Here's a comprehensive list of key highlights of MS in Machine Learning program:

• 3-Year Post-Study Work/STEM OPT Visa: Eligibility to work in the USA for up to 3 years after graduation.

• Simplified Application Process: No GRE, TOEFL, or other additional tests or prerequisites are required for admission.

• Substantial Cost Savings: Potential to save over INR 55 lakhs compared to similar programs.

• Alumni Status from the University of Arizona: Graduates become part of the esteemed alumni network of the University of Arizona.

• Hybrid Learning Model: Combines online education in the first year with on-campus learning in the second year.

• Interactive Sessions with Faculty: Live, interactive learning experiences with the University of Arizona faculty.

• Industry Expert Insights: Practical insights from industry experts, enhancing the real-world applicability of skills learned.

• Hands-On Projects and Case Studies: Involvement in 11 hands-on projects and case studies for experiential learning.

• Capstone Project: Opportunity to work on a comprehensive capstone project, integrating and applying learned skills during this Master's program.

• In-Person Faculty Interaction: Direct learning from University of Arizona faculty during the on-campus phase.

This machine learning program follows a hybrid structure:
 

1st year: Online

2nd Year: On-campus at the University of Arizona in Tucson, Arizona. 

This structure allows for a flexible learning approach in the first year, followed by immersive on-campus experiences.

Yes, students can take up to a one-year break by applying for 'Leave of Absence,' with the university typically approving such requests. Visa applications must align with the break period.

There are two intakes each year, in Spring (January) and Fall (August), with on-campus attendance following the subsequent Spring or Fall semester.

WES accreditation is not applicable, as the program is offered by the University of Arizona, an accredited US university.

This is a master's degree program that will be rigorous. Although the time needed will vary depending on prior knowledge, students should set aside 15 to 18 hours per week.

Retake of the examination with the subsequent cohort will be an option for the student.

They will, however, be put on probation for a semester if their GPA does not remain at 3.0. You can access the complete policy on graduate probation on this page.

Attendance at live sessions is encouraged but not mandatory. If you miss a session, it's recorded and made available on the Learning Management System (LMS), allowing you to access and review it at your convenience.

In the second year of the Hybrid program, students at the University of Arizona can look forward to:

• Vibrant Campus Environment: Tucson is sunny for over 300 days a year, making it ideal for outdoor activities.

• On-Campus Living: The campus offers 23 dorms and numerous fraternity and sorority houses.

• International Student Support: Dedicated services provide immigration guidance, academic resources, and cultural and social event coordination.

• Wide Range of Student Clubs: Over 600 student clubs and organizations cater to diverse interests, from hobbies to professional development.

• Access to Modern Facilities: State-of-the-art facilities across technology, arts, and sciences are available for in-depth learning.

• Top-Ranked Campus Recreation: The Campus REC offers fitness and wellness activities, ranking among the top 10 recreation centers by Best Value Schools.

• 24/7 Technical Support: Continuous technical assistance ensures a smooth campus experience.

The program boasts a diverse team of experts, including professors and assistant professors from the School of Information, specializing in various aspects of Information Science and Machine Learning. They bring a wealth of research and practical experience, enriching the program's academic rigour and industry relevance.

The key highlights of the program curriculum for the MS in Information Science: Machine Learning include:

• Foundations of Information: Introduces foundational ML and AI concepts, focusing on data types, collection, usability, and storage.

• Data Mining and Discovery: Equips with methods for data discovery and understanding, covering data mining and analysis techniques.

• Data Analysis and Visualization: Focuses on visualizing data effectively for dashboards and statistical patterns using various visualization theories.

• Introduction to Machine Learning: Comprehensive overview of machine learning algorithms, including both linear and non-linear models.

• Data Warehousing and Analytics in the Cloud: Delves into relational databases and cloud analytics, emphasizing SQL, data modelling, and Azure.

• Data Ethics: Addresses the ethical implications of AI, covering ethical conduct in data science and issues like algorithmic bias.

• Neural Networks: Introduces neural network concepts and training for handling data types like text, images, and video.

