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Study in USA for MPS in Applied Machine Intelligence
Explore Study in USA for MPS in Applied Machine Intelligence with a clear guide to course options, eligibility, study format, fees and the questions to ask before applying.
LevelStudy Abroad ModeOnline Duration1 to 1.5 years
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Course Overview
Study in USA for MPS in Applied Machine IntelligenceCourse Overview
Eligibility10+2 pass or equivalent, with mathematics and English proficiency as required by the university.
The MPS in Applied Machine Intelligence is a career-focused postgraduate program that combines artificial intelligence, data management, analytics, and practical applications. Students learn how intelligent technologies can be used to solve complex problems across industries such as healthcare, finance, business, and human resources.
The Northeastern University program includes AI fundamentals, AI applications, AI system technologies, data governance, responsible AI, and experiential learning. Students may also be able to explore specialized study areas depending on the university's current curriculum.
Program Highlights
- Degree: Master of Professional Studies (MPS) in Applied Machine Intelligence
- Study destination: United States of America
- Academic focus: Artificial intelligence, machine learning, analytics, and intelligent systems
- Learning approach: Technical coursework, applied projects, and experiential learning
- Career direction: AI development, data analytics, intelligent automation, and technology consulting
Take the next step toward an international education that connects AI knowledge with practical business and technology challenges.
Skills
Prepare to work with modern AI technologies while developing the analytical and professional skills employers value.
Core AI and Professional Skills
- Artificial Intelligence: Understand AI concepts, applications, and intelligent systems.
- Machine Learning: Explore how models learn from data and support predictions.
- Data Management: Organize, process, and interpret data for analytical applications.
- Programming and Analytics: Build familiarity with tools and techniques used in data-driven problem-solving.
- Data Visualization: Communicate analytical findings through meaningful visual representations.
- Responsible AI: Understand data governance, ethical considerations, and responsible technology use.
- Critical Thinking: Identify problems, evaluate evidence, and develop practical solutions.
- Communication and Collaboration: Present technical ideas and contribute to multidisciplinary projects.
Who can apply?
Are you ready to turn your interest in technology into advanced professional skills? This program may be worth exploring if you have a background in computing, engineering, mathematics, analytics, or a related field.
Potential Applicants Include:
- Bachelor's degree holders interested in AI and machine learning.
- Computer science, IT, engineering, and mathematics graduates.
- Data analysts and technology professionals looking to advance their expertise.
- Working professionals interested in AI-driven innovation.
- International students seeking postgraduate education in the USA.
Typical Admission Considerations
Applicants may need to provide academic transcripts, evidence of English-language proficiency where required, a resume, and other supporting materials specified by the university.
Eligibility: Eligibility, prerequisite knowledge, minimum academic requirements, and English-language requirements depend on the institution and program. Confirm the current criteria before applying.
Not sure whether your bachelor's degree qualifies? Request an eligibility review before beginning your application.
Job Roles
Turn your AI knowledge into career opportunities across technology, finance, healthcare, and other data-driven industries.
Popular Job Opportunities
| Job Role & Key Responsibilities | Focus Area |
|---|---|
| Machine Learning Engineer Develop, test, and optimize machine learning models used for prediction, classification, and intelligent automation. | Machine Learning |
| AI Engineer Help design and implement AI-powered applications, intelligent workflows, and automated business solutions. | AI Applications |
| Data Scientist Analyze complex datasets, identify patterns, and develop models that support business decisions. | Data Science |
| Data Analyst / Business Intelligence Analyst Transform raw data into reports, dashboards, and actionable insights for organizations. | Analytics & BI |
| NLP Engineer Work on language-based AI applications such as chatbots, text classification, and intelligent search. | Language AI |
| Computer Vision Engineer Build AI applications that analyze images and videos for areas such as quality inspection, retail, and healthcare. | Computer Vision |
| AI Solutions Consultant Help organizations identify business challenges and implement suitable AI-driven solutions. | Consulting |
7 roles listed. Job roles are illustrative and depend on experience, skills and employer requirements.
Career note: Career outcomes depend on prior education, technical proficiency, practical experience, and employer requirements. The degree does not guarantee a particular job or salary.
