Idaho is one of several U.S. states at the forefront of the big data boom. According to a 2014 report published by the University of Idaho, the state is “leading the region in applying data to complex issues,” thanks in large part to a number of recent initiatives established by both the state’s public and private sectors.
In April of 2015, the Idaho Department of Commerce partnered with the Idaho National Laboratory (INL) and the Center for Advanced Energy Studies (CAES) to officially form the Idaho Autonomous Systems Center of Excellence – a team designed to support research and development opportunities in Idaho through data-focused technologies. By synthesizing information from massive data assets in areas ranging from agriculture to natural resource management, the Center aims to capitalize on the emerging opportunities in the autonomous systems field, which is expected to become an $89 billion industry in the next 15 years.
In Idaho’s private sector, Boise-based Micron Technology is continuing to push the boundaries of big data’s potential. In November of 2015, the company announced that machine learning processes managed by data scientists allowed them to create a new memory chip called the nonvolatile persistent memory solution (NVDIMM), which allows companies to maximize the use of dynamic random access memory (DRAM). This fascinating development illustrates how data science itself can be used to develop the technologies that help further the advancement of data science in different applications. The invention is just one of several major developments Micron has announced in recent years, making the company a major player in the field of data science.
The common thread running through these government initiatives and technological advancements in the private sector are the master’s-educated data scientists working to improve our understanding of the world through data.
Preparing for a Master’s Degree in Data Science in Idaho
To prepare for a master’s degree program in data science, students would be expected to hold a relevant undergraduate degree, achieve high scores on entrance exams and gain relevant experience that supports proficiency in coding, database administration, hacking and more.
Undergraduate Degree and Master’s Prerequisite Courses
To be considered for admission to a master’s program in data science, applicants would typically be expected to meet the following undergraduate requirements:
- Bachelor’s degree in a relevant quantitative field such as applied math, statistics, computer science, or engineering
- A course load that includes coverage of key disciplines like linear algebra, statistics, calculus I and II, programming languages, and quantitative methods
- Minimum GPA of 3.0
Beyond these core admission standards, programs consider applicant criteria in the following areas:
- GRE and/or GMAT exams
- Prior work experience
- Fundamental concepts
Preparing to Succeed on GRE/GMAT Exams
To earn top consideration for admission to master’s programs in data science, students would typically have to score in the top 15% of the quantitative section of the GRE or GMAT. Many programs also consider strong scores in the Verbal and Writing sections of these exams, which can demonstrate an applicant’s communication skills.
GRE – The Graduate Record Exam (GRE) revised general test quantitative reasoning section evaluates the following:
- Algebraic topics such as functions, linear equations, algebraic expressions, quadratic equations, and graphing
- Arithmetic topics such as integers, roots, exponents, and factorization
- Geometry topics including the properties of triangles, circles, quadrilaterals, polygons, and the Pythagorean theorem
- Data analysis, including topics such as statistics, graphs, Venn diagrams interquartile range, standard deviation, probabilities, permutations, and tables.
To prepare for the GRE, students may take two sample tests by downloading a free program through Educational Testing Service (ETS). Additionally, students may sign up with the Princeton Review to take a practice exam.
GMAT – The quantitative section of the Graduate Management Admissions Test (GMAT) consists of 37 questions that evaluate students’ data analytics skills, particularly in problem solving and data efficiency. To prepare for the GMAT, students may take practice exams through Veritas Prep and the Princeton Review.
Relevant Personal and Work Experience for Admissions
Applicants with strong professional backgrounds, particularly those who have demonstrated strong communication skills and elite quantitative and analytical reasoning abilities, are given top consideration for admission to master’s programs in data science. Schools may consider the following when reviewing applications:
- Database administration proficiency
- Communication skills
- Total relevant work experience (five years is preferred)
- Data mining ability
- Programming proficiency in languages such as JAVA, C++, and Python
- Coding skills
- Hacking skills
Many gain relevant experience while working in Idaho’s tech sector. A few examples of employers and jobs in Idaho that would help develop the proficiencies graduate schools are looking for include:
- Statistical analysis at On Semiconductor Corp
- Cyber security at Saint Alphonsus Regional Medical Center or Eastern Idaho Regional Medical Center
- Data management at Melaleuca, Inc.
