Want to advance your career by working in the field and studying AI at the same time, but don’t have the energy (or the patience) for a full-blown Master’s degree? University of Pennsylvania’s Master of Science in Artificial Intelligence program might be just what you need. The program’s shorter, more focused courses can give your resume a serious boost from an Ivy League university without putting your career on hold.
If you’re looking to get specialized and get a foothold as an expert in the world of AI, a Master’s degree is the way to go. It’s a short and concentrated journey, and it’ll equip you with the knowledge and skills to become a skilled professional of AI.
And remember, folks, online certificates aren’t really looked down favorably for federal financial aid, unlike online degrees, where you get that support. Therefore, do your homework and make sure you know the ins and outs before you dive in!
Key highlights of the program
- Ivy League pedigree: Benefits of studying at a renowned institution.
- Flexible online format: Balance work and study commitments.
- Practical curriculum: A blend of theoretical knowledge and hands-on projects.
- Potential for financial aid: Access to scholarships and federal student aid options.
What is the focus of the Artificial Intelligence Masters of Science at UPenn?
The Master of Science in Artificial Intelligence (MS AI) program at Penn Engineering offers a comprehensive curriculum designed to equip you with the knowledge and skills to excel in the field of AI. To graduate, one must complete 10 courses: 7 core from the required list, 2 technical electives from a list of three options and one free elective they can choose from other online programs.
Core Courses: The Building Blocks of AI
These core subjects will lay the foundation for your AI experience:
- Artificial Intelligence: This has fundamental concepts of AI, including search algorithms, machine learning, probabilistic reasoning, natural language processing, and knowledge representation. This is a compulsory course in the first semester.
- Natural Language Processing: Students will tackle how to build technologies that enable machines to understand and process human language, with applications in machine translation, sentiment analysis, and more.
- Machine Learning for Data Science: Students experience a variety of machine learning techniques, including regression, classification, clustering, and deep learning.
- Statistics for Data Science: Here, students will learn statistical concepts and their application to data analysis and machine learning.
- Principles of Deep Learning: One can master theoretical and applicatory aspects of deep learning, including neural networks, convolutional neural networks, and recurrent neural networks.
- Technology Ethics and the Legal Landscape: Learning should never be restricted to the technical aspects, that’s why, it’s important to understand the ethical implications of AI and the legal framework surrounding its development and deployment.
- Internet and Web Systems: Students can develop their knowledge on how to build scalable and reliable web systems, essential for deploying AI applications.
- GPU Computing for Machine Learning Systems: One can AI understand how to fasten the speed of AI models by leveraging the power of GPUs.
While the first six are mandatory, students can select from either of the last two core options as their seventh and final core course.
Electives and Practical Experience
You can further expand your expertise in your studies by choosing from a range of electives, including:
- Networked Systems: Students catch on to the principles of network design and implementation, crucial for building distributed AI systems.
- Computer Vision & Computational Photography: Students can develop techniques for analyzing and understanding visual information.
- It is a working title. However, UPenn is also offering an AI Practicum course that will be soon added to their curriculum which will expand student’s learning experiences, as often only offline students get this opportunity.
How do you get admission to MS in Artificial Intelligence at UPenn?
Penn Engineering’s MS AI Online program is designed for professionals. The admission requirements for the program are straightforward. As an Ivy League, it is expected for University of Pennsylvania to be competitive, even in online schooling. But, here’s the bright side: if you fulfill these requirements, you don’t have to worry about anything!
Are you the lost piece of the AI puzzle at UPenn Online?
The ideal candidate for the MS AI Online program is a passionate professional with ambition, someone who is always looking to upgrade and keep up with the current trends. They wish to become a leader in the AI landscape. This program isn’t just about ticking boxes; it’s about finding individuals with a proven track record in computer science, computer engineering, or a related field.
The Essentials of Your Application at UPenn Master’s program
You still need to show them what makes you tick all the boxes apart from your excellent experience. Students need to submit an application with these things:
- Resume: They want to see your functional job skills, the depth of your experience, and evidence of your leadership qualities. Forget about bragging about years of service; what matters most are the lessons learned on your professional journey.
- Personal Statement: This is your space to make it about you and why you should be selected. Tell them why you’re drawn to the MS AI Online program in 1000-1500 words. How will this program elevate your career and equip you to achieve your professional goals? Don’t forget to showcase your commitment – juggling the program with your existing workload requires clear planning.
- Letters of Recommendation: Get a trusted mentor or colleague to vouch for your abilities. Submit at least two and the third can be optional. These letters should paint a clear picture of your academic and professional potential. Skip the generic recommendations from friends or colleagues; go for the individuals who know you best professionally.
- Academic Credentials: Transcripts are your passport to the program. Submit unofficial transcripts when you apply and official transcripts upon acceptance.
- Standardized Tests (Optional): While GRE scores aren’t mandatory, strong scores can strengthen your application.
- You need to pay a non-refundable $90 application fee alongside your other documents.
Comments on the Application Process
Here are some personal views on how we, at CollegeHippo, feel about the whole decision-making and preparation of admissions into the degree:
What we liked about the application process
- Focuses on experience: The application prioritizes your professional journey over standardized tests. It asks for details on your skills, leadership, and online learning experience.
- No GRE: Submission of GRE scores is optional.
- Flexible deadlines: Offers Fall and Spring semesters with clear application deadlines for each. Early decision options are also available.
- Detailed instructions: Provides clear instructions and resources for each required document (transcripts, recommendations, etc.).
