Masters in Data Science

What Do You Learn in a Masters in Data Science

Those who complete a master’s degree in data science may learn a lot about the data landscape and how quickly it is changing. One of the reasons students embrace this type of education (and employers often seek it out in employees) is because of just how complex and ever-changing the field is. This type of degree may enable students to get more of the most recent and modern skills they need to work in the field.

The master of data science degree aims to teach a wide range of topics, including predictive modeling, artificial intelligence, data visualization, big data, and machine learning, among others. The goal is often to build on current skills to better manage, visualize, and explore data sets using the most up to date technologies and resources. This often means using applied data science and analytical methods within the course work.

Those who complete this graduate level degree in data science may hope to work as data scientists or in other fields of computer systems. They may work in the private or non-profit sector as well as government positions as a result.

The courses available to students in data science may offer some flexibility. Students may wish to pursue various electives to achieve their desired educational and career path.

Top 25 Schools with a Masters in Data Science

Consider these colleges and universities in the U.S. graduating the highest number of students with a master’s degree in data science, as reported by the NCES in the 2019/20 school year.

Courses for a Master’s Program in Data Science May Include

Math for Data Scientists

In this course, students may learn techniques for interpreting mathematical models. These could occur across multiple disciplines in mathematics. Those may include linear algebra, discrete math, probability, and calculus. This course aims to provide a base for other courses taken in this program.

Applied Statistics with R

The base of this course is often statistical analysis. Students may cover topics such as evaluating statistical information and performing data analyses. In this course, the R language is often introduced to be used in statistical analysis. Descriptive statistics, central tendency, and probability theory may all be covered, among other topics.

Data Science in Practice

This course is typically based on case studies. The purpose is often to provide problem solving skills and to teach technical and leadership roles in the field of data science. In this course, the students may act as data scientists while using the case studies as a guide.

Database Systems and Data Preparation

Data management and preparation are often the base lessons for this course. Items such as the relational model, normalization process, and structured query language may all be covered in this course. Data cleaning and integration, database programming, and load operations are all topics that may be covered..

Practical Machine Learning

The basis of this course is often to introduce machine learning and how it applies to business applications. Students may learn various algorithms and application techniques as a part of the course. Students may also implement machine learning models that may be used in the field of data science.

Decision Analytics

This course is designed to cover a number of topics in data analytics. Solution techniques, modeling approaches, and fundamental concepts are all topics that may be covered in this course. Linear programming, goal programming, and network optimization may all be covered in this course.

How much does a Masters in Data Science cost?

Students who are thinking about a career as a data scientist or a similar field may need to come up with funding options for their education. Financial aid may be available to those who qualify. The average cost paid by a master’s student for the 2018 to 2019 school year was $19,314, according to NCES. That makes it important to look for all sources of funding available to cover those costs.

The good news is that there may be a number of different paths for getting that funding. Take a closer look at some of the most commonly used methods for paying for a master’s degree.

Scholarships

It is often important for students to consider scholarship opportunities. That’s because these are funds that may be used to pay for college and other needs, but they often do not require repayment. Students may find a wide range of scholarship options available to them for completing a data science degree, including at the master’s level. Some of the options in scholarships for data science may be readily available.

Federal Loans

One of the ways to cover the cost of college, including at the master’s level, may be with federal student loans. These loans are often backed by the U.S. government. As a result, they typically may be more affordable and have interest rates that are more competitive other loans. Yet, there may be many requirements to receiving them. At the master’s education level, there might be fewer options available. Some of the most commonly used loans may include the following:

• Direct Unsubsidized Loans: These are often available to graduate schools and professional students. Unlike direct subsidized loans, which are usually made available to undergraduate students with demonstrated financial need, direct unsubsidized loans often do not have a need based requirement. Many students may be eligible for them.
• Direct PLUS Loans: These are typically made available to professional or graduate level students. They may be designed to pay for educational expenses that are typically not paid for through other loans. Eligibility for these loans is often not based on financial need. However, some may require a credit check to be performed, and borrowers may not qualify without meeting other requirements in some cases.
• Direct Consolidation Loans: These loans often enable a student to combine all of their undergraduate and graduate level federal debt into one new loan. This consolidation loan is typically provided after a student completes their education.