Filling Skills Gaps Through MOOCs in Order to Meet Master’s Programs Admission Criteria
Professionals who are interested in pursuing a master’s degree in data science may lack one or more of the minimum qualifications for admission into a graduate program. This is very common and programs are in place specifically designed to fill knowledge/skills gaps, whether in advanced math, statisticis or programming. These professionals would complete bridge programs or massive open online courses (MOOCs) to fulfill their outstanding requirements.
Massive Open Online Courses (MOOCs), which consist of filmed lectures, problem sets, and student-professor communication, provide students with the opportunity to fill gaps in their education through flexible online formats. Just a few examples of relevant MOOCs for data scientists include:
- Data Science and Machine Learning Essentials
- Networks, Crowds and Markets
- Text Mining and Analytics
Data Science Bridge Courses are available as pre-master’s courses for students that have met requirements for enrollment and have been accepted by a graduate school, even though they may lack proficiency in a certain key area. Graduate schools offer these bridge courses in an effort to be more inclusive of highly qualified prospective students that may need just a course or two before being ready for graduate study.
Fundamental Bridge Programs provide coursework in linear algebra, algorithms and analysis of algorithms, and data structures.
Programming Bridge Programs provide coursework in the mandatory programming languages required to begin master’s-level courses.
Earning a Master’s Degree in Data Science in Idaho
By offering both curricular coursework and immersion experiences, master’s programs in data science equip students with the skills sought after by today’s top companies. With part-time and full-time options available, students can set their own pace and earn their degree in 18-30 months. Through accelerated learning formats, students may earn their degree in as little as 12 months.
Examples of master’s degrees in data science include:
- Data Mining and Applications Graduate Certificate
- Data Science Certificate
- Master of Science in Data Science (MSDS)
- Master of Science (MS) in Data Science
- Online Certificate in Data Science
- Graduate Certificate in Data Science
- Master of Information and Data Science (MIDS)
With no specific master’s programs in data science in Idaho, students in the state often apply to accredited online programs to earn degrees such the Master of Science in Data Science (MSDS) or the Master of Information and Data Science (MIDS). The flexibility of these programs allow students to further their education without sacrificing their current career obligations.
Core Curriculum and Immersion
Master’s in data science programs offer diverse courses designed to equip students with relevant, in-demand tools for the professional world. Just some of the courses often found in these programs include:
- Experimental statistics
- Statistical sampling
- Visualization of data
- Ethics and law for data science
- Network and data security
- Applied regression and time series analysis
- Quantifying materials
- Data mining
- Experiments and causal inference
- Data research design and applications
- Machine learning and artificial intelligence
- Data storage and retrieval
- Scaling data – macro and micro
- Information visualization
- Advanced managerial economics
- File organization and database management
An important aspect of data science programs is the immersion experience, which consists of a collaborative project designed to simulate real-world applications of data science. Corporate recruiters often come to observe students during these immersion experiences, providing students with the opportunity to demonstrate their talent in a team-based setting and become professionally established before graduating.
Key Competencies and Objectives
Upon graduating from a master’s program in data science, students should be proficient in the following core competencies:
- Be able to work in teams to achieve specific goals
- Become familiar with hash algorithms, cyphers, and secure communications protocols
- Be able to conduct association mining and cluster analysis
- Learn programming languages such as GitHub, SAS, Python, and Shiny by Rstudio
- Be able to interpret and communicate results
- Develop innovative design and research methods
- Be able to run an analysis of survey data
- Be able to develop and conduct sophisticated data analyses
- Be able to conduct database queries
Career Opportunities in Idaho for Data Scientists with Advanced Degrees
The simultaneous growth of data science in Idaho’s public and private sectors will likely mean increased job opportunities for the state’s master’s-prepared data scientists in the coming years. According to the Idaho Department of Commerce, the solutions and strategies developed by Idaho Autonomous Systems Center of Excellence will play a significant role in shaping Idaho’s economy, impacting industries and services such as:
- Disaster response
- Public safety
- Environmental monitoring
The following job listings were taken from a survey of job vacancy announcements in Idaho performed in February 2016 calling for master’s-prepared data scientists (examples are shown for illustrative purposes only and are not meant to represent job offers or provide any assurance of employment):
Data Scientist at Micron in Boise – The job would consist of driving strategy for data analysis and data warehousing systems across the company, as well as identifying and cleaning existing data sets.
Senior Manager Data Scientist, Machine Learning at Otsuka Pharmaceutical (Remote) – The professional would be expected to create innovative methodologies for data, build proof of concept systems, and establish strategic partnerships with technical leadership across functional areas.