The MS in Information Science: Machine Learning is a 21-month online program offered by the University of Arizona in collaboration with Great Learning with the aim to empower one to leverage the opportunities created by the information age and the advent of machine learning. From the foundations of information management to complex applications of it with machine learning, the program provides a holistic overview of the data ecosystem.

Through this program, students will receive career mentoring support from Great Learning, which includes creating an e-portfolio, resume review, interview preparation sessions, access to an exclusive job board, and career guidance. This career support platform assists students in paving the way for a successful career path in Information Science and Machine Learning.

The online mode of learning will furthermore let the students continue working while upgrading their skills and save up on accommodation costs. Post completion of the program, they will receive a MS in Information Science from University of Arizona and join the global alumni network of the University of Arizona that gives them access to extensive career and alumni support to advance in their careers.

Both live sessions and pre-recorded video lectures will be used. Live sessions will also be recorded so that students who can't make it to a session or want to review it afterward can do so by watching the session recording.

The typical duration of a live session would be 2.5 to 3 hours in a month.

There will be at least four live sessions in every course, while the exact number of sessions will depend on each faculty member.

WES accreditation is only required for courses from universities outside of the US to prove that they are equivalent to one by an accredited US university.

For example, WES may look at a course by an Indian engineering college that assigns points out of 100 and then converts it to an equivalent score for a similar course in the US out of a 4.0 GPA scale. 

As the Master’s in Information Science: Machine Learning Program is from the University of Arizona, a US-accredited university, there is no question of having WES review and recognize the course for credits.

Each faculty member will determine the grading system of their respective subjects and share the evaluation criteria with you at the beginning of each course.

While attendance to the live sessions is strongly encouraged it is not mandatory. You can view the session recording on the LMS (Learning Management System) at a later time of your convenience.

Flexibility
Taught in a blended format with live online classes and recorded lectures, the program features hands-on projects and mentorship sessions to enhance the learning experience and is structured to suit the schedules of working professionals.

Committed Student Support
Learners are facilitated with constant support from several industry experts that assist them in every stage of their learning journey.

Career Assistance
Great Learning offers excellent placement prospects when learners successfully complete this course. Comprehensive career assistance is offered to every learner to help them land the jobs they desire.

Learn the most in-demand tools
Upon taking up this program, learners gain an understanding of the most in-demand tools such as Python, TensorFlow and more.

The UArizona Advantage
Through this MS in Information Science: Machine Learning program, you can join the global alumni network of the University of Arizona and access the extensive career and alumni support they offer to advance your career

There are a lot of amazing benefits this course has got to offer you.Here are a few of them

• World-Class Faculty
  Upon taking up the Masters Program, you would learn from the world-renowned faculty of University of Arizona through Live Interactive Sessions. 
   
• Hands-on Learning
  Learners work on several hands-on projects and case studies to apply machine learning techniques to solve real-world business problems and a capstone project that incorporates all the tools and techniques learned throughout the course.
   
• Comprehensive Curriculum
  The curriculum is designed by leading experts at the University of Arizona and practicing industry professionals. It is specifically curated to cover a range of information science skills - starting from the fundamentals and progressing to more complex, hands-on applications. Learners master several in-demand tools such as MS Azure TensorFlow, HuggingFace and more.
   
• Masters Degree from University of Arizona
  Upon the successful completion of MS in Information Science: Machine Learning program, you would receive a Master’s Degree from The University of Arizona that adds value to your resumes.

The curriculum is designed by leading experts at the University of Arizona and practicing industry professionals. It is specifically curated to cover a range of Artificial intelligence and machine learning skills - starting from the fundamentals and progressing to more complex, hands-on applications. Throughout this course, you would learn about several concepts like Data Mining and Discovery, Data Visualization, Data Warehousing and Analytics in the Cloud, Advanced Natural language processing, Neural Networks & more.

You would work on several hands-on projects and case studies to apply machine learning techniques to solve real-world business problems and a capstone project that incorporates all the tools and techniques learned throughout the course.

After completing this master's in machine learning program, you will be able to:

• Review and report on information generation and processing to comprehend data from a larger perspective.
• Assess and enhance information management systems to discover best practices, gaps, and areas for improvement.
• Utilize machine learning approaches to address current business challenges.
• Work on the entire information management pipeline.
• Deploy the latest techniques to get valuable insights for growth to become the ideal ML leader.

21 months, 5 semesters of 4 to 4.5 months each.

This program follows a cohort-based approach. So, students are required to finish these courses in a specified order and time period.

