Masters In Machine Learning Online

Machine learning is set to revolutionize today’s tech industry. That’s probably why more and more companies want to hire experts for their offices. Also, there are a growing number of master’s programs available offering a dedicated study in machine learning. If you want to get into Machine Learning, you will eventually need to get a Master’s Degree in the topic. But there are many programs to choose from. In this article we have gathered and ranked the top Master’s programs in Machine Learning (ML) for 2022.

Machine Learning

Best Master’s Degree In Machine Learning


With the advent of deep learning, neural networks, data science and artificial intelligence, there’s a lot of interest in machine learning, as well as master’s programs in machine learning. In this article, we’ll cover the top programs for machine learning, give you a rundown of what to look for in a program, and tell you how to actually get into them. According to, The average Machine Learning Engineer salary in the United States is $122,283 as of January 27, 2022 but the salary range typically falls between $110,679 and $135,729.

Masters In Machine Learning Online 2023 | Top 14 Rankings

#1 Best Online Machine Learning Programs

Autonomous systems are increasingly becoming an important part of our future, such as robots, autonomous cars, and self-driving cars. The IU Online Master of Science in Artificial Intelligence will prepare you for a career in which advances in artificial intelligence make things possible that seemed impossible only a few years ago.
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#2 Best Online Machine Learning Programs

In this MSc, you’ll gain a deeper understanding of state-of-the-art data science, with applications touching on issues as diverse as mathematics to physics, and from biology to computer science.
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#3 Best Online Machine Learning Programs

After completing the program requirements, the graduate will be able to: demonstrate a highly specialized understanding of the modern machine learning pipeline: data, models, algorithmic principles, and empirical evidence; Acquire advanced knowledge of data preprocessing and the use of various exploration and visualization tools.

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#4 Best Online Machine Learning Programs

The study of Artificial Intelligence (AI) is one of the most exciting areas of computer science and engineering.

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#5 Best Online Machine Learning Programs

If you’re fascinated by artificial intelligence, the application of robotics, and creating machines that can ‘see’, then this program is for you.

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#6 Best Online Machine Learning Programs

Understand machine learning and autonomous system technologies and learn how to research, design, and develop them.

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#7 Best Online Machine Learning Programs

Become an Artificial Intelligence expert by learning how to develop the algorithms and systems that enable self-driving cars, smart cameras, surveillance systems, robotic manufacturing, machine translation, internet searches, and product recommendations.

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#8 Best Online Machine Learning Programs

Machine learning is an engineering branch, which is focused on implementing machine learning algorithms with an application-oriented approach, such that it can be used for imaging, audio, or other sensory inputs.

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#9 Best Online Machine Learning Programs

Unleash the power of statistics to make sure the right choices are made.

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#10 Best Online Machine Learning Programs

Many professions and industries, such as manufacturing, retail, medicine, finance, robotics, telecommunications, and social media, are increasingly using Machine Learning. After completing the programme, graduates will be well qualified to pursue exciting careers in industry and doctoral studies.

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#11 Best Online Machine Learning Programs

Advances in algorithms and machine learning are being used to extract information for applications including self-driving cars, optimised manufacturing, improved healthcare, and more energy-efficient systems.

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#12 Best Online Machine Learning Programs

A number of different areas such as computer vision, speech recognition, and language processing have been revolutionized by the development and use of machine learning (ML) and artificial intelligence (AI).

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#13 Best Online Machine Learning Programs

The Master of Science in Artificial Intelligence, accredited by the American Association for the Advancement of Science, enables you to create cutting-edge methods for various applications such as biotech & medicine, cybersecurity, adtech, law, and sustainability.

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#14 Best Online Machine Learning Programs

Getting a master’s degree in machine learning puts you on the fast track to making an impact in one of the fastest-growing fields of today.

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What Is Machine Learning?

The field of machine learning consists of the development of methods that allow computers to learn without being explicitly programmed. This is a very basic definition but it does have some deep implications. The goal of machine learning is to develop programs that can learn on their own from data they’re given.

