While pursuing a master’s in machine learning, programs teach a combination of research methods, statistics, programming, and computer science. Usually, this includes courses in algorithms, artificial intelligence, and data structures.
In addition, some master in machine learning programs include a concentration on a specific application, such as business, nursing informatics, or computer information systems.
10 Master’s in Machine Learning Programs
Many of the master’s in machine learning programs listed below combine statistical analysis and data mining with elements in data science or computer science programs with key topics in programming for a complete understanding of the field.
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Though a relatively young school, George Mason University has made impressive strides in size, stature, and influence in just a short amount of time. Now, as Virginia’s largest public research university, they strive to set the benchmark as a bold, progressive education.
About the Machine Learning Master’s at George Mason
The Master of Science (MS) in Computer Science prepares students for research and professional practice in computer science and related programs. This includes topics such as:
- Fundamentals and advanced work in artificial intelligence and machine learning
- Theoretical computer science and intelligent systems
- Programming languages
- Visual computing
Purdue University combines history, traditions, and achievements with the application of technology and research to teach students how to meet the challenges of the modern world.
About the Machine Learning Master’s at Purdue
Recently, Purdue has hired 15 new faculty members for the Department of Computer Science and plans on hiring even more moving forward.
These faculty members are looking for graduate students to the Master's in Computer Science to advise and mentor as they carry out their research projects in topics such as:
- Machine learning and information retrieval
- Theory of computing and algorithms
- Databases and data mining
- Computational science and engineering
Typically, master’s students earn their degree in three or four semesters, though students with assistantships may take longer because of a lower course load.
A world-class research institution committed to use-inspired research with real-world applications, Drexel University values experiential learning to help students develop knowledge, skills, and values.
About the Machine Learning Master’s at Drexel
The MS in Computer Science - Master offers a multidisciplinary and in-depth understanding of the core and advanced topics of computer science while placing an emphasis on theory and practice through courses such as:
- Approximation Algorithms
- Advanced Data Structure and Algorithms
- Machine Learning
- Advanced Artificial Intelligence
- Knowledge-Based Agents
Founded on the Yale campus in 1920, the University of New Haven is a private, coeducational university offering transformative, career-focused programs to a diverse and vibrant community of more than 6,800 students.
About the Machine Learning Master’s at New Haven
The 30-credit Master of Science in Computer Science blends theory with hands-on practice to teach a solid foundation of skills and the ability to adapt to the constantly evolving landscape of computer science.
In addition, this program strives to offer flexibility of preparing you to enter the field or to continue your education.
Some of the required courses and electives include:
- Artificial Intelligence
- Cryptography and Data Scrutiny
- Computer Networks and Data Communication
- Algorithm Design and Analysis
Don’t Have a Bachelor’s in Computer Science?
The University of New Haven MS in Computer Science program has a set of six bridge courses to help you transition from your previous degree and experience to a level of readiness to successfully pursue your master’s.
At Northcentral University, they are dedicated to providing students with the personal attention you’re looking for when pursuing an advanced degree.
This is why they offer a class size of one, which means you partner with a doctoral faculty member in each of your courses so that you can receive the personal attention you’re looking for.
Machine Learning Master’s Programs at NCU
About the Machine Learning Master’s at NCU
The machine learning master’s programs at NCU teach a broad knowledge base that includes topics such as:
- Data lifecycle
- Data science
- Data mining
- Big data integration
- Data visualization
These topics and others help analyze how to process large amounts of unstructured data into useable datasets that organizations can utilize through the creation of algorithms and machine learning techniques.
Looking to Earn a PhD?
In addition to the master’s programs, NCU also offers a Doctor of Philosophy in Data Science.
Founded in 1946, Utica College is a comprehensive, independent, private institution that offers a high degree of personal attention to create a community of learners with diverse experiences and perspectives.
Machine Learning Master’s Programs at Utica
- MS in Data Science
- MS in Data Science: Financial Crime
- MS in Data Science: Social Science Analytics
- MS in Data Science: Business Analytics
- MS in Data Science: Cybersecurity
About the Machine Learning Master’s at Utica
All of the MSDS programs at Utica share similar core courses, which include:
- Statistical Methods
- Data Mining
- Machine Learning
These courses focus on teaching strong analytical skills and expertise in research methods and how to apply findings for meaningful change.
In addition, the emphasis on research design and the critical evaluation of data using theoretical models help teach an understanding of the limits of data, as well as legal and privacy issues.
The State University of New Jersey, Rutgers University is a leading national research university and the state’s preeminent public institution of higher education. Established in 1766, Rutgers is the eighth-oldest higher education institution in the United States and has more than 69,000 students.
About the Machine Learning Master’s at Rutgers
As other analytical degree programs adapt to the advent of Big Data, the MSDS at Rutgers is designed from the ground up to focus on the latest systems, tools, and algorithms to retrieve, process, and analyze large data sets.
