Master of Professional Studies in Applied Machine Intelligence – Boston
If you’re looking for a successful career in applied artificial intelligence and machine learning in the fields of pharmaceuticals/healthcare, finance, human resources, and business ventures, the MPS in Applied Machine Intelligence program prepares you to excel in these fast-growing and highly in-demand fields—focusing on data, technology, and human literacy.
Take a quick look
We’re committed to creating an education as unique as your career path. So, whether your goal is a new career or moving up in your field, our innovative programs will get you going your way.
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Customize your plan
We work with you to map your path to your goal.
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Learn from experience
From real-world case studies to employer-based projects, we prepare you to manage what comes next.
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Choose your focus
Whatever you’re passionate about, you’ll find the classes to sharpen your specialty.
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Study anywhere, on your time
Part-time or full-time, we move at your speed, to get you where you’re going.
Overview
In this program, you’ll take a multi-disciplinary approach to learning, creating well-rounded and sought-after innovators primed to utilize data and AI to inform domain-specific business decisions. Combining the disciplines of applied machine learning and artificial intelligence, data management, data analysis, and data visualization, a Master of Professional Studies in Applied Machine Intelligence teaches you to solve business problems within the rapidly growing field of artificial intelligence.
The diverse concentrations of healthcare, finance, human resources, and business ventures are a direct reflection of the AI value potential in these categories. Our program empowers students to apply AI models and algorithms to a chosen industry and focuses on the interpretation, operationalization, contextualization, and implementation of AI.
With a modular curriculum, you can easily customize your learning activities and experiences across multiple contexts both online and on-ground. Plus, you can earn your degree in less than two years.
More Details
Three Literacies
- Technological literacy: evaluating and integrating tools, techniques and conceptual skills necessary for managing complex systems.
- Data literacy: illustrating the significance of digital and global transformation leading to the creation of business strategies, to make data informed decisions, and to drive innovation as well as create competitive advantage.
- Human literacy: lifelong learning, communication, and design, and leading innovation needed for guiding AI systems, including assessing and developing an ethical position, critical thinking and cultural agility.
Unique Features
- Graduate with a portfolio of work samples that demonstrate your range and depth of competencies and skills with machine learning and artificial intelligence.
- Work closely with faculty from different fields and areas of expertise.
- Our experiential AI curricula includes an introductory core, as well as an advanced core with an end-to-end AI education, with the goal to proactively and thoughtfully prepare students for the evolving technology and the challenges it presents.
Career Outlook
According to Gartner, an estimated 2.3 million AI jobs will be created by 2020. Now’s the time to prepare yourself for a changing industry by building desirable skills and experience with an MPS in Applied Machine Intelligence.
Hear more from industry experts speaking at Northeastern’s AI Symposium on how AI-related technologies will impact organizations and workers.
Experiential / Co-op opportunities
Northeastern's signature experience-powered learning model has been at the heart of the university for more than a century. It combines world-class academics with professional practice, allowing you to acquire relevant, real-world skills you can immediately put into action in your current workplace.
This makes a Northeastern education a dynamic, transformative experience, giving you countless opportunities to grow as a professional and person.
Get Set with a Custom Course Plan
General Requirements
Note: All students accepted to the MPS in Applied Machine Intelligence will be required to complete a Python Placement Exam upon acceptance. Those who achieve an 85% or greater will start with EAI 6000, those below 85% will have to take a required Python course in their first term that will count towards a required elective.
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Experiential Network and Capstone
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Elective Courses
Complete a minimum of 10 quarter hours from the following to reach 45 quarter hours.
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Concentrations
AI for Business Ventures
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AI for Finance
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AI for Healthcare
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AI for Human Resources
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Now Let's Talk Admissions
You know where you are headed and you've seen how our program will lead you there. So let's get going. Here's what you need to know before you enroll.
Application Requirements
- Online application
- Statement of purpose (500–1000 words): identifies your educational goals and expectations of the program; please be aware that the University's academic policy on plagiarism applies to your statement of purpose
- Professional resume
- Unofficial undergraduate transcripts (Official transcripts required at the time of admission) Reflecting degrees in engineering, computer technology, or coursework in place of Statistics.
