North Dakota provides high-level infrastructure that enables data science companies to succeed in the state. While many rural areas lack access to broadband, more than 95% of North Dakota’s population has access to broadband services according to the ND Association of Telephone Cooperatives.
- SMU - Master of Science in Data Science - Bachelor's Degree Required.
- Syracuse University - M.S. in Applied Data Science: GRE Waivers available
- UC Berkeley - Master of Information and Data Science Online - Bachelor's Degree Required.
- Syracuse University - Master of Information Management Online
The state has long been home to operations for such major international companies as Microsoft, Amazon, Unisys, and Cargill Global Business Services. North Dakota’s tech scene received prominence when Microsoft acquired Great Plains Software for $1.1 billion in 2001.
Since then Fargo’s tech and startup scene has been burgeoning. In fact, Fortune.com reported that many people undervalue Fargo’s tech scene in a 2015 article. Newer startup companies in Fargo that rely heavily on data science include Intelligent InSites which “is experiencing explosive growth.” This company provides tracking for real-time operational intelligence to healthcare companies. Additional high-tech companies featured in the Fortune.com article in Fargo include Appareo Systems and Botlink.
North Dakota residents who want to learn the skills to take advantage of the opportunities offered in the state have a number of options available through the high-quality online master’s degrees offered by highly reputable educational institutions.
Preparing for a Master’s Degree in Data Science in North Dakota
Students who aspire to become data scientists should start preparing for a master’s degree as they obtain their Bachelor’s of Science degree. Taking the appropriate courses and obtaining relevant work experience will greatly improve their chances of being accepted into a data science master’s program.
Undergraduate Degree and Master’s Prerequisite Courses
Graduate schools with data science programs seek students who have the appropriate training to succeed in their advanced studies. Preparation for graduate school entails:
- Having a minimum GPA of 3.0
- Obtaining a Bachelor’s of Science degree in a quantitative field such as computer science, statistics, applied math, or engineering
- Taking courses in key disciplines such as linear algebra, calculus I and II, statistics, quantitative methods, and programming languages
Relevant Personal and Work Experience for Admissions
Typically, graduate schools choose applicants with highly relevant professional experience:
- Strong communication skills
- Personal experience related to data mining, database administration, coding, hacking, programming, mathematics, or statistics
- At least five years of technical work experience ideally through employment that demonstrates quantitative skills
Examples of qualifying local experience in North Dakota that may satisfy these requirements include:
- Systems Engineer with Microsoft in Fargo
- C++ Mobile Engineer with Botlink in Fargo
- Data Analytics Manager with US Bank in Fargo
- Business Intelligence Report Developer with Sanford Health in Fargo
Since stellar letters of recommendation are crucial to being admitted into a data science master’s programs, prospective graduate students should focus on performing high-quality work.
How to Prepare for the Quantitative Sections of the GRE/GMAT
An excellent way to demonstrate core competency in key data science skills is to score in the top 15th percentile of the GRE and/or GMAT. According to both students who have taken the exams and the testing companies themselves, advance preparation is essential to do well on these exams. Students should take practice tests on sample math problems until they become highly comfortable with them.
The quantitative section of the GRE is particularly important and evaluates the candidate’s skills in data analysis, algebra, geometry, and arithmetic. Candidates seeking a career in data science should pay particular attention to statistics including probabilities and standard deviations. The official GRE website contains sample questions and free practice exams.
The General Management Admissions Test (GMAT) evaluates a candidate’s quantitative, writing, and verbal abilities. While it is important to score well in all of these areas, graduate school admissions departments pay particular attention to the 37 questions that assess problem solving and data efficiency. Candidates can take GMAT practice exams through Veritas Prep and The Princeton Review®.
Closing Gaps in Functional Knowledge through Massive Open Online Courses and Bridge Courses
Massive Open Online Courses (MOOCs) are one way to acquire key skills if a candidate has not been trained in key skills during his or her education or experience. These types of courses are educational programs hosted online designed to supplement the education required to become a data scientist. While many online hosts offer MOOCs, Class Central is a course that is particularly apt for data scientists wishing to supplement their education.
Another way to acquire key skills applying to data science is to take advantage of the bridge programs offered by many graduate programs. Two types of bridge programs are available:
- Fundamental bridge programs – courses in algorithms and their analysis, data structures, and linear algebra
- Programming bridge programs – training in such essential programming languages as JAVA, C++, and Python
Earning a Data Science Master’s Degree in North Dakota
Students in North Dakota who want to obtain a master’s degree in data science have a number of options through high-quality programs available online. North Dakota is especially well suited to this type of study since broadband access is nearly ubiquitous in the state.
These types of programs offer a great deal of flexibility to working professionals, since they are offered in a variety of options. Students who are working have the option of part-time programs that take 32 months. Those who can dedicate themselves to their education full-time can obtain their master’s degree in 18 months or as little as 12 months if they take part in an accelerated program.
While students take their initial courses entirely online, most master’s programs require that students take part in an immersion experience during their final semester. Students take intensive classes on campus and interact with their professors and peers during this final semester.
Degree programs available include:
- Master of Information and Data Science (MSDS)
- Master of Science (MS) in Data Science
- Master of Science in Data Science (MSDS)
- Data Science Certificate
- Data Mining and Application Graduate Certificate
- Graduate Certificate in Data Science
- Online Certificate in Data Science
Core Curriculum Content
Although the coursework will vary in different Master’s programs, the core courses will cover essential skills that data science positions require. All programs will include these topics:
- Data mining
- Machine learning and artificial intelligence
- Data storage and retrieval
- Data research design and applications
- Data research design and applications
- Scaling data – macro and micro
- Statistical sampling
- Experimental statistics
- Applied regression and time series analysis
- Network and data security
- Information visualization
- Quantifying materials
- Advanced managerial economics
- Ethics and law for data science
- Experiments and casual inference
- File organization and database management
Most online data science programs provide an opportunity for their students to apply the training from their courses to real-world problems in an immersion experience. This enables students to work in small teams and spearhead a data science project. These projects often involve working with data that will help a company with its business needs.
Key Competencies and Objectives
Data science master’s programs equip their graduates with a wide array of proficiencies in core areas. This breadth of training will enable these data scientists to work in a number of core areas:
- Data collection and analysis
- Data cleansing
- Data mining and machine learning
- Data and network security
- Database management and file organization
- Statistical sampling
- Research design
- Communication and visualization
- Programming languages such as Python and C++
- Ethics, privacy, and relevant law
Career Opportunities for Data Scientists in North Dakota with Advanced Degrees
The demand for data scientists has skyrocketed as gaining a deeper understanding of the hidden information found in massive data assets has emerged as being essential to remaining competitive in the global marketplace. In its 2011 report, the McKinsey Global Institute estimated that by 2018 the demand for data scientists is expected to be so great that there will not be enough trained professionals to fill available positions.
The number of high-tech jobs in North Dakota increased by 18% between 2007 and 2011 according to a report published by the Bay Area Council Economic Institute commissioned by Engine Advocacy.
The economic climate in Fargo is so favorable that the city is home to the third largest Microsoft campus in the country. As Fargo’s start-up scene matures with the help of incubators, the number of jobs for data scientists is increasing to even higher levels.
For example, the Fargo based company Botlink relies heavily on data science for its work on drone safety and control. This company introduced a piece of data-processing software compatible with every drone commercially available much to the shock of West Coast competitors who had no idea that Fargo was home to such expertise.
Obtaining a master’s degree in data science provides North Dakota residents with the skills to take advantage of the state’s rapidly growing prominence in high technology.