• Applied Natural Language Processing: Explores modern NLP techniques using neural networks, focusing on text representation and classification.

• Advanced Machine Learning/AI Applications: Covers advanced machine learning and AI applications, including a deep understanding of computer vision and generative AI modeling.

• Capstone Projects: Allows hands-on experience with projects aligned to university research priorities, like climate change analysis and public health data interpretation.

This curriculum is designed to provide a holistic and interdisciplinary approach, equipping students with the necessary skills and knowledge for a career in information science and machine learning. For more details on the curriculum, click here.

Upon completing the program, you'll be skilled in: 

• Data Interpretation: Gain expertise in reviewing and interpreting data within a broader context.

• Information Management System Assessment: Learn to assess and enhance information management systems, identifying best practices and areas for improvement.

• Machine Learning Application: Acquire skills to apply machine learning techniques in solving real-world business challenges.

• Information Management Skills: Develop proficiency across the entire information management pipeline, from data mining to modeling.

• Innovation and Insights: Become equipped to innovate in information science and extract actionable insights for organizational growth.

Participants will engage in 11 hands-on projects and case studies, along with a capstone project. These practical experiences are designed to apply learning in real-world contexts, enhancing both technical skills in machine learning and broader information science competencies.

This Machine Learning program is a hybrid program that includes both online and on-campus classes. Obtaining this Machine Learning Masters Degree is an excellent choice for several reasons:

• Academic Excellence: The USA has prestigious universities with top-notch research facilities, innovative teaching, and many courses.

• Career Prospects: The USA's job market is expansive, particularly in tech, engineering, and finance, offering excellent opportunities for graduates locally and globally.

• Networking Opportunities: A Master's degree from a US university provides access to an extensive network of alumni, academics, and industry professionals, aiding career development.

• Cultural Enrichment: For international students, studying in the USA offers a unique cultural experience, fostering personal growth and a broader understanding of diverse perspectives.

The hybrid model allows students to start the program online in the first year, providing flexibility and accessibility. In the second year, students transition to on-campus learning at the University of Arizona. It offers an immersive educational experience and the opportunity to interact with faculty and peers in person.

A hybrid learning format combines online and in-person education, offering several key advantages:

• Cost-Efficiency: It is often more budget-friendly than full-time programs, saving expenses like housing and transportation.

• Flexible Scheduling: Offers the convenience of choosing when and where to study, ideal for balancing work, life, and education.

• Employment While Studying: Enables full-time work during the first online year, allowing practical application of learning and financial stability.

• Personalized Learning: Tailors to different learning styles with a mix of online and in-person resources.

• Enhanced Collaboration: Promotes networking and collaboration among diverse students through online and in-person activities.

• Global Community Access: Connects students with an international network, broadening their global perspective.

• Eligibility for OPT: Qualifies students for a 3-year OPT in the USA, offering career opportunities post-study.

• Practical Skill Application: Encourages immediate application of skills in professional settings, enhancing career growth.

• Access to Comprehensive Resources: Provides access to the University of Arizona and Great Learning's resources for up-to-date Machine Learning and Information Science knowledge.

Students benefit from the expertise and resources of a top-ranked global university and a leading professional learning platform. The collaboration ensures a blend of academic rigour, practical industry insights, cost savings, and a rich network of alumni and professionals. 

Great Learning brings its expertise in professional and industry-oriented education, complementing the academic strengths of the University of Arizona. This synergy ensures a well-rounded education that is both academically sound and industry-relevant.

Classes on the Arizona campus generally consist of around 25 students per faculty member.

Hybrid students can consider any available remote Research Assistant (RA) or Teaching Assistant (TA) positions right from their first year. Additionally, during their last online semester, they can look into on-campus assistantship opportunities, informing the faculty about their expected arrival date on campus.

Graduates can pursue careers in various sectors that value machine learning and information science expertise, including technology companies, research institutions, consulting firms, and more.

Generally, online masters in Machine Learning require programming knowledge, but this MS in Machine Learning program does not require proficiency in programming languages. Great Learning offers comprehensive pre-course resources and in-course assistance to compensate for the knowledge gap.