What we did not like about the application
- Limited waiver options: While the English proficiency exam can be waived for degrees taught in English, the program offers no other waivers for application components.
- Lengthy essay: The personal statement requires 1,000-1,500 words, which can be time-consuming to write and edit.
- Recommendation letters: Requires a minimum of two; however, discourages letters from colleagues or friends. Securing these letters can take additional time and effort.
How much is it gonna cost you to study at UPenn’s MS in Artificial Intelligence?
The MS AI Online program at Penn Engineering offers a competitive tuition structure designed to make your educational journey accessible. The program costs $3,500 per course unit, totalling $35,000 for the entire curriculum if you take the recommended ten courses overall. Additionally, there are online service fees of $156 per course unit.
One of the significant advantages of pursuing an online degree is the eligibility for federal financial aid. This means that eligible students can tap into a variety of federal student aid options, including loans, grants, and work-study programs, to help finance their education.
By combining a competitive tuition structure with federal financial aid opportunities, Penn Engineering’s MS AI Online program aims to make advanced education in artificial intelligence accessible to a wider range of students. Check our archives for a deeper-dive into the the latest Online Master’s in Artificial Intelligence programs.
Early Bird Dean’s Master’s Scholarship: A Rewarding Step for the Master’s students
Applying early for the MS AI Online program offers several advantages. Not only does it increase your chances of securing the Dean’s Master’s Scholarship for Penn Engineering Online Students, but it also gives you a slight advantage in the admissions process. Additionally, early applicants can expect to receive a decision sooner, allowing them to plan their academic journey with greater certainty.
Applications will start in a month, from 16th December 2024 and the early application deadline is 3rd March 2025.
So, what are you still doing here? Go! Go! Go! Get that worm!
Our Overall Review
UPenn Online Engineering’s MS in Artificial Intelligence program offers a wonderful opportunity for professionals who have a strong background and are looking to get even better. With its flexible format, rigorous curriculum, and prestigious Ivy League affiliation, this program can provide a significant boost to anyone’s professional profile. While the program demands dedication and commitment, the potential rewards are substantial.
UPenn vs Georgia Tech: $540 per course Vs. $3,500 per course unit?
When comparing the Online Master’s programs in Artificial Intelligence at the University of Pennsylvania (UPenn) and Georgia Tech, the first big difference is cost. Georgia Tech’s OMSCS program is a standout for its affordability, charging just $540 per course, with $180 per credit hours (with further discounts for taking additional credits). Hence, the total cost $5,400 for a minium of 10 courses. This makes it a highly budget-friendly option, especially for professionals looking to gain AI expertise without breaking the bank. On the other hand, UPenn’s program comes at a significantly higher price tag, totaling $35,000 for the entire degree. For students considering financing options, UPenn offers eligibility for federal financial aid, which could help ease the financial burden, but overall, Georgia Tech offers a much more affordable pathway.
In terms of reputation and curriculum focus, both institutions offer exceptional opportunities but with different strengths. UPenn, being an Ivy League school, brings a prestigious degree that can open doors in more traditional or academic environments. However, Georgia Tech, while not part of the Ivy League, is renowned for its emphasis on practical, hands-on learning and cutting-edge research, particularly in robotics and machine learning. Georgia Tech’s flexible, self-paced learning format also gives working professionals more control over their schedules, while UPenn offers a more structured approach with access to specialized electives and an upcoming AI practicum for real-world experience. Ultimately, if you’re looking for flexibility and affordability, Georgia Tech stands out, but if prestige and financial aid opportunities are more important, UPenn may be the better fit.
$35,000 at UPenn vs. $10,000 at UT Austin—Is the Price Difference Worth It for an AI Master’s?
When weighing the choice between UT Austin and UPenn for an AI Master’s, the decision ultimately comes down to your priorities. UT Austin offers an exceptional, globally recognized program for just around $10,000, making it a fantastic option for those seeking affordability, hands-on experience, and access to Austin’s vibrant tech scene. In contrast, UPenn—with its prestigious Ivy League status—comes at a much steeper price of $35,000, but delivers unparalleled academic rigor, a rich network, and the potential for federal financial aid. UPenn’s program focuses on leadership and professional experience, appealing to those aiming for a career in elite AI research or top-tier industry roles. While UT Austin stands out for flexibility and innovation, UPenn offers a more traditional, research-driven approach with deep academic roots.
Flexibility vs. Prestige: How Johns Hopkins and UPenn Stack Up for AI Master’s
The AI Master’s programs at Johns Hopkins and UPenn both offer top-tier, flexible online options, but they differ in several key areas. Johns Hopkins stands out for its flexibility, offering students the choice between applied or theoretical tracks and a wide array of electives. This makes it an ideal choice for those who want to tailor their studies to specific interests. In contrast, UPenn’s program is more structured, with 7 required core courses and fewer electives. However, it benefits from the prestige of an Ivy League institution and includes a unique AI Practicum, giving students valuable hands-on experience.
While both programs come with a significant price tag, Johns Hopkins offers a Dean’s Fellowship and strong employer contribution options, whereas UPenn provides federal financial aid and a competitive Early Bird scholarship. Admission to both programs emphasizes professional experience, though Johns Hopkins also offers provisional admission for applicants who need to complete certain prerequisites. In the end, if you’re seeking a highly flexible and customizable curriculum, Johns Hopkins may be the better choice. However, if you’re drawn to the networking and prestige of an Ivy League education, UPenn could be the right fit for you.