Last Updated: August 21, 2022
Recommended Programs for Machine Learning
Machine Learning is a field of study that is considered to be part of artificial intelligence involving the creation and modification of software applications that enhance the accuracy of predicting outcomes. This is an area of intelligence that has high stakes in the job industry with increased projected employment of 11% between 2019 and 2029. Candidates who wish to take up educational programs in this field will mostly be able to choose it as a specialization at a master’s level or they will be able to take certification courses for the same at different universities with a smaller time duration.
Candidates will often be able to choose this field as part of a master’s program in computer science or they will be able to take a direct master’s in machine learning depending on the university they are applying to. Some universities also provide only specializations in artificial intelligence which will contain machine learning as a major component and will provide candidates with a wider scope of job opportunities since they will be well-versed in both artificial intelligence and machine learning.
Cost of Studying MS in Machine Learning
The cost of taking an MS in Machine Learning in the country is dependent on the kind of institution one is studying in along with the level of the degree they are taking. The best machine learning programs offered are at a master’s level with students opting for general programs at a bachelor’s level in subjects like data science, computer engineering, etc. Candidates who opt for a private institution will find that the fee here is higher than that of public institutions. Those who opt for public universities will find that the fee is different for in-state and out-of-state students with the latter having to pay twice or thrice the amount paid by the former.
The estimated fee for taking a master’s degree in the subject can be anywhere between $30,000 to $55,000 per year depending upon the institution they are attending.
Recommended Universities to Study Machine Learning
- Cornell University
- Carnegie Mellon University
- Massachusetts Institute of Technology
- Duke University
- University of Rochester
- Stevens Institute of Technology
- University of California
- Stanford University
- Columbia University
- University of Wisconsin
- Michigan State University
- Georgia Institute of Technology
13 Recommended Programs in Machine Learning
Some of the recommended programs that one can take for machine learning include-
|Programs||University||Place||In-State Fee||Out-of-State Fee|
|MS in Machine Learning||Carnegie Mellon University||Pennsylvania||$52,000 per year||$52,000 per year|
|MEng in CS with Machine Learning||Cornell University||New York||$62,500 per year||$62,500 per year|
|MS in CS with Machine Learning ||Georgia Institute of Technology||Georgia||$19,500 per year||$19,500 per year|
|MS in EECS with Machine Learning ||Massachusetts Institute of Technology||Massachusetts||$29,000 per year||$29,000 per year|
|MS in CS with AI and Machine Learning ||University of Rochester||New York||$1,900 per credit||$1,900 per credit|
|MS in Machine Learning ||Stevens Institute of Technology||New Jersey||$19,000 per semester||$19,000 per semester|
|MS in EECS with Machine Learning||University of California||San Diego ||$17,000 per year||$32,000 per year|
|MS in CS with Machine Learning ||Stanford University||California||$66,500||$66,500|
|MS in CS with Machine Learning ||Columbia University||New York||$75,000||$75,000|
|MS in ECE with Machine Learning ||Duke University||North Carolina||$86,500||$86,500|
|PhD in Machine Learning ||Carnegie Mellon University||Pennsylvania||-||-|
|MS in ECE- Machine Learning and Signal Processing||University of Wisconsin||Madison||$1,200 per credit||$1,200 per credit|
|MS in CS with Machine Learning||Michigan State University||Michigan||$850 per credit||$1,800 per credit|
#1 MS in Machine Learning-CMU
This program has a duration of 2 years and candidates will have to take 4 core courses, 2 menu courses, 3 electives, and a practicum for course completion. The core courses include an introduction and advanced programs for machine learning, data analysis, intermediate statistics, etc. Candidates will be able to choose from programs like deep reinforcement learning, graduate artificial intelligence, regression analysis, convex optimization, etc. as their menu course.
#2 MEng in CS with Machine Learning- Cornell University
This program has a duration of 1 year and focuses on fields like machine learning and computer security. The technical topics covered in the program include applied machine learning, machine learning engineering, natural language processing, human-computer interaction, etc. At the same time, candidates will be able to take studio topics like intellectual property, law for non-lawyers, product management, etc. as part of the program.
#3 MS in CS with Machine Learning- Georgia Institute of Technology
This program has a duration of 1.5 to 2 years depending on the track they choose. Candidates will be able to choose from a project option and a thesis option both of which will require them to complete 30 credit hours. Candidates will be able to choose the machine learning specialization. The core courses for the program will include graduate algorithms, approximation algorithms, randomized algorithms, etc. They will be able to take up electives like reinforcement learning, deep learning, machine learning for robotics, machine learning for trading, etc. as part of the program.
#4 MS in EECS with Machine Learning- MIT
The MS in EECS program at MIT is one of the most prestigious programs offered by the institution. It has a duration of 2 years but candidates will be able to complete it within 1 year if they can fulfill the requirements. Candidates will be able to choose machine learning from the core specializations offered which will include topics like AI, statistical learning theory & applications, machine learning for healthcare, dynamic programming & reinforcement learning, advanced topics in control, etc.
