

The Education Objectives

The Education Objectives of the Micro-Master in Artificial Intelligence program are to graduate students who will be able to:

  1. Provide innovative solutions to complex problems.
  2. Become an effective team member.
  3. Acquire a position of leadership/responsibility in an organization.
  4. Demonstrate ethical and social behavior.
  5. Pursue further studies and become life-long learner”
Program Coordinator

Prof. Mohammed Al Betar (Profile)

Admission Requirements
  • The applicant should have a Bachelor degree (or equivalent qualification) in Computer Science or a directly related discipline from an accredited university recognized by the UAE Ministry of Education.
  • The department will consider applications from holders of a Bachelor degree with a minimum GPA of 3.0 on a 4.0 scale or equivalent score.
  • English Proficiency Tests – must be taken no more than two years prior to admission to Ajman University. A minimum English proficiency scores are set for the Micro-Master in Artificial Intelligence program as follows: A minimum TOEFL score of 550 on the Paper-Based, 213 on the Computer-Based, or 79-80 on the Internet-Based test, or its equivalent in a standardized English language test, such as 6.0 IELTS or another standardized, internationally recognized test approved by the CAA.
Exceptions
  • An applicant who is a native speaker of English and has completed his/her undergraduate education in an English medium institution in a country where English is the official language.
  • An applicant with an undergraduate qualification from an English-medium institution who can provide evidence of acquiring a minimum TOEFL score of 500 on the Paper-Based test, or its equivalent on another standardized test approved by the Commission, at the time of admission to his/her undergraduate program.

Meeting the above conditions does not guarantee automatic admission into the program. Authority for admitting an applicant for the Micro-Master in Artificial Intelligence program is vested in the Dean of the College of Engineering and Information Technology and the Dean of the Graduate Studies and Research. By written communication, both Deans will transmit the decision to the applicant, and the registrar.

Transfer Admission
  • Transferred students will be accepted under the following conditions:
  • Student transferring from a federal or licensed institution in the UAE, or a foreign institution of higher learning based outside the UAE and accredited in its home country, are eligible for transfer admission.
  • Student is required to meet the English language proficiency requirements for the Micro-Master in AI program, prior to commencing their study.
  • Only students in good academic standing (a minimum cumulative grade point average of a 3.0 on a 4.0 scale, or equivalent) will be accepted to the Micro-Master in AI program;
  • A maximum of 12 credit hours of a degree program may be gained through transfer, and thesis transfer is not allowed.
  • Degree requirements may be satisfied by transfer of graduate credit for courses of a grade of B or above from an accredited college or university and completed outside the master’s degree. Courses normally taken in an undergraduate program will not be counted as credit toward the Micro-Master in Artificial Intelligence degree. No credit hours can be used to satisfy more than one degree.
  • Generally, graduate transfer credit that is more than five years old may not be accepted to complete a degree.

The Program Coordinator recommends transfer of credits to the Dean who will forward it to the Registrar who makes appropriate changes to the student transcript. A student enrolled at Ajman University who wishes to take courses at another institution with the intention of transferring them to AU must have the prior written permission of the Program Coordinator and the Dean before registering for such courses. Details about the required documents for admission are available in Graduate Student Catalog.

Graduation Requirements

The completion requirements of the Micro-Master’s degree in Artificial Intelligence shall be:

  • An overall cumulative grade point average (CGPA) of 3.0 or above (out of 4.0) after the completion of the 30 credit hours as per the degree requirement and the study plan.
  • A minimum grade of C is required to pass any course.

 

Career Opportunities

Graduates of the Micro-Master in AI program will have careers in various areas and fields local, regional, and international as follows:

  1. Pursuing Ph.D. degree in AI related areas.
  2. R&D at specialized firms developing AI algorithms and applications.
  3. Data analytics and scientists at firms and organizations; private and public.
  4. Robotics engineers and developers.
  5. Decision makers and all levels managers who need to use and develop AI based systems.
  6. Games developers and programmers.
  7. Security specialists and analyzers.
  8. Smart governments and smart e-commerce specialists.
  9. Medical imaging and pattern recognition engineers.
  10. Smart education and e-learning specialists.
  11. Speech recognition and natural language processing specialists.

 

Program Learning Outcomes

On successful completion of this program the graduate will be able to:

PLO#1: Demonstrate an in depth understanding of the theories and techniques of AI.

PLO#2: Review and contrast new research findings and developments in the AI field.

PLO#3: Integrate diverse AI technologies to formulate innovative solutions to complex problems.

PLO#4: Analyze and evaluate critically AI-based solutions to highly complex problems.

PLO#5: Manage and take responsibility for conducting AI-based research/project development.

PLO#6: Function independently and collectively as a member of a team and assume leadership roles.

PLO#7: Resolve highly complex ethical and societal issues arising from implementing AI-based solutions.

Courses Descriptions

Artificial Intelligence – MAI602

Credit hours: 3  Theory: 3  Lab: 0  Prerequisite: None

The aim of this course is to provide graduate students with in-depth knowledge of AI principles, algorithms and techniques. Topics covered include Knowledge Representation schemes and Automated Reasoning, uncertain knowledge and probabilistic reasoning, search strategies, intelligent agents, machine learning, planning, and ethical and societal issues relating to artificial intelligence.  Students also work on a course project individually or in pairs.

 

 

Data Mining – MAI601

Credit hour: 3  Theory: 3  Lab: 0  Prerequisite: None

Data mining is the process of discovering patterns and knowledge from huge amount of dataset. This course aims to equip students with the necessary skills and knowledge that allow them to develop models using data mining techniques that include association, clustering, outlier, web mining, text mining, and pattern mining approaches.  Students will also learn to collate, filter, clean, transform, and sort data using established contemporary tools. Validation and performance assessment is applied to compare test data with training data and assess accuracy of processes and models. 

 

Machine Learning – MAI603

Credit hour: 3  Theory: 3  Lab: 0  Prerequisite: None

This course aims to provide students with an in-depth introduction to the main areas of machine learning. Topics covered include, supervised and unsupervised learning models and algorithms in classification, regression, and clustering, reinforcement learning algorithms and models, genetic algorithms in machine learning, and model selection and evaluation. Students also work in group projects (2 to 3 students) that embodies the solution to a machine learning problem. 

 

Robotics – MAI605

Credit hour: 3  Theory: 3  Lab: 0  Prerequisite: None

Methods of analysis for operations of robotics are presented. The manipulators dynamics and kinematics including trajectory planning along with motion control, vision, and sensing are covered. Programming to control robots using hardware interfaces (microcontrollers) for motion and motion planning along with task assembling. Optimum trajectory and optimum grippers are presented. Uncertainty and stability issues in grasping and planning. Applications of robots in several areas of real life. Hybrid AI and robotics techniques.  Lab work will provide hands on experience.