Machine learning is a subset of artificial intelligence (AI) that allows computer programs to access data and learn for themselves by analyzing it. Computer programs that learn from experience without being explicitly programmed are called machine learning. Machine learning is an integral part of a much broader field of study known as artificial intelligence (AI). In fact, machine learning methods are used in almost every AI project.

Machine learning will continue to transform business, science, and our daily lives. It is an iterative process, and the sophistication of the AI that we see today will continue to improve, little by little, year after year.

What Is A Master’s In Machine Learning?

The Master of Science in Machine Learning program offers students with a Bachelor of Science degree the chance to learn more about Machine Learning. Students will become familiar with many applications of machine learning, including using machine learning to predict outcomes and to optimize systems. Students will have the opportunity to work on research projects from faculty members throughout the department and gain an understanding of how machine learning is applied within various fields. The program primarily consists of coursework, although there is an opportunity for students to engage in research.

Machine Learning Degree Requirements

There are many universities in the US that have full-time as well as part-time ML degree programs. The requirements for the admission may vary from university to university. Some might ask for more documents than others. You should check the websites of these institutions which will be providing such courses.

Master of Science in Machine Learning Curriculum

The Master of Science in Machine Learning invites citizens from around the world to participate in a new era in big data, Artificial Intelligence, and computational science. It is a global community that develops groundbreaking methods for the interpretation and prediction of information.


MS students take all seven Core courses:

  • 10-701 Introduction to Machine Learning or 10-715 Advanced Introduction to Machine Learning
  • 10-703 Deep Reinforcement Learning or 10-707 Topics in Deep Learning
  • 10-708 Probabilistic Graphical Models
  • 10-716 Advanced Machine Learning: Theory and Methods (formerly 10-702 Statistical Machine Learning)
  • 10-718 Data Analysis
  • 10-725 Convex Optimization
  • 36-700 Probability & Mathematical Statistics or 36-705 Intermediate Statistics


  • Special Topics in Machine Learning
  • Algorithms for NLP
  • Machine Learning for Text Mining
  • Neural Networks for NLP
  • Multimodal Machine Learning
  • Algorithms
  • Graduate Artificial Intelligence
  • Multimedia Databases and Data Mining
  • Algorithms in the Real World
  • Computer Vision
  • Regression Analysis
  • Advanced Statistical Theory I
  • Advanced Statistical Theory II
  • Independent Study, under ML Core Faculty
  • Independent Study, under ML Core Faculty


MS students also complete a 36-unit practicum (an internship or research related to Machine Learning), generally conducted during the summer.

Opportunities For Machine Learning Majors

Software Engineer

Software engineers are basically computer scientists with a keen interest in writing applications. Software engineers use the principles from computer science and engineering in mathematics acquired from their machine learning degree, to design and develop software. They build things like apps, databases, and operating systems out of computer-based algorithms – which means they need to be able to write code that a computer can understand. Machine learning specialists use analytical tools and processes to make mathematical models in order to develop software. In short, computer scientists have started using mathematical principles in their work. Salary: $110,140 per year

Designers of Human-Centered Machine Learning

Designers in human-centered machine learning have to constantly juggle these three parts: user experience, applications, and data. These are all part of any one ‘system’ that allows them the opportunity to create something that can be useful and meaningful for a person. This means understanding how users will interact with the machine. The designers create a system that runs on ‘data’, which is essentially a stream of information which then processes that information through an ‘application’ and gives it back to the user in the form of a ‘user experience’.

Netflix is a good example of companies creating interfaces that mimic personalization and in turn create a better experience based on machine learning, but the process can be more abstract. We are able to ‘train’ our smartphones to recognize a voice, we can even train our phones to ‘learn’ and better suit our needs. This is all based on data and algorithms that eventually make sense and ‘learns’ as an individual user.

Machine learning will become increasingly useful for businesses, as it is expected to be commonly used in the coming years. As a result, more designers will likely need to be involved in human-centered machine learning in order to build such technologies.

