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The BS in Computational Data Science develops strong interdisciplinary skills in mathematics, statistics, computer science, and big data processing. The program teaches how to create algorithms and write code and scripts to solve problems beyond the basic use of existing tools in support of an industrial, enterprise-level big data pipeline. The mix of competencies and experiences required for data science differs significantly from those developed in the individual degree programs in the four areas mentioned above. Students will gain real-world experience as a springboard to working in industry as a data scientist or to pursue a graduate degree.
Total Program Credits: 121
General Education Requirements: | 35 Credits | ||
ENGL 1010 | Introduction to Academic Writing | 3 | |
or | ENGH 1005 | Literacies and Composition Across Contexts (5) | |
ENGL 2010 | Intermediate Writing Academic Writing and Research | 3 | |
MATH 1210 | Calculus I | 4 | |
American Institutions: Complete one of the following: | 3 | ||
HIST 1700 | American Civilization (3) | ||
HIST 1740 | US Economic History (3) | ||
HIST 2700 | US History to 1877 (3) | ||
and | HIST 2710 | US History since 1877 (3) | |
POLS 1000 | American Heritage (3) | ||
POLS 1100 | American National Government (3) | ||
Complete the following: | |||
PHIL 2050 | Ethics and Values | 3 | |
HLTH 1100 | Personal Health and Wellness (2) | ||
or | EXSC 1097 | Fitness for Life | 2 |
Distribution Courses: | |||
COMM 1020 | Public Speaking * | 3 | |
COMM 2110 | Interpersonal Communication * | 3 | |
Biology (choose from list) | 3 | ||
Fine Arts Distribution (choose from list) | 3 | ||
PHYS 2210 | Physics for Scientists and Engineers I * | 4 | |
and | PHYS 2215 | Physics for Scientists and Engineers I Lab* | 1 |
Discipline Requirements: | 74 Credits | ||
Complete one of the following GE course/lab combinations: | 5 | ||
BIOL 1610 | College Biology I (4) | ||
and | BIOL 1615 | College Biology I Laboratory (1) | |
or | CHEM 1210 | Principles of Chemistry I (4) | |
and | CHEM 1215 | Principles of Chemistry I Laboratory (1) | |
or | PHYS 2020 | College Physics II (4) | |
and | PHYS 2025 | College Physics II Lab (1) | |
or | PHYS 2220 | Physics for Scientists and Engineers II (4) | |
and | PHYS 2225 | Physics for Scientists and Engineers II Lab (1) | |
Minimum grade of C- required in these courses. | |||
Computer Science | |||
CS 1400 | Fundamentals of Programming | 3 | |
CS 1410 | Object-Oriented Programming | 3 | |
CS 2300 | Discrete Mathematical Structures I | 3 | |
CS 2420 | Introduction to Algorithms and Data Structures | 3 | |
CS 2700 | Causal Inference | 3 | |
CS 305G | Global Social and Ethical Issues in Computing | 3 | |
CS 3100 | Data Privacy and Security | 3 | |
CS 3270 | Python Software Development | 3 | |
CS 3320 | Numerical Software Development | 3 | |
CS 3520 | Database Theory | 3 | |
CS 3530 | Data Management For Data Sciences | 3 | |
CS 3800 | Data Science Through Statistical Reasoning | 3 | |
CS 3810 | Applied Data Science | 3 | |
CS 3820 | Visualization Analytics for Data Science | 3 | |
CS 4700 | Machine Learning I | 3 | |
CS 4710 | Machine Learning II | 3 | |
CS 4800 | Data Science Capstone | 3 | |
Mathematics | |||
MATH 1220 | Calculus II | 4 | |
MATH 2210 | Calculus III | 4 | |
MATH 2270 | Linear Algebra | 3 | |
Statistics | |||
ECE 3710 | Applied Probability and Statistics for Engineers and Scientists | 3 | |
STAT 2050 | Introduction to Statistical Methods | 4 | |
Elective Requirements: | 12 Credits | ||
Complete 12 credits from any of the following (A minimum grade of C- is required): | 12 | ||
4 courses from another discipline, at least 6 hours of which must be 3000 level or higher. Requires department head approval. | |||
Any CS 3000 or 4000 level course not already required |
Graduation Requirements:
This graduation plan is a sample plan and is intended to be a guide. Your specific plan may differ based on your Math and English placement and/or transfer credits applied. You are encouraged to meet with an advisor and set up an individualized graduation plan in Wolverine Track.
Milestone courses (pre-requisites for a course in one of the subsequent semesters) are marked in red and Italicized.
Semester 1 | Course Title | Credit Hours |
CS 1400 | Fundamentals of Programming | 3 |
ENGL 1010 or ENGH 1005 |
Introduction to Academic Writing or Literacies and Composition Across Contexts |
3 |
MATH 1210 | Calculus I | 4 |
STAT 2050 | Introduction to Statistical Methods | 4 |
Semester total: | 14 | |
Semester 2 | Course Title | Credit Hours |
CS 1410 | Object-Oriented Programming | 3 |
ENGL 2010 | Intermediate Writing Academic Writing and Research | 3 |
MATH 1220 | Calculus II | 4 |
PHYS 2210 | Physics for Scientists and Engineers I | 4 |
PHYS 2215 | Physics for Scientists and Engineers I Lab | 1 |
Semester total: | 15 | |
Semester 3 | Course Title | Credit Hours |
CS 2300 | Discrete Mathematical Structures I | 3 |
CS 2420 | Introduction to Algorithms and Data Structures | 3 |
MATH 2210 | Calculus III | 4 |
GE | Choose from American Institutions distribution list | 3 |
GE | Choose from Biology Distribution list | 3 |
Semester total: | 16 | |
Semester 4 | Course Title | Credit Hours |
CS 3520 | Database Theory | 3 |
MATH 2270 | Linear Algebra | 3 |
CS 2700 | Causal Inference | 3 |
GE | Choose from HLTH 1100 or EXSC 1097 | 2 |
GE | Third Science Distribution | 5 |
Semester total: | 16 | |
Semester 5 | Course Title | Credit Hours |
CS 3530 | Data Management for Data Sciences | 3 |
CS 3270 |
Python Software Development | 3 |
ECE 3710 | Applied Probability and Statistics for Engineers and Scientists | 3 |
COMM 2110 | Interpersonal Communication | 3 |
CDS Elective | 3 | |
Semester total: | 15 | |
Semester 6 | Course Title | Credit Hours |
CS 3800 | Data Science Through Statistical Reasoning | 3 |
CS 3320 | Numerical Software Development | 3 |
CS 3820 | Visualization Analytics for Data Science | 3 |
GE | Choose from Fine Arts Distribution list | 3 |
CDS Elective | 3 | |
Semester total: | 15 | |
Semester 7 | Course Title | Credit Hours |
CS 3810 | Applied Data Science | 3 |
CS 4700 | Machine Learning I | 3 |
CS 3100 | Data Privacy and Security | 3 |
PHIL 2050 or PHIL 205G | Ethics and Values | 3 |
CDS Elective | 3 | |
Semester total: | 15 | |
Semester 8 | Course Title | Credit Hours |
CS 4800 | Data Science Capstone | 3 |
CS 4710 | Machine Learning II | 3 |
CS 305G | Global Social and Ethical Issues in Computing | 3 |
COMM 1020 | Public Speaking | 3 |
CDS Elective | 3 | |
Semester total: | 15 | |
Degree total: | 121 |
The Computer Science department is in the Scott M. Smith College of Engineering. To find the most up-to-date information, including Program Learning Outcomes for degree programs offered by the Computer Science department, visit their website.