- Two letters of recommendation: from individuals who have either academic or professional knowledge of your capabilities such as a faculty member, colleague, or mentor, preferably one from your current employer
- English Language Proficiency Proof: students for whom English is not their primary language must submit one of the following:
- Official bachelor's degree transcript from an accredited college or university in the U.S, stating degree conferral and date
- TOEFL, IELTS, or NU Global Exam scores
All students accepted to the MPS in Applied Machine Intelligence will be required to complete a Python Placement Exam upon acceptance. Those who achieve an 85% or greater will start with AI 6000 those 84% and below will have to take a required Python course in their first term that will count towards a required elective.
International Requirements
Are You an International Student? Find out what additional documents are required to apply.
Global Engagement Learn how our teaching and research benefit from a worldwide network of students, faculty, and industry partners.
Financing Requirements
Finance Your Education We offer a variety of resources, including scholarships and assistantships.
How to Apply Learn more about the application process and requirements.
Cost and Tuition
Estimated Total Tuition
This is an estimate based on the tuition rates for Academic Year 2020-2021 and does not include any fees or other expenses. Some courses and labs have tuition rates that may increase or decrease total tuition. Tuition and fees are subject to revision by the president and Board of Trustees at any time. For more detailed information, please visit Student Financial Services.
Application Deadlines
Our admissions process operates on a rolling basis; however, we do recommend following the application guidelines below to ensure you can begin during your desired start term.
Spring 2021
| Recommended Admissions Deadline: | |
|---|---|
| International out-of-country application complete (start date: April 12, 2021) | February 8, 2021 |
| International in-country application complete (start date: April 12, 2021) | March 8, 2021 |
| Domestic application complete (first half start: April 12, 2021) | April 2, 2021 |
| Domestic application complete (second half start: May 24, 2021) | May 14, 2021 |
Summer 2021
| Recommended Admissions Deadline: | |
|---|---|
| International out-of-country application complete (start date: July 12, 2021) | May 10, 2021 |
| International in-country application complete (start date: July 12, 2021) | June 14, 2021 |
| Domestic application complete (first half start: July 12, 2021) | June 28, 2021 |
| Domestic application complete (second half start: August 9, 2021) | July 26, 2021 |
Fall 2021
| Recommended Admissions Deadline: | |
|---|---|
| International out-of-country application complete (start date: September 20, 2021) | July 19, 2021 |
| International in-country application complete (start date: September 20, 2021) | August 23, 2021 |
| Domestic application complete (first half start: September 20, 2021) | September 7, 2021 |
| Domestic application complete (second half start: November 1, 2021) | October 18, 2021 |
Winter 2022
| Recommended Admissions Deadline | |
|---|---|
| International out-of-country application complete (start date: January 10, 2022) | November 8, 2021 |
| International in-country application complete (start date: January 10, 2022) | December 13, 2021 |
| Domestic application complete (first half start: January 10, 2022) | December 20, 2021 |
| Domestic application complete (second half start: February 22, 2022) | February 8, 2022 |
Spring 2022
| Recommended Admissions Deadline | |
|---|---|
| International out-of-country application complete (start date: April 11, 2022) | February 7, 2022 |
| International in-country application complete (start date: April 11, 2022) | March 14, 2022 |
| Domestic application complete (first half start: April 11, 2022) | March 28, 2022 |
| Domestic application complete (second half start: May 23, 2022) | May 9, 2022 |
Summer 2022
| Recommended Admissions Deadline | |
|---|---|
| International out-of-country application complete (start date: July 11, 2022) | May 9, 2022 |
| International in-country application complete (start date: July 11, 2022) | June 13, 2022 |
| Domestic application complete (first half start: July 11, 2022) | June 27, 2022 |
| Domestic application complete (second half start: August 8, 2022) | July 25, 2022 |
Student Body Profile
Below is a look at where our Analytics alumni work, the positions they hold, and the skills they bring to their organization.
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Where They Work
- Dell EMC
- JPMorgan Chase & Co.
- ADP
- Staples
- Interactive Data
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What They Do
- Information Technology
- Operations
- Program and Project Management
- Business Development
- Entrepreneurship
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What They're Skilled At
- Business Analysis
- Leadership
- Requirements Analysis
- Software Development Life Cycle (SDLC)
- Project Management
Learn more about Northeastern Alumni on Linkedin.