Syllabus/Curriculum
The curriculum is designed to develop a foundation in AI and analytics before progressing toward practical applications and specialized industry projects. The exact subjects and credit requirements depend on the university, campus, and applicable academic catalog. The Northeastern University MPS Applied Machine Intelligence catalog includes the following core subjects and experiential learning requirements.
| Subject / Course | What You Learn |
|---|---|
| Fundamentals of Artificial Intelligence | Core AI concepts, methods, and applications |
| Applications of Artificial Intelligence | Applying AI techniques to practical problems |
| AI System Technologies | Technologies and systems used to support AI applications |
| Data Management and Big Data | Organizing, managing, and analyzing large datasets |
| Data Governance and Responsible AI | Data stewardship, ethical AI, and responsible technology use |
| Python and Analytics Systems Technology | Programming and analytical tools, where selected |
| Advanced Analytical Utilization | Applying analytical methods to complex problems |
| Integrated Experiential Learning | Applying knowledge through practical projects |
| Integrated Experiential Capstone | Bringing together skills to address a real-world challenge |
Potential Areas of Specialization
- AI for Business Ventures
- AI for Finance
- AI for Healthcare
- AI for Human Resources
Note: The availability of these concentrations and course titles may vary with curriculum updates.
Why choose it ?
Learn skills relevant to the evolving AI landscape. Build knowledge that connects intelligent technologies with practical organizational needs.
- Industry-Relevant Learning: Explore how AI can be applied to real business and technology challenges.
- Practical Experience: Develop your understanding through applied coursework and experiential projects.
- Multidisciplinary Exposure: Connect AI with business, finance, healthcare, and workforce applications.
- Analytical Thinking: Learn to interpret data and use evidence to support decisions.
- Specialization Opportunities: Explore a focus area aligned with your professional interests, subject to availability.
- International Education: Experience the academic and professional environment of the United States.
- Career Development: Build a foundation for pursuing opportunities in AI, analytics, and intelligent technology.
Northeastern's published program materials emphasize experiential learning, practical AI applications, and industry-focused problem-solving.
Learning Module
The learning experience combines conceptual understanding with applied work so students can progress from learning AI fundamentals to exploring practical use cases.
Learning Phases
- Module 1: AI Foundations Understand artificial intelligence concepts, terminology, and applications.
- Module 2: Data and Analytics Explore data management, data preparation, analytical methods, and visualization.
- Module 3: AI Systems and Applications Study how AI technologies can be applied to solve industry-specific problems.
- Module 4: Responsible AI Learn about data governance, ethical considerations, and responsible use of intelligent systems.
- Module 5: Experiential Project and Capstone Apply your learning to a structured project or practical challenge.
Note: These modules summarize the program's learning themes; they are not a substitute for the official course sequence.
Examination Pattern
The examination and assessment pattern depends on the university's academic rules and course requirements. A professional program in applied AI may assess students through a combination of:
| Assessment Component | Format |
|---|---|
| Assignments | Analytical exercises |
| Coursework | Programming or data-focused coursework |
| Projects | Individual and group projects |
| Case studies | Practical applications |
| Presentations | Presentations and technical reports |
| Experiential learning | Applied learning activities |
| Capstone | A capstone project or final applied assessment |
Important: Students should confirm the current assessment format, grading scale, minimum passing requirements, attendance rules, and resit policy directly with the university.
Approvals
When choosing a US university, students should verify the institution's recognition and accreditation status before paying application or tuition fees. The US Department of Education does not directly accredit universities; accreditation is carried out by independent accrediting agencies.
For a Program Offered by Northeastern University, Students Should:
- Confirm that the university and the relevant campus or delivery location are officially recognized.
- Check institutional accreditation using the US Department of Education's accreditation resources.
- Review the official university catalog for the exact degree title and curriculum.
- Confirm that the selected program and study format are available to international students.
- Ask the university's international student office about I-20 eligibility and F-1 visa requirements if studying on campus.
Important for Indian students: UGC recognition rules for Indian universities are not the same as the US accreditation system. If you plan to use a foreign qualification in India, check the relevant requirements for your intended purpose.
Fee Structure
The total cost of studying in the USA depends on tuition, credit requirements, the selected study format, living expenses, insurance, and other university or immigration-related costs.
For planning purposes, the university's published 2026–2027 tuition schedule lists MPS Applied AI at US$1,653 per semester credit hour. This is a published rate, not a guaranteed all-inclusive program price. The exact degree title, curriculum, credit total, and applicable fees must be confirmed for the student's intake.
| Expense Category | What to Consider |
|---|---|
| Tuition fees | Based on the program's required credits and applicable rate |
| Application fee | Check the university's current application charges |
| University fees | Technology, student services, and other applicable charges |
| Living expenses | Housing, food, transport, and personal costs |
| Health insurance | Requirements for international students |
| Visa and travel | Visa-related costs, flights, and initial settlement |
Get a Personalized Fee Estimate
Ask for the current tuition schedule, eligible scholarships, payment deadlines, and an estimate of living expenses before making your decision.