With large data sets tracking financial data online, machine learning is gaining an important role in the financial industry as more and more people rely on online banking. Banks are working with software developers to design programs that are able to detect subtle patterns found within these vast data sets. Machine learning algorithms are designed to find these patterns and connect them to past events that may or may not have been considered fraudulent.

While ZipRecruiter is seeing annual salaries as high as $179,000 and as low as $25,000, the majority of Human Centered Design salaries currently range between $81,500, (25th percentile) to $176,500, (75th percentile) with top earners (90th percentile) making $177,000 annually across the United States.

Computational Linguist

Computer linguists use and develop a variety of programs and applications that help machines learn to follow spoken commands and to recognize conversational patterns. They test these programs for accuracy through subjectivity tests, in which participants in a focus group verbally respond to a series of questions or verbal instructions.

Computational linguists can find high-paying jobs in banks, government agencies and research organizations. They might work with teams of economists, lawyers or scientists, for example, with the goal of building programs capable of mining legal documents and spotting trends that humans might fail to recognize.

Salary level varies depending on the industry and particular role. PayScale indicates that computational linguists make an average of about $81,747 a year, with the top-end annual salary at $106,000.

Data Scientist

When applying to become a data scientist, you will need to be proficient in multiple programming languages. Programming languages that include statistics, such as R, Python, and SQL are used every day by data scientists. This is because these languages have ways of analyzing and organizing information. Data analysis is the process of using data to discover useful information. If you’re thinking about becoming a data scientist, learning these programming languages will help you get your foot in the door.

For most data scientists, the job is not only about using cutting-edge machine learning algorithms but also about integrating analytical methods to resolve business challenges. Data scientists typically have an engineering degree in Computer Science, Engineering or Mathematics. Their focus is on applying their technical skills while making strategic decisions for running a highly successful enterprise: They will be responsible for developing new solutions and helping organizations reduce cost and improve their performance through data analytics and a predictive approach.

The average data scientist salary is $126,830 per year, according to the U.S. Bureau of Labor Statistics. The driving factor behind high data science salaries is that organizations are realizing the power of big data and want to use it to drive smart business decisions.

FAQs About Master’s In Machine Learning

Making a career change into a machine learning engineer would be a good move. Today, machine learning expertise ranks as one of the most sought-after technical skills, and was recently cited as the third most desired AI job.

Engineers tend to earn more than the national average salary and some reputable organizations expect this trend to continue in the future. In fact, 10 of the top 17 highest paid degrees at the time of writing were engineering degrees. To become an engineer, you will most likely need a degree.

So, exactly how much do machine learning engineers make? According to Indeed’s research, the average machine learning salary is approximately $146,085 (an impressive 344% increase since 2015). A machine learning engineer’s average salary is much higher than other technology jobs on the list.

Artificial intelligence (AI) is a simulation of human intelligence processes by machines, especially computer systems. Despite the definitions, many people consider that Artificial Intelligence and Machine Learning are the same. Recently, Google has announced that its new AI combines both Machine Learning and Neural Networks. As we all know, ML is a subset of AI which focuses on methods to create systems that can learn from data. This learning will provide the basis for automatically informed decisions or actions in the future.

Software Developer

Software developers also help to make sure that upgrades work properly, and they will provide documentation for the systems they build to assist with the machine’s ongoing maintenance. Their work involves strategic planning, including the creation of models and diagrams, to plot out how an entire system will need to work in concert with its various parts and components. These specialists are also responsible for creating user manuals and training guides for other users of the software.

A software developer is responsible for creating and maintaining the source code which drives a computer’s operating system and applications. They also test these programs to see if they are working according to their specifications and can then deploy them across their organization. The work of a software developer encompasses writing and updating code, estimating timelines for the completion of programming tasks, and creating features to complete larger tasks. A developer must not only have strong knowledge of computer science and how the hardware and software systems interact, but also database modeling, data structures, technical writing, problem solving skills and a sound understanding of storage architecture, such as distributed processing.

The average salary for a Software Developer is $72,283. Visit PayScale to research software developer salaries by city, experience, skill, employer and more.

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