Training in data science can come in several ways, whether from online certifications, boot camps, or online tutorials, all of which are justified and trustworthy pathways to data science learning. Here we will be discussing the Top Five Data Science Master Programs for this post. These Master’s programs come from conventional four-year universities, most of which have recently added a degree in Data Science to their brochure. The other ways of Data Science learning and about the forms of the learning, we will attach a link below regarding the article. The recommended services are as follows:
1. SMU (Southern Methodist University)
Southern Methodist University which is also known as SMU is the most recommended Data Science study center. This Data Science School regardless holds a prestigious position in the state of Texas. One must keep in their mind that it is better to be in a school which is nearer to the state of your working place.
The online program mainly lasts for 20-28 months and consists of 33.5 credits. Courses include Machine Learning and Business Analytics-
- Data Science.
- Statistical Foundations.
- Applied Statistics.
- Modeling and Inference.
In the statistics courses, you can expect to become proficient in experimental design, analysis of variance, ethics, and communication of results. What makes these two statistics courses unique is the focus on communicating what the results mean in a non-technical setting.
Here are the choices for specializing in machine learning
- Learning Computer II.
- Processing natural languages.
- Protection of Data and Networks.
The Data and Network Security course is a unique course that might not see in most Data Science programs. This course includes topics like ciphers, hash algorithms, and secure communication protocols. The NLP course covers text classification, clustering, tagging, taxonomy, corpus analytics, and semantic query analysis.
2. UC Berkeley
The Master of Information and Data Science program at the University of California at Berkeley is online, like SMU. With three primary paths, this program is flexible: accelerated, standard, and decelerated. If you have a current job or kids, a slower path could be a better approach.
Here are some of the Berkeley courses:
- Machine Learning Applied.
- Behind the Data: People & Values.
- Processing of natural language with Deep Learning.
This program is based at Columbia University’s Data Science Institute for its Master of Science degree in Data Science. They also have a Ph.D. degree in Data Science, which is very interesting. The curriculum breaks down the courses in the following disciplines:
- The Science of Computers.
- Ingenieur, Programmer.
- The Electives.
Here are a couple of Columbia’s special courses to highlight:
- Data Science Algorithms.
- Capstone and Ethics for Data Science.
- Topics in Operations Research: Theory and Implementation of Personalization.
- Quantitative Finance Topics: Big Data in Finance.
As you can see, there are lots of specific courses to choose from in Columbia. Overall, with an emphasis on computer science and programming, they are the most detailed in data science.
The Big Data course discusses algorithmic trading subjects, while the Theory course is focused more on personalization systems, behavior-based, and content-based recommendations.
Data Science is characterized by the University of Michigan as a combination of computer and information science, statistical science, and domain expertise.
- Data Management and Manipulation Skills.
- Data Science Approaches experience.
- Capstone Cape.
- The Electives.
In this curriculum, there are special and tried-and-true courses as well, some of them highlight includes the following:
- Retrieval of knowledge and Web Search.
- Health Big Data Case Studies for.
- Processing Adaptive Signal.
- Advanced processing of signals.
Concerning health, the emphasis of these courses is signal processing and Big Data. A credible healthcare system is also part of the University of Michigan, so it is no surprise that their Data Science curriculum also focuses on health topics. However, a unique focus is the elective signal processing that they have that you can enroll in.
At Syracuse University, the Master’s in Applied Data Science program is 36 credits and is usually completed in 2 years. Analytics focuses on the core of this program. While they stress analytics, the program also promotes its elective courses which will offer more flexibility to its students, including 12–15 credits worth. The primary facets highlighted by this program are:
- Data collecting and organizing.
- Pattern identification.
- Development of alternative tactics.
- Business Decisions Implementation.
- Skills for Communication.
- Dimensions of ethics.
The courses include a common core, an analytics core for applications, and a core for electives:
- The Analytics of Big Data.
- Analytics for Market.
- Management Science Principles.
- Analytics for Marketing.
- Analytics on Accounting.
- Management of Clouds.
- Internship in Datta Applied Science.
This program is the way to go if you want to be more business and customer-facing in your future role in Data Science. The analytics courses concentrate on survey research, data management, and synthesis.
There are plenty of benefits to attending a graduate program at the universities discussed. Ultimately, it is up to you to decide which graduate school you will attend. These programs may not be for you.
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