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Many students prefer Masters programs in Machine Learning in the USA
Businesses of all sizes embrace emerging technologies, such as machine learning, data science, and artificial intelligence (AI), to accelerate their growth. According to the Analytics and Data Science India Industry Study 2020, advanced analytics, predictive modeling, and data science account for 16% of enterprise analytics revenues. Rapid digital adoption has also widened the skill gap. Many educational institutions worldwide are now offering Masters programs in Machine Learning online and offline to fill this void.
Here are 6 best Masters programs in Machine Learning in the USA
Carnegie Mellon University
Program- Master of Science in Machine Learning
Location- Pittsburgh, Pennsylvania
Duration- Up to 2 years
The Master of Science in Machine Learning program consists of seven core courses, two electives, and a practicum. Incoming students should have strong analytical abilities as well as a strong aptitude for mathematics, statistics, and programming.
MS students take all six core courses-
- Introduction to Machine Learning or Advanced Introduction to Machine Learning
- Intermediate Deep Learning or Deep Reinforcement Learning or Advanced Deep Learning
- Probabilistic Graphical Models
- Machine Learning in Practice (formerly Data Analysis)
- Convex Optimization
- Probability & Mathematical Statistics or Intermediate Statistics
Program- Computer Science M.S. with a Specialization in Machine Learning
Location- Ithaca, New York
Duration- 2 years or more
This is a four-semester program for students who want to advance their knowledge of computer science through advanced coursework, research, writing, and teaching. The program is ideal for self-motivated students with expository skills who enjoy research and working with undergraduates in introductory courses. Students in the program work as teaching assistants and get compensation for full tuition and a stipend.
The program comprises five core areas-
- Artificial intelligence
- Computer science
- Programming languages and logics
- Scientific computing and applications
- Theory of computation
Georgia Institute of Technology
Program- Master of Science in Computer Science with a Specialization in Machine Learning
Location- Atlanta, Georgia
Duration- 2 years
The Master of Science in Computer Science (M.S. CS) degree program helps students prepare for highly productive careers in the industry. Machine Learning, Interactive Intelligence, Scientific Computing, High-Performance Computing, and Human-Computer Interaction are among the 11 areas of specialization available to students.
- Computability, Algorithms, and Complexity
- Introduction to Graduate Algorithms
- Computational Complexity Theory
- Design and Analysis of Algorithms
- Graph Algorithms
- Approximation Algorithms
- Randomized Algorithms
- Computational Science and Engineering Algorithms
- Machine Learning
- Computational Data Analysis- Learning, Mining, and Computation
Program- Data Analytics & Machine Learning Master’s Programs
Location- Durham, North Carolina
Duration- 1.5–2 years
The emphasis on data analysis and machine learning equips master’s students with the tools they need to manage, interpret, and gain new insights from data. Students will learn about the mathematical foundations of Big Data, as well as practical programming skills and lessons in machine learning, statistics, and information theory.
- Vector Space Methods with Applications
- Random Signals and Noise
- Programming, Data Structures, and Algorithms in C++
- Introduction to Machine Learning
- Deep Learning
- Probabilistic Machine Learning
- Machine Learning
Massachusetts Institute of Technology
Program- Master of Science in EECS with a Specialization in Machine Learning
Location- Cambridge, Massachusetts
Duration- 1 to 2 years or more
The Master of Science in Electrical Engineering and Computer Science (EECS) program provides opportunities for research in artificial intelligence, computer graphics and vision, human-computer interaction, machine learning, natural language processing, and speech processing.
- Machine Learning for Big Data and Text Processing-Foundations
- Machine Learning for Big Data and Text Processing-Advanced
Program- MS in Artificial Intelligence
Duration- 2 years
In the MS in AI degree program, students will learn how to build modern AI and machine learning systems using creative thinking, algorithmic design, and coding skills. Deep technical training and expertise in machine learning, computer vision, and natural language processing will be provided to students.
- Introduction to Natural Language Processing
- Machine Learning
- Image and Video Computing
- Artificial Intelligence
- Machine learning has tremendous possibilities for developing hi-tech applications in a variety of sectors, such as cyber security, image recognition, medicine, and more.
- All types of businesses are utilizing emerging technologies such as machine learning, data science, and artificial intelligence (AI) to boost their growth. Faster adoption of such technologies has also widened the skill gap.
- Many institutions are providing masters courses in machine learning to curb the skill gap. These courses are available for students in both online and offline modes. Universities like Carnegie Mellon, MIT, Duke, and Cornell also provide these courses.
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Q1. Do AI jobs require masters degrees?
Ans- Most top-level AI jobs, such as research scientists, AI engineers, and big data engineers, typically require a master’s degree. Most AI positions require applicants with strong programming knowledge and skills in MATLAB, C/C++, and Python.
Q2. Can I work in AI without coding?
Ans- Yes, you can! Machine Learning without programming is making AI accessible to all. Artificial Intelligence can be obtained without writing a single line of code, regardless of the size of your company. This is helping to bridge the gap between technology experts and businesses.
Q3. Which AI skills are most in demand?
Ans- Given below are top AI skills-
- Programming Skills.
- R language
- Libraries and Frameworks
- Mathematics and Statistics
- Machine Learning and Deep Learning