Fee note: Confirm the total fee and any scholarship or discount for your intake directly with the university before paying.
Placement Assistance
Prepare for your career with a structured approach to employability and professional development. Depending on the university and the program's available services, career support may include:
Resume and CV Preparation
Resume and CV preparation for AI and analytics roles.
Interview Preparation
Interview preparation and career coaching.
Professional Networking
Professional networking opportunities.
Project Presentation
Guidance on presenting projects and technical skills.
Career Workshops
Career workshops and employer events.
Job Search Advice
Advice on identifying relevant job opportunities.
Career sectors: Support may also include communicating AI concepts to technical and non-technical audiences. Potential employment sectors include technology, financial services, healthcare, consulting, retail, and other industries using AI and analytics.
Important: Placement assistance is not the same as a job guarantee. Before enrolling, confirm which career services are included and whether access to internships, co-ops, or employer projects is guaranteed, optional, or subject to selection.
Admission Process
Follow these steps to begin your application for the MPS in Applied Machine Intelligence.
- Explore the program Review the university, course structure, delivery format, fees, and available intake dates.
- Check your eligibility Confirm academic prerequisites, English-language requirements, and any additional criteria.
- Prepare your application Gather transcripts, degree certificates, a resume, a statement of purpose, and any other required documents.
- Submit the application Complete the official university application and pay any applicable application fee.
- Complete any additional requirements Respond to requests for documents, English-language scores, or other evidence.
- Receive and review the admission decision Check the offer conditions, deposit requirements, and deadlines.
- Prepare for your studies If attending in person, follow the university's instructions for I-20 documentation, visa application, travel, and arrival.
Please note: Northeastern University's general master's admissions guidance lists an online application, statement of purpose, undergraduate transcripts, and English-language proficiency evidence where applicable; additional requirements may apply to individual programs.
Required Documents
Prepare the following documents as a starting checklist. The exact list may vary by applicant and intake.
| Document | When Required |
|---|---|
| Valid passport | For all applicants |
| Bachelor's degree certificate or provisional certificate | For all applicants |
| Official academic transcripts and mark sheets | For all applicants |
| Resume or CV | For all applicants |
| Statement of purpose | For all applicants |
| English-language test results | If required |
| Letters of recommendation | If required |
| Financial documents for visa processing | Where applicable |
| Additional documents requested by the university | If requested |
Document tip: Make sure your name, dates, and academic details are consistent across your documents. Submit certified translations if required for records that are not in English.
STUDENT GUIDELINES
UGC Refund Policy
Understand the university's refund rules before paying. Because this program is offered by a US institution, the UGC refund policy for Indian universities does not automatically govern the university's tuition payments.
1. Before You Pay, Check
| Application fee | Whether the application fee is refundable. |
|---|---|
| Tuition deposit | Whether a tuition deposit can be refunded. |
| Withdrawal deadlines | The withdrawal deadlines and any applicable deductions. |
| After classes begin | How refunds are calculated after classes begin. |
| Refund request | The process for submitting a withdrawal or refund request. |
| Visa refusal or deferral | Any special conditions related to visa refusal or deferral. |
Before paying any deposit or tuition, request the university's written refund and withdrawal policy.
Official document: View UGC Refund Policy (PDF)
Official document: View UGC Refund Policy (PDF)
2. Enrolling Through an Education Partner
If you are enrolling through an Indian education partner, request a separate written explanation of the partner's fees and cancellation terms. Do not assume that a partner's refund policy is the same as the university's policy.
Important: Students should confirm the applicable refund rules using official sources. Visit the UGC Official Website for official notices and information.
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Look for a clear module list, learning outcomes, hands-on assignments and a sensible progression from foundational to advanced topics. For Study in USA for MPS in Applied Machine Intelligence, confirm that the syllabus is current and covers the areas you specifically want to learn.
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Study in USA for MPS in Applied Machine Intelligence may suit learners whose goals and previous experience align with the subject. Review the expected workload and prerequisites first; the best fit depends on your background, available time and what you want to do next.
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Entry criteria depend on the provider and course level. Check accepted qualifications, minimum marks, subject prerequisites, work experience and any language or entrance-test requirements in the latest official admission information for Study in USA for MPS in Applied Machine Intelligence.
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Assessment may include exams, projects, assignments, practical exercises or a final evaluation, depending on the provider. Ask how Study in USA for MPS in Applied Machine Intelligence is assessed, whether attendance is compulsory and what conditions apply to completion or certification.
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