This program is a master’s degree and will be rigorous in nature. While the time needed will vary depending on prior knowledge, you should plan to spend around 8-10 hours every week.

Knowledge of a programming language is not a prerequisite for this Master's Degree in Machine Learning and Information Science. GL provides extensive pre-course materials as well as in-course support to help bridge the gap.

Yes, as this program is offered online, students from any part of the world (except the United States and China)can take up the MS in Information Science: Machine Learning.

While in terms of curriculum design, degree and transcripts, and access to university resources, this online degree is the same as an on-campus program, the key difference comes in how the curriculum is delivered. Classroom based learning relies on more in-person interactions where students attend lectures in a classroom, interact with faculty over office hours, have study sessions with TAs etc. In an online program all this interaction shifts so that it happens over the internet. Thus an online program offers more convenience, flexibility and safety (by providing social distancing) compared to a classroom program.

The online degree programs are much more affordable compared to an on-campus program and the student also saves on housing in the US and opportunity cost of not working for two years.

There are no predefined set of questions that an applicant needs to answer. The SOP is more of a means for the admissions staff to learn more about an applicant's background. Some of the topics a candidate could address to accomplish this include:

• What inspired you to apply for this MS in IS: Machine Learning Program?
• How can this master’s degree help you reach your professional objectives?
• What strengths do you have that will help you make the most of this master’s degree to further your career?

No, since this is a fully online course, enrolment will not entitle students to a U.S. student visa.

A clean and complete application with all the necessary documents will be reviewed and reverted to in two weeks.

Applicants are required to submit their bachelor’s degree certificate, academic transcripts, resume, Statement of Purpose and a Letter of Recommendation.

Although there is no unique benefit to applying early, the sooner you apply, the sooner you will receive a response. We suggest candidates submit the application form as early as possible to avoid missing the deadline or having to scramble at the last minute. Some phases in the application process will take time, and the admissions team will carefully review each application.

Since there is a limited number of seats for every cohort, candidates applying in time are more likely to get into a cohort of their choice. Some early applications also get shortlisted for scholarships. Please check with your Program Advisor for more details.

Learners can get in touch with their Program Advisors on guidance on how to go about completing their application. They can also directly go ahead and apply here.

While this master’s degree program is intended for working professionals, any student who fulfills the prerequisites can enroll in this program.

Students must have completed a 4 year U.S. bachelor’s degree or equivalent.

A bachelor’s degree along with Master’s, 1st year of Master’s or 1 year Diploma. If the 3 year bachelor’s is equivalent to 120 credits or the transcript of the same states it is equivalent to 4 years then it is acceptable.

Although it will be helpful, having a background in mathematics and statistics is not a requirement. Potential candidates are urged to brush up on their mathematical skills if they haven't used them recently because this program's particular disciplines will all have significant quantitative components.

The students also have access to Program Support by Great Learning in case of any issues faced during the program. With a dedicated program manager to solve all queries, mentorship from Industry Experts & peer interaction to build a network, the students get the right guidance and structure needed to successfully complete the program.

No, if the medium of instruction for your bachelor degree was English. If the medium of instruction for the bachelor’s degree was not English then you would need to give an English language proficiency test like IELTS or TOEFL.

No. GRE or GMAT scores are not required to qualify for this master’s degree.

Students who earned their bachelor's degree outside of the US: You may apply for this program if your transcript review indicates that your degree is equal to a four-year U.S. bachelor's degree.

Students who earned their bachelor's degree in the US: You may apply if you have a 4-year bachelor's degree.

The tuition fee for this MS degree is USD 10,500.

Through this MS in Information Science: Machine Learning program, you can join the global alumni network of the University of Arizona and access the extensive career and alumni support they offer to advance your career.

• Bear Down Network - Directory of The University of Arizona Alumni with features such as Job Board, Mentorship Opportunities and much more.

• Wildcat Mentor Society - The Transformative Program to build strong professional networks and get guidance from seasoned mentors.

• Graduate Center - Resource for graduate and postdoctoral learners to enhance their academic and professional success.

• Lifelab - Platform to help learners with Resume-building, Cover letters, LinkedIn Profiles and much more.

• Handshake - The University of Arizona's official job board and campus interview system for hiring opportunities, career preparation resources and peer networks.

Furthermore, students have access to university ID, free software licenses, offline resources and multiple workshops. For career development, they can also submit their documentation (CVs, Resumes etc.) for review online and get feedback from the counselor within 24-48 hrs.

No, the degree will not mention the mode of learning. The degree certificate and the transcripts will be the same as the ones offered for the on-campus program.