“It has become commonplace to refer to data as the ‘new oil’ of the global economy. Data scientists are the talent that provide the ability to extract, refine, and deploy this new source of value in the global economy” (World Economic Forum, July 2019, p. 4).
Kettering University Online has a well-earned reputation for providing educational opportunities coupling theory and practice in effective and meaningful ways. The new MS Data Science program is no exception. This cutting-edge program affords you the opportunity to build a well-rounded skill set by blending technical capability, quantitative knowledge, and the communication skills that will distinguish you in the job market as a data science professional and leader.
Data science, and the models data scientists offer, inform every corner of our reality, from our physical health, to the volatility of the stock market, to the unpredictability of the housing market. Leaders in government, non-profit organizations, and Fortune 500 companies rely heavily on the models data scientists offer to make the decisions shaping the world in which we live.
Data scientists combine their advanced skills in math, data, and computer science to perform complex functions, manage large-scale information, and solve complex data-oriented problems. In addition to technical and scientific skills, data scientists must have the capacity to think strategically, communicate effectively, and work from an ethical perspective in order to succeed in today’s data driven world. “It is important for a data scientist to be a tactical business consultant. Working so closely with data, data scientists are positioned to learn from data in ways no one else can; that creates the responsibility to translate observations to shared knowledge, and contribute to strategy on how to solve core business problems. This means a core competency of data science is using data to cogently tell a story. No data-puking – rather, present a cohesive narrative of problem and solution, using data insights as supporting pillars, that lead to guidance” (Lo, 2020, para. 16).
Data Science Program Themes
The fusion of statistical and data management, computing technologies including data mining, machine learning, cloud computing, and visualization, is apparent in the program’s course content. Designed by industry experts and accomplished academicians, the Data Science program contains four overarching themes, weaved through all courses, enveloping a variety of objectives for learners:
1. Identify, Manage, and Communicate
- Demonstrate ability to frame data science tasks in the context of organizational or project goals, manage and maintain large datasets, and effectively communicate data science concepts, results and visualizations
- Demonstrate ability to compose for common data science genres as well as facilitate the visualization, exploration, discussion, and action on data science findings
- Develop strategies to determine how data should be managed and applied
- Demonstrate ability to collect, clean, and prepare data as well as evaluate the data in terms of source, volume, frequency, and flow
- Use design principles and best practices for data visualization – matching visuals to purpose, audience, and context
- Blend visual, written, and verbal communication to relate data concepts to a diverse group of stakeholders, including incorporating visuals into text and presenting your data
2. Apply and Evaluate Statistical Methods
- Demonstrate ability to identify and classify variables, choose and apply appropriate quantitative models to solve data science tasks, and assess models used to solve data science tasks
- Be able to extract information and access findings and limitations of data science analysis
- Identify specific, discrete, and continuous probability models
- Use random variables, calculate probabilities, moments, and moment generating functions
- Apply transformations to random variables and identify resulting probability distributions
- Apply specific probability models to practical problems of science and engineering
- Examine machine learning concepts such as supervised learning, learning theory, unsupervised learning, and reinforcement learning and control
3. Employ Powerful Computing Technologies
- Solve complex problems using powerful methods and technologies that unlock solutions hidden in data
- Gain experience using industry software, languages, and tools, such as Python, R, MATLAB, SQL, XML, PHP, and Hadoop
- Develop knowledge in cloud infrastructure services (storage, compute, cloud brokers, etc.), and strategies for Infrastructure as a Service (IaaS), vendor solutions such as Amazon, HP, Microsoft, IMB, Oracle, and VerizonSearch
- Evaluate large-scale data storage and Software as a Service (SaaS) vendor solutions, such as real-time analytics and cloud-based data science applications
4. Evolve as a Leader
- Build well-rounded knowledge and professional skills to pursue leadership roles in data science
- Demonstrate the leadership and management skills to direct a team of data science professionals toward meeting project goals
- Integrate data science capabilities into the formation of a business plan and explain how data assets can be used to develop a competitive advantage
- Identify and analyze social, legal, and ethical issues regarding the collection, use, and communication of data
- Apply your knowledge to a final project in order to solve a real-world data science problem
All courses in the MS Data Science program reflect Kettering University Online’s “Learn Today-Use Tomorrow” approach to graduate programs. This approach encourages students to use their current work challenges in the classroom thereby strengthening the links between transformative experiential learning, rigorous academic standards, and real-world applications. The following courses include carefully curated learning resources, robust discussion questions, and academically rigorous assignments:
- CS 541: Foundations of Data Science
- COMM 601: Communicating Data
- MATH 637: Statistical Inference and Modeling
- CS 565: Data Mining and Information Retrieval
- CS 651: Cloud Computing: Architecture and Applications
- CS 661: Database Systems
- CS 682: Machine Learning
- CS 691: Special Topics in Data Science
- CS 690: Capstone Project in Data Science
Leaders in every industry need professionals who understand how to develop, find, model, and manage the data that informs their decision-making and influences their organization. As such, data science careers have a very desirable outlook and provide many graduates with promotions and salary increases. Following are examples of occupations and median salaries for various jobs in the data science industry (Robert Half, 2020).
- Data Engineer- creates and manages data infrastructure and tools, including collecting, storing, processing, and analyzing data and data systems, median salary $163,250
- Artificial Intelligence (AI) Architect – creates and maintains architecture using leading AI technology frameworks, median salary $143,750
- Data Architect – builds and maintains a company’s database by identifying structural and installation schedules, median salary $141,250
- Data Modeler – creates data models optimized across different data domains and for a variety of purposes, median salary $125,250
More Program Highlights
- 100% online – ideal for working professionals
- Complete in as few as 24 months
- Four intakes per year (fall, winter, spring, summer)
- Accredited by the Higher Learning Commission and a member of the North Central Association of Colleges and Schools
Kettering University Online’s Data Science program is for those possessing strong mathematical and statistical skills, a computer science background, related work experience, and the motivation to drive their career forward with advanced expertise in data science. If you are ready to drive innovation with the science of information by learning how to change the world through data science solutions, enrolling in this program is your next step. Contact one of our dedicated Enrollment Advisors at 1-855-418-0201 for more information about admission requirements, tuition, and course descriptions.
Robert Half. (2020). Technology salary data and hiring trends.
Lo, F. (2020). What is data science? Data Jobs.
World Economic Forum (2019, July). Data science in the new economy: A new race for talent in the Fourth Industrial Reunion.