Some of the common courses include:
- Data Structures and Algorithms
- Massive Data Mining and Learning
- Artificial Intelligence
- Machine Learning
- Advanced Algorithms
- Linear Algebra
Master’s in Machine Learning Programs at Rutgers
Loyola University Maryland is a Jesuit, Catholic University committed to the educational and spiritual traditions of the Society of Jesus and the development of the whole person and inspires students to learn, lead, and serve in the diverse and changing world.
About the Machine Learning Master’s at Loyola
As organizations continue needing to derive value from available data, the Master of Science (MS) in Data Science teaches programming skills in Python needed to transform messy web data into clean, useable data.
In addition, the program blends computer science and statistics courses with business courses so that students who have earned the degree should be able to adapt their statistical ad computational skills to any domain.
St. John’s University is committed to academic excellence and the pursuit of wisdom to preserve and enhance an atmosphere in which scholarly research, imaginative methodology, global awareness, and an enthusiastic quest for truth serve as the basis of the teaching-learning process.
Machine Learning Master’s Programs at St. John’s
- Data Mining and Predictive Analysis, MS
- Applied and Computational Mathematics, MA
- Master of Science in Computer Science
About the Machine Learning Master’s at St. John’s
As computer science and predictive analysis continually adapt to meet the needs of businesses, governments, healthcare, and academia, the various master’s in machine learning programs from St. John’s strive to teach topics such as:
- Theoretical mathematics
- Procedures and algorithms that underlie computation
- Statistical and data mining techniques
- Identify patterns and trends
- Build models to predict future events
With 24 campuses and 17,000 faculty and staff serving more than 100,000 students, Penn State University is where inspiration meets perspiration. By focusing on teaching incoming students that the real measure of success is what you do to improve the lives of others, PSU follows a set of values to keep everyone consistent in the way they conduct themselves.
About the Machine Learning Master’s at Penn State
The Master of Science in Computer Science emphasizes practical concerns and theoretical background, providing students with the skills and knowledge to perform a variety of tasks, including the development of:
- Scientific and engineering applications
- Safety and / or security critical systems
- Systems software
- Solutions to computationally hard problems
The program is a one-year intensive master’s degree meant to prepare students for work in industry. While there is no thesis required, there is a final paper during the last semester of the program. Some of the courses include:
- Algorithms and Data Structures
- Database Management Systems
- Programming Language Concepts
What Is Machine Learning?
Machine learning is the science of getting computers to learn and act like humans do. This includes providing data and code so that a machine can learn to make a determination or prediction without explicitly being programmed to do so.
In other words, machine learning is based on algorithms that can learn from data or how to perform important tasks without relying on rules-based programming.
Difference Between AI and Machine Learning
The difference between artificial intelligence (AI) and machine learning is that AI is the ability of a machine to carry out tasks in a similar way as a human. On the other hand, machine learning is the application of AI that allows machines to learn for themselves.
For instance, an algorithm can tell an AI how to respond in certain situations, whereas during machine learning computers are given access to data to learn different responses and make predictions without the aid of humans.
List of Machine Learning Masters Programs
MS in Computer Science
Master's in Computer Science
MS in Computer Science
Master of Science in Computer Science
MS in Data Science, MS in Computer Science
MS in Data Science, MS in Data Science Cybersecurity, MS in Data Science Business Analytics
MS in Data Science - Computer Science and Statistics Tracks
MS in Data Science
Data Mining and Predictive Analysis, Applied and Computational Mathematics, MS Computer Science
Masters of Science in Computer Science
4 Key Concepts of Machine Learning Master’s Programs
It seems that machine learning continues to change every day. That’s because companies such as Google and Tesla have put so many resources into developing technologies that rely on machine learning.
Some of the key concepts of machine learning, which you’ll likely study while earning a master’s degree include those listed below.
1. Machine Learning Can Predict
One of the key aspects of machine learning that separates it from other technologies is that it can take data and predict how to solve problem by itself.
In essence, machine learning is an advanced form of statistics that learns to identify patterns and data to make predictions from those patterns.
2. Machine Learning Requires Training
Machines can’t learn by themselves. They still require training through the form of algorithms and repetition, similar to the way humans learn, to achieve successful predictions.
For instance, computers can now “see” images and categorize them. They can also “read” text and understand context, whether the sentiment is positive or negative. Now, computers can also listen to us, understand us, and respond.
However, this doesn’t happen overnight and includes a learning process.
3. Not 100% Accurate
Machine learning isn’t perfect. In fact, many companies are happy with about a 90% success rate. However, the whole concept of learning means that they will continue to improve.
For instance, recently many companies were happy with only an 80% success rate. As we continue to develop and improve the learning processes, machines will continue to approach 100% accuracy.
Whether they ever achieve 100% accuracy is yet to be determined.
4. Machine Learning May Change the Future
The possibilities seem endless as to how machine learning can impact the future. Some of these include:
- Personalized healthcare based on your genetic makeup and lifestyle
- Data analysis and data security programs
- Computer assisted security in airports and stadiums
- Self-driving cars
- Advanced fraud detection in financial and insurance fields
- Universal translator on your phone or other device
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