The university is ranked as a Top 50 Public University and a Top 100 Global University by U.S. News & World Report and is within the top 0.47% of worldwide universities by the Center for World University Rankings.

The MS in Information Science: Machine Learning program is ideal for young, early-career professionals seeking to expand their skills abroad, mid and senior-level professionals aiming to update their information management knowledge, and those looking to transition into a career in information management with industry-relevant skills.

The program caters to anyone with a keen interest in information science and machine learning, regardless of their current professional stage, and who aspires to play a pivotal role in shaping the future of digital information management.

The eligibility criteria for the MS in Information Science and Machine Learning are as follows:

• A 4-year accredited bachelor's degree, OR

• A 3-year accredited bachelor's degree plus a master's degree, OR

• A 3-year accredited bachelor's degree plus a postgraduate diploma, OR

• A 3-year bachelor's degree alone provided it includes at least 120 credits and has been obtained in Division I from an institution accredited by the National Assessment and Accreditation Council (NAAC) with a score of 'A' or higher.

Please note: Graduate applicants from India are not required to submit an English proficiency test (like IELTS/TOEFL) for admission to the Graduate College. However, specific degree programs might have their own English proficiency requirements. Additionally, students from India must demonstrate English proficiency for positions as graduate teaching assistants/associates.

For English proficiency requirements applicable to applicants from other countries, please visit the University of Arizona International Admissions Requirements.

Yes. Generally, master's in artificial intelligence and machine learning programs require GRE and GMAT scores, but to pursue this master's degree in the USA, you are not required to have a GRE or GMAT score.

In India, English proficiency test scores are not required. However, the requirements for applicants from other countries are the same as for online programs. 

For detailed information on English proficiency requirements for various nationalities, please visit the University of Arizona International Admissions Requirements.

Please note: TOEFL scores or equivalent may be necessary for students hired in Graduate Assistant roles, particularly as Teaching Assistants. More information can be found here: English Speaking Proficiency Evaluation for Graduate Assistants.

The program is designed for individuals interested in pursuing an online master's degree in machine learning or an on-campus MS in Machine Learning. It's suitable for early-career professionals, mid and senior-level professionals, and those aiming to transition into information management or machine learning careers.

A general interest and aptitude in machine learning and information science are likely needed.

Yes, the Grad College and International Student Services will help students find accommodation. International Student Services provides referrals to the Office of Residence Life and Off-Campus Housing for help with finding accommodations.

No, evaluation of transcripts is not a prerequisite for program application.

If a student needs help with their application, they can talk to their Program Advisors or send their documents (such as transcripts, an SOP, a degree certificate, and a CV) to msml.hybrid@greatlearning.in via email.

People who want to apply should send in their forms as soon as possible so they can meet the deadline and have to rush at the last minute. There will be steps in the application process that take time, and the admissions team will carefully review each.

Because there are only a certain number of seats for each cohort, applicants who send in their applications early have a better chance of getting into the cohort of their choice. Some early applicants are also chosen to receive scholarships. To find out more, please contact the Program Advisor.

People who want to apply must send in proof of their bachelor's degree, academic transcripts, a resume, a Statement of Purpose (SOP), and a Letter of Recommendation (LOR).

Here's the admission process for the MS in Information Science: Machine Learning program:
 

1. Apply Online: Complete an online application form without any additional tests or prerequisites.

2. Pre-screening: The admissions team contacts you by phone to confirm your eligibility for the program.

3. Application Assessment: Your application is thoroughly assessed, followed by a prompt response from the admissions team.

4. Join the Program: If selected, you'll receive an acceptance letter with payment details and instructions on joining the program.

Note: The program offers a significant cost saving compared to a full-time Master in Information Systems or Master in Machine Learning. Great Learning provides comprehensive support throughout the University of Arizona application process, including assistance with the US visa application for hybrid students.

Online participation is an option for the student. Alternatively, after completing a Leave of Absence, students may reapply for the visa and return in subsequent semesters/years.

