In the age when knowing the weather forecast for a week beforehand is doable it is no wonder that computers can learn and understand as much as humans do. The advancement of modern technology has paved the way for some path-breaking developments with Artificial Intelligence and Regenerative Medicine is on top of the list. Machine Learning has become a popular choice for computer enthusiasts looking for an unconventional career option. Courses like MS in Machine Learning are being opted to pursue a career in the field.
This Blog Includes:
What is Machine Learning?
Machine Learning is the study of making computers learn complex concepts from data and experience to answer the fundamental questions on research. Owing to its usage in diverse fields like Robotics, Healthcare and Business, it is growing at a fast pace. Taught as a sub-discipline of Computer Science, the subject deals with learning conceptual structures through developmental processes, extracting and retrieving information using algorithms. Its widespread usage has led to the universities offering courses like MS in Machine Learning and Data Science. Using interdisciplinary techniques such as statistics, linear algebra, optimization etc, it is used to create automated systems that can process unprecedented volumes of data at fast speed. Being a subfield of Artificial Intelligence, it offers cost-effective alternatives to data processing in data-rich disciplines like Bioinformatics, Neuroinformatics, Cheminformatics, Environmental Informatics, Social Informatics, Business Informatics, Materials Informatics, Security Informatics etc.
Understanding MS in Machine Learning
The masters in Machine Learning that spans over 1-2 years is proposed to meet a growing need for individuals skilled in Artificial Intelligence and Data Analytics. A practical oriented course designed to train students for the ever-increasing market and giving them the skill set to be the future innovators in the domain of Computer Science. The course covers the principles, design and implementation of the subject to improve the performance of tasks. Combining theoretical and practical aspects of the field, the course aims at the all-round development of a student. Upon the completion of the course, the students are ready to implement their broader understanding of Machine Learning algorithms and their use in program synthesis.
Following topics are covered in MS in Machine Learning:
- Probabilistic Models
- N-gram Models
- Markov and Hidden Markov Models
- Computational Learning Theory
- VC Dimension
- Occam Learning
- Data Mining
- Support Vector Machines
- Algorithmic Models of Learning
- Human-computer Interaction
- Dimensionality Reduction
- Probabilistic Relational Models
- Pattern Recognition
- Program Synthesis
Also Read: Best Books for Machine Learning
The eligibility criteria for MS in Machine Learning can vary for universities as each of them have a different set of requirements, however, the standard eligibility criteria for most of them require you to have:
- Completed a bachelor’s degree or equivalent in Computer Science.
- A valid GRE score as mentioned by the university.
- A valid English-language proficiency test score – IELTS, TOEFL, PTE)
Best Universities for MS in Machine Learning
Join a booming, in-demand field with an MS in Machine Learning from one of the globally recognised universities in the world. Students will develop an in-depth understanding of Machine Learning methods along with practical skills and guided experience in applying those to a real-world scenario. The study curriculum is designed to propel your engineering career forward and help you take the position of an Engineer, Data Scientist and Analyst or Computational Statistician.
Thus we have curated a list of best institutions that will nurture your knowledge to go beyond the realms of science and algorithms and turn your data skills into actionable insights.
- Carnegie Mellon University
- University of Michigan
- Cornell University
- University of California Berkeley
- Stanford University
- University of Massachusetts
- John Hopkins University
- Pennsylvania State University
- University of North Carolina Chapel Hill
- University of California San Diego
- University of Wisconsin Madison
- California Institute of Technology
- University of Illinois Urbana Champaign
- Columbia University
- University of Washington
- Georgia Institute of Technology
The current trend suggests that this as a field is expected to grow at an exponential rate, generating high paying jobs for professionals with the specialization in the subject. An MS in Machine Learning from a reputed university is set to drive you towards a successful and highly rewarding career in the field. Some of the high paying job profiles in the field include:
- Machine Learning Engineer
- Data Scientist
- NLP Scientist
- Business Intelligence Developer
- Machine Learning Designer
Its time to enrol for an MS in Machine Learning to study computational, mathematical and statistical foundations of Machine Learning and pioneer new research. If you need help in choosing the right university to learn such new-age courses abroad, talk to us at Leverage Edu and we can help you in preparing your study abroad application.