Data Science
The Associate of Science in Data Science degree provides an excellent opportunity for students wanting to increase their data literacy and data acumen, improve their marketability, and/or prepare for a career in a data science field. It is also suitable for those who wish to advance their professional careers by supplementing their work experience or an existing college or graduate degree with data science knowledge.
Students will use mathematics, statistics, and data science skills to tackle unstructured data, solve multifaceted problems, consider ethical implications, and make data-driven recommendations. Through hands-on experiences using a variety of the most ubiquitous data tools and technology, students will learn to build the skills necessary to explore, analyze, visualize, and communicate about large data sets. Additionally, students will explore ethical implications of the use of data in the data lifecycle.
Program Outcomes
-
Assess different analysis and data management techniques and justify the selection of a particular model or technique for a given task.
-
Execute analyses of large and disparate datasets and construct models necessary for these analyses.
-
Demonstrate competency with programming languages and environments for data analysis.
-
Summarize and communicate findings of complex analyses in a concise way for a target audience using both graphics and statistical measures.
-
Understand, evaluate, and apply ethical principles and practices in the data lifecycle.
Program Advising
Meet with your academic advisor regularly to discuss your academic plans and make sure you are on track to graduate and/or transfer. The program advising guide outlines the certificate requirements and is meant to supplement the advising process.
Careers
For some positions listed, a bachelor's degree or higher may be required. Use the Career and Program Explorer to see a full report for this career field. See links below chart for further guidance and/or connect with a Program Advisor to discuss career goals.
Data science is now transforming industries beyond the technology industry, in areas such as health care, energy, and transportation. With benefits of data becoming more numerous and widespread, demand for data science and analytics talent is projected to grow by 15 percent by 2020 (US Bureau of Labor).
- MC Student Employment Services: Speak with the Student Employment Specialist for help with resume writing, interviewing, setting up a College Central Network (CCN)new window account and other job search topics.
- Career Coach: Explore Career Coach to learn more about this career and/or discover related majors and in-demand careers based on your current interests! Take a Career Assessment and then browse careers and job opportunities in the area.
Curriculum
A suggested two-year course sequence for students in Data Science Associate of Science follows
- All students should review the advising guide and consult an advisor.
- Find out about related programs and course in the Fields of Study section.
- Most courses have either assessment levels that must be met or prerequisites (courses that must be taken first). Part-time students and those who need to meet assessment levels or take prerequisite courses will take longer to complete a degree. An advisor will help make sure you are taking your courses in the right order.
- All degree-seeking students must take a central group of General Education courses in English, mathematics, arts, behavioral and social sciences, humanities, and science. These courses are included in the suggested course sequence below.
Suggested Course Sequence
A suggested course sequence for full-time students follows. All students should review the Program Advising Guide and consult an advisor.
First Semester
- ENGL 101 - Introduction to College Writing 3 semester hours
- MATH 181 - Calculus I 4 semester hours (MATF)
- PSYC 102 - General Psychology 3 semester hours (BSSD)
- COMM 108 - Foundations of Human Communication 3 semester hours (GEEL)
-
OR
- COMM 112 - Business and Professional Speech Communication 3 semester hours (GEEL)
- MATH 117 - Elements of Statistics 3 semester hours
-
OR
- MATH 217 - Biostatistics 3 semester hours
Second Semester
- English Foundation 3 semester hours (ENGF)
- PHIL 140 - Introduction to the Study of Ethics 3 semester hours (HUMD)
- GEOG 130 - Global Geography 3 semester hours (BSSD, GCP)
- DATA 101 - Introduction to Data Science 3 semester hours
- DATA 110 - Data Visualization and Communication 3 semester hours
Third Semester
- Natural Sciences Distribution with Lab 4 semester hours (NSLD) **
- DATA 201 - Statistical Methods in Data Science 3 semester hours
- MATH 264 - Applications in Linear Algebra 4 semester hours
- Program Elective 4 semester hours †
Fourth Semester
- Arts Distribution 3 semester hours (ARTD)
- Natural Sciences Distribution with Lab 4 semester hours (NSLD) **
- DATA 205 - Capstone Experience in Data Science 4 semester hours
- 200-Level Program Elective 3 semester hours †
* ENGL 101/ENGL 101A, if needed for ENGL 102/ENGL 103 or program elective.
** Students are strongly encouraged to take two consecutive lab sciences courses. Examples include CHEM 131/CHEM 132, PSCI 101/PSCI 102, PHYS 203/PHYS 204.
‡ MATH 284 may be substituted for MATH 264
† Program Electives: MATH 165, MATH 182, CMSC 140, CMSC 203, CMSC 206, GEOG 240, and GEOG 260. Department strongly recommends CMSC 206 and GEOG 240. CMSC 206 provides programming skills in Python; GEOG 240 provides foundational knowledge of Geographic Information Systems (GIS). Not all program elective options transfer to all institutions. Please consult a data science program advisor or the transfer institution before selecting program elective courses.
Related Programs and Courses
If you choose to pursue a general studies degree in Science, Technology, Engineering and Mathematics (STEM Core), you can explore the Data Science Certificate plus A.A. Degree Option.
MC offers a wide variety of noncredit courses designed to help you upgrade your skills, pursue career training, or learn something new.