I20 applications are accepted immediately following the first semester. However, the student will have to consult with ISS to determine whether the I20 application process can be initiated even sooner, i.e., immediately following receipt of the university's offer letter.

Here's a process that details when you should apply for the VISA of the Hybrid program format:

• The student notifies Great Learning (GL) of their needs.

• GL communicates with the I-School, handling the submission of necessary documents for the student.

• The I-School then informs the International Student Services (ISS).

• ISS issues the I-20 form to the student.

• The student then applies for and obtains a visa from the embassy.

To ensure smooth processing, it's advised that students initiate the I-20 application and visa appointment process approximately 6 months before their planned arrival in the US. The I-20 application, managed through the University of Arizona’s International Student Center, typically takes around 10 business days to process. Once the I-20 is issued, students can schedule a visa appointment at their local consulate.

Yes. Students are eligible for up to 3 years of Post-Study Work/STEM OPT Visa in the United States if they enroll in this program.

A Statement of Purpose (SOP) should include:

• Introduction: A brief personal introduction and career goals.

• Academic Background: Key academic experiences and achievements.

• Professional Experience: Relevant work history, if applicable.

• Program Motivation: Reasons for choosing the specific program and its alignment with your goals.

• Career Objectives: Short-term and long-term career plans.

• University Choice: Why did you select this university and program?

• Personal Strengths: Your skills and qualities make you a good fit for the program.

• Extracurricular Activities: Any relevant activities outside academia.

• Future Contribution: How do you plan to contribute to the field and university community?
   

Conclusion: A strong closing statement emphasizing your enthusiasm and readiness for the program.

The tuition fee for each term is payable on the semester's first day. Students can sign up for a Payment Plan before the semester begins, allowing them to divide their fees into three equal installments. Further details about Payment Plans and specific tuition deadlines are available at Tuition Payment Plan | Bursar (arizona.edu).

Students interested in scholarships can apply at the following link: University of Arizona Scholarships
 

For Research Assistant (RA) or Teaching Assistant (TA) positions, students are encouraged to apply within the iSchool and other departments. The Handshake portal is a useful resource for these applications. Additionally, students can explore opportunities through employment and career services. The International Student Services (ISS) also assists in finding on-campus job opportunities.

Indeed, international students are permitted to work on the University of Arizona campus for a maximum of 20 hours per week. This on-campus employment does not necessitate authorization from International Student Services.

For more information, visit [On-Campus Employment for International Students].

Great Learning provides comprehensive support in the application process and the US visa application for hybrid students. Additionally, there are scholarships and financing options available, for which you can contact a Program Advisor for more information.

The program fees are INR 10,18,635 (including 18% GST) for the first year and USD 23,676 for the second year, saving over INR 55 lakhs compared to traditional full-time US master's programs. 

After completing this program, you can pursue job positions like Information Architect, Data Engineer, Data Analyst, Database administrator, Data Scientist, AI/ML engineer, Digital Artist, Software Engineer, and various leadership roles in different companies.

These are some of the primary recruiters associated with the University of Arizona: Tesla, NASA, Boeing, Enterprise Rent-a-car, GEICO, Altria, American Express, Goldman Sachs, Vanguard, Charles Schwab, and many more- You can check it out here.

Yes. The program supports obtaining a 3-year post-study work/STEM OPT visa in the USA, which is crucial for international students seeking to gain work experience in the United States post-graduation. Check it out here.

Enrolling in this program offers access to the University of Arizona's extensive alumni network, providing several advantages:

• Career Advancement: Join a network with a 92% employment rate and access career fairs for networking opportunities.

• Bear Down Network: Access an exclusive alumni job board, mentorship opportunities, and university news.

• Wildcat Mentor Society: Engage in a program that connects alumni with university thought leaders for mentorship and professional growth.

• Graduate Center Support: Benefit from resources aimed at enhancing academic and professional success, including recruitment to top organizations.

• LifeLab: Utilize personalized career guidance, including help with resume-building and LinkedIn profile optimization.

• Handshake Access: Gain entry to the university’s official job board for hiring opportunities and career resources.