The high speed infrastructure is definitely in place here for data intensive businesses in North Dakota to tap into. More than 95% of the state’s population has access to broadband services according to the ND Association of Telephone Cooperatives, putting North Dakota right at the top of national rankings and giving high tech startups in the state an unexpected advantage.
- Grand Canyon University - B.S. in Business Information Systems and M.S. in Data Science
- SNHU - A.S. in Data Analytics, B.S. in Computer Science, B.S. in Data Analytics, and M.S. in Data Analytics
- 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
It’s no surprise then that in 2020 the state Department of Commerce designated technology-based businesses among the five industries slated for significant growth in the state. More than 3,000 such businesses have a presence here, including ruggedized electronics manufacturer Appareo Systems and drone software company Botlink, which combined, have almost 22,000 high tech employees on the payroll.
Even as the high tech new guard establish themselves in the state, they’re able to follow in the footsteps of trails blazed and infrastructure laid by such tech juggernauts as Microsoft, Amazon, Unisys, and Cargill Global Business Services, which have long had operations here.
The skills it takes to tap into all the opportunities in North Dakota’s high tech sector can be yours through the high-quality online master’s degrees in data science available to grad students here.
Preparing for a Master’s Degree in Data Science in North Dakota
Anybody looking to become a data scientist here should start preparing for a master’s degree, even as early as when selecting a bachelor’s program. Taking the appropriate courses and obtaining relevant work experience will greatly improve your chances of being accepted into a high quality data science master’s program down the road. Picking an unrelated discipline doesn’t entirely torpedo your chances, but it can make the path to earning a master’s a bit more of a challenge.
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. Competition is fierce and standards are high. Being well prepared for graduate school entails:
- Having a minimum GPA of 3.0
- Obtaining a bachelor’s 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 on top of their education. You need demonstrable practical skills in areas such as:
- Strong communication skills
- Personal experience related to database administration, 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 program, 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’re totally comfortable with the material covered.
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®.
Data Science Bootcamps to Prepare for Your Master’s Program Application or for the Skills You Need to be Job-Ready
Of course, not everyone realizes they want to be a data scientist early enough to make sure they take all the right turns at the bachelor’s level and in their job selections after graduating, which can leave some gaps in your CV when applying to a master’s program.
But you still have an opportunity to jazz that CV up and get the core skills you need, both quickly and inexpensively. The downside is that it will take a lot of hard work, because you’re going to have to do it in a data science bootcamp.
Bootcamps are just as intensive as they sound. The idea is to pack in years worth of study and training into a few weeks or months of hands-on, practical experience working with real-world data and cutting-edge data science tools under the tutelage of experienced instructors in the field. You’ll work with your fellow students on a series of projects that replicate the type of work that you will find actual data scientists performing daily.
Bootcamps were originally in-person and full-time, offered by a variety of private companies, but today you’ll encounter a lot more offerings, including ones that are both online and part-time, like these popular programs available in North Dakota:
- Northwestern Data Science and Visualization Boot Camp
- Rice University Data Analytics Boot Camp
- The Data Analysis and Visualization Boot Camp at Texas McCombs
- University of Minnesota Data Visualization and Analytics Boot Camp
As part-time programs, they are longer than many bootcamps, hitting 24 weeks. But they are also held on evenings and weekends, which allows you to attend even if you are already holding down a job.
And like other entry-level bootcamps, they teach a comprehensive catalog of fundamental skills, including:
- Use of specialized libraries like D3.js, Leaflet.js, and Numpy
- Social media and other data mining techniques
- Machine learning and artificial intelligence
- Advanced statistical analysis
You get the advantages of learning from instructors with solid academic and on-the-job credentials, and all the resources of a major data science department behind them. That includes big-time career development support, including individual coaching on interviews and resume building, and portfolio development and showcasing. It’s the perfect way to build up your skillset for either a master’s program or a job in the industry.
Closing Gaps in Functional Knowledge through Massive Open Online Courses and Bridge Courses
Sometimes, though, you only have a few relatively small holes in your CV that you need to take care of, stuff that’s minor enough that a full-on bootcamp wouldn’t be necessary. In those cases, you can look to MOOCs or bridge programs to help you through.
Massive Open Online Courses (MOOCs) are one way to dive into very specific areas of knowledge if you have not been trained in key data science skills during your education or experience. These types of courses are hosted online and designed to supplement the education required to become a data scientist. With huge classes, you won’t get a lot of individualized attention, but they are excellent for self-starters and the asynchronous schedule allows you to fit them into your busy lifestyle.
Your preferred data science program itself might offer you another option for getting up to speed through a bridge program. These are basically sets of undergraduate courses, usually offered in the summer, that cover essential skills that you may be lacking before you get started on the main program. 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
- Applied regression and time series analysis
- Network and data security
- Information visualization
- Quantifying materials
- 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 equip you for success by developing your talents in a number of important areas in data analysis:
- 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.
That’s made clear by DICE’s 2020 Tech Job Report, which lists Data Engineer and Data Scientist as two out of the three fastest growing tech occupations in the country. Data engineers experienced a tremendous 50 percent year over year growth rate since 2019, with employers listing critical data science skills such as Python, SQL, and Hadoop as among their most important factors for hiring in those positions.
The shortage is boosting salaries along the way. The 2020 Robert Half Salary Report showed, salary levels for starting data scientists in Bismarck to be around $95,000, while individual contributors at the top end of the profession could command $161,500 per year. In Fargo the range was $91,300 at the entry-level, on up to $155,700.
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 a small city in North Dakota could be home to such expertise.
Obtaining a master’s degree in data science provides the skills to get yourself well-positioned during North Dakota’s rapid rise to prominence in high technology, and well-positioned to take advantage of the growing salaries that come with it.