Be sure to check qualifications for any federal student loan to ensure your degree path qualifies for it.

Private Student Loans

Private student loans may also be available to pay for a master’s in data science. This type of student loans is usually not backed by the government. That means all of the terms and conditions may be different – and they may vary significantly from one organization to the next. Those considering the use of private student loans should think about the following:

• Any credit score requirements for obtaining the loan
• Limitations on repayment adjustments or term changes
• Costs associated with the loan, including fees
• Whether the interest rate is fixed or variable and competitively set
• Consolidation options
• Repayment options

Private loans may be very helpful for those seeking out a master’s degree in data science. They may often help fill in gaps for funding this graduate level of study.

Is a statistician a good career?

Statisticians may be one of the options for careers for those who complete a master’s degree in data science. These individuals may work to develop and apply mathematical theory and methods in a number of ways. They may use these methods to gather and organize data, interpret that information, and then summarize it (all with a mathematical focus). This information may be beneficial in a number of fields, including economics, business statistics, agricultural statistics, biostatistics, and other areas.

Those who work as a statistician may analyze and interpret data to identify changes and differences in the relationships between data sources. They may also conduct research and create solutions for problems within organizations when found. They may determine whether various methods are fitting, check for inaccuracies, process information, and adjust for raw data. Other could work activities may include interacting with computers to manage all aspects of the data process, analyzing that data, getting information from relevant sources, and interpreting the meaning of that data.

This may lead to the evaluation of technical data to determine plans or designs. They may also work to evaluate data quality and prepare for data analysts.

As a result, those working in this field typically need to have strong mathematical, critical thinking and reading comprehensions skills. They also may need to have analytic and scientific software experience, data mining software experience, and some level of experience with presentation software.

Those working in this field may require a graduate degree. They may also need extensive experience and skill in these fields, often five or more years to obtain a position in some situations. There may be limited access to on-the-job learning.

• Mathematics — Using mathematics to solve problems.
• Critical Thinking — Using logic and reasoning to identify the strengths and weaknesses of alternative solutions, conclusions, or approaches to problems.
• Reading Comprehension — Understanding written sentences and paragraphs in work-related documents.

Median Salary for Statisticians

The following is a list of the median annual salary in 2023 for those working as statisticians as provided by Bureau of Labor Statistics (BLS).

Is database architect a good career?

The job of a database architect often includes designing strategies for data warehouse systems, enterprise databases, and various networks. Those in this field may also set standards for database operations, security, query processes, and programming. Their work often includes modeling and designing large relational databases for various industry needs.

Some of the tasks completed by a database architect could include designing databases to support specific needs such as reliability, performance, security, and business needs. They may also work with system architects and design analysts to meet industry requirements. They may also develop architectural strategies during the modeling phase and implementation stages. They may also set up database clusters and backup solutions.

A number of key skills are often needed in this field as a result. That often includes software skills in areas such as metadata management, data base user interface and query, and data base management. It may also include web platform development experience. Other core skills could include critical thinking, judgment and reasoning, complex problem solving, and active listening, all of which contribute to the skills on the job.

• Critical Thinking — Using logic and reasoning to identify the strengths and weaknesses of alternative solutions, conclusions, or approaches to problems.
• Judgment and Decision Making — Considering the relative costs and benefits of potential actions to choose the most appropriate one.
• Reading Comprehension — Understanding written sentences and paragraphs in work-related documents.

Some of the activities completed here may include creating databases to store all types of electronic data, designing computer modeling and simulation programs, and working with others to design specifications or details. They may also interact with computers for most of the day, process information, and make decisions to handle problems as they occur.

Those working as a database architect may need to have at least a bachelor’s degree, though some employers may require a master’s degree for the higher level of skill training it may provide. Much of the skill based education here often comes from formal classes rather than on-the-job training. These occupations may require individuals to have 5 or more years of experience as well.

Median Salary for Database Architects

Take a closer look at the median annual salary for those working as a database architect in 2023 according to BLS.