#5 MS in CS with AI and Machine Learning- University of Rochester
This program has a duration of 2 years and is essentially an MS in CS degree. Candidates will be able to choose an AI and machine learning specialization as a part of the program. This will allow them to learn about topics like machine learning, statistical speech, language processing, data mining, etc. They will also be learning about computer vision, artificial intelligence, advanced algorithms, etc. Candidates are required to complete 30 credits for the course.
#6 MS in Machine Learning- Stevens Institute of Technology
This is a direct MS in Machine Learning with an emphasis on both theoretical and practical aspects of the field of study. Candidates will be able to avail themselves of the program in part-time and full-time options and they will be able to get experiential learning and internship opportunities as part of the course. The core courses in the field include AI, statistical machine learning, deep learning, natural language processing, etc. They will also be able to choose from electives like causal inference, web mining, cognitive computing, applied machine learning, big data technologies, statistical methods, etc. The program has a duration of 2 years in all.
#7 MS in CS with Machine Learning- University of California
Candidates who wish to specialize in machine learning will be able to choose the MS program in CS which has a focus on both computer science and computer engineering. MS students will be able to choose from a thesis option, a comprehensive standard plan, and a comprehensive interdisciplinary plan as their track for course completion. They will be dealing with the fundamentals of the subject, updated information within the field, and an area of specialization of their choosing which will be their depth requirement. Students will be able to choose the AI specialization which has extensive content for machine learning.
The content for machine learning includes machine learning theory, data systems for machine learning, 3-D centric machine learning, advanced analytics, machine learning systems, machine learning on geometrical data, machine learning on 3-D data, etc. The program has a duration of 2 years.
#8 MS in CS with Machine Learning- Stanford University
Candidates who have chosen to take an MS in CS from Stanford University will be able to choose the AI specialization which focuses on 3 main components in the field. This course will be 1.5 to 2 years long depending on how long the candidate takes to complete 45 units. The main focus of this track will be on AI principles, natural language processing with deep learning, and machine learning. Under machine learning, candidates will be learning about generative/discriminative learning, neural networks, support vector machines, unsupervised learning, learning theory, etc. Candidates will also be introduced to topics like robotic control, data mining, bioinformatics, speech recognition, etc.
#9 MS in CS with Machine Learning- Columbia University
This program is offered in online mode and has a 30-credit requirement. Students who wish to apply for the program will require a minimum GPA of 3.3 and they will also have to clear the GRE examination. They will have to take two-track courses as a part of the program with the tracks including subjects like computational learning theory, machine learning for data science, graphical models, computer vision, natural language processing, computational aspects of robotics, etc. The elective courses provided include database systems, algorithms for data science, computer vision, computational aspects of robotics, computational genomics, biometrics, etc. Out of these electives, candidates will be required to choose any two.
#10 MS in ECE with Data Analytics & Machine Learning- Duke University
This university is well known for its contribution to the research of machine learning and AI. They provide different tracks for those who wish to take a degree in machine learning. Candidates can choose from an MS or Meng depending on their interests. Both these tracks have different requirements that candidates will have to fulfill for enrollment. The key courses for the program include vector space methods with applications, programming, deep learning, probabilistic machine learning, etc. Other important courses include digital signal processing. Uncertainty analysis, information theory, numerical optimization, etc. The duration of the program is between 1.5 to 2 years depending on how long the candidate takes to complete 30 credit hours.
#11 PhD in Machine Learning- CMU
Candidates who have completed their master’s degree in AI or machine learning will be able to take up a Ph.D. in the subject from this institution. This program will require them to complete 6 core courses and 1 elective. They will also have to prove their skills in teaching and presentation. For the successful completion of the program, they will have to write a thesis and defend the same. The required courses for the program include intermediate statistics, advanced introduction to machine learning, machine learning in practice, etc. Candidates will be able to choose from deep reinforcement, convex optimization, graduate artificial intelligence, regression analysis, etc. for their elective course.
#12 MS in ECE-Machine Learning and Signal Processing- University of Wisconsin
This program has a duration of 12 to 16 months and requires 30 credit hours for course completion. Candidates will be learning about subjects like matrix methods in machine learning, theory in machine learning, image processing, artificial neural networks, mathematical foundations of machine learning, digital signal processing, etc.
#13 MS in CS with Machine Learning- Michigan State University
This program is offered by the College of Engineering at Michigan State University. Candidates will be able to complete this program within 2 years depending on when they can cover 30 credit hours. They will have the option of taking a thesis or non-thesis option for the program. The topics they will cover include parallel computing, foundations of computing, AI, natural language processing, deep learning, language & interaction, data mining, etc.