- Overview
- Learning Outcomes
- Requirements
- Curriculum Details
Program Purpose
The Bachelor of Science in Data Science program seeks to provide students with a solid foundation in data analysis and data management methods and skills, as well as experience in the practical applications of data science to prepare students for careers or advanced studies in data analysis or a related field.
Educational Objectives
The Bachelor of Science in Data Science program aims to:
- Provide students with a solid foundation in the theories and methods of mathematics and statistics, computer science principles relating to data representation, retrieval, and programming, key technologies in data science, as well as the effective use of data analysis tools to practical applications.
- Equip students with hands-on experience and professional skills in practical data analysis, problem solving, and data driven decision-making.
- Enable students to develop critical thinking and communication skills, along with a sense of teamwork, professional attitudes, and ethical judgment.
Faculty
Program Learning Outcomes
After completing the program, students should:
1. Demonstrate command of key concepts, methods, theories and application in the core areas of data science: data mining and statistical analysis, inferential and predictive modeling, programming and data management.
2. Demonstrate proficiency with statistical analysis of data, develop the ability to build and assess data-based models, and execute statistical analyses with professional statistical software; develop relevant programming abilities and skills in data management.
3. Apply skills and knowledge in a collaborative and professional setting through projects, practical and internships experiences.
4. Identify social, legal, and ethical issues in data science and apply a professional code of ethics relevant to the data science profession.
5. Demonstrate a capacity for critical thinking and communicating complex statistical methods to managers and other audiences.
Admission Requirements
- Applicants entering as freshmen should have one of the following:
- minimum score of 670 on the Math section of the SAT,
- a 29 on the Math section of the ACT.
- a score of 3 or higher in AP Calculus AB or BC exams,
- a grade of “C” or higher in a 3-credit-hour (or more) Calculus I course from an accredited US college for any student to be admitted.
- Transfer students should have a minimum cumulative GPA of 2.3.
Graduation Requirement
- The academic requirements for graduation are the successful completion of the curriculum with a grade point average of no less than 2.0.
- In addition, a graduate must have taken at least 50% of all courses from FTC Northern.
- Students must also complete at least 42 courses designated as “LAS” or Liberal Arts and Science in accordance with New York State regulations.
Curriculum Overview
The BS in Data Science is a 120-semester credit curriculum with three major components: major requirements, core general education courses, and free electives.
BS in Data Science Curriculum
| Area | Credits |
|---|---|
| Major Requirements | 65 |
| Mathematics and Statistics | 21 |
| Computer Science | 19 |
| Senior Synthesis and Career Development | 9 |
| Major Electives | 16 |
| General Education Requirements | 42 |
| Humanities | 6 |
| Art and Aesthetics | 5 |
| Values and Ethics | 3 |
| Writing and Rhetoric | 9 |
| Quantitative Reasoning (fulfilled by major requirements) | 0 |
| Natural Sciences | 4 |
| Social Sciences | 6 |
| World Languages | 6 |
| Personal Management | 3 |
| Free Electives | 13 |
| Total Required Credits forGraduation | 120 |
Curriculum Details
Major Requirements(65 credits)
The major requirements are comprised of fundamental courses in mathematics and statistics (21 credits), computer science (19 credits), courses that enable students to develop professional working ethics, experience and insights (9 credits), as well as major electives (16 credits).
| Code | Course Title | Credits | Prerequisite(s) |
|---|---|---|---|
| Major Core (49 cr) | |||
| Mathematics and Statistics (21 cr) | |||
| MAT105 | Calculus I | 4 | None |
| DAS101 | Introduction to Data Science | 3 | COS102 |
| MAT201 | Linear Algebra | 4 | None |
| COS211 | Probability for Computer Science | 4 | MAT105, COS102 |
| DAS241 | Data Visualization | 3 | COS102, STA101 or COS211 |
| DAS251 | Data Inference | 3 | COS102, COS211 |
| Computer Science (19 cr) | |||
| COS102 | Introduction to Computer Programming | 3 | None |
| COS205 | Data Structures | 4 | COS102 |
| COS321 | Database Systems | 4 | COS205 |
| COS331 | Data Mining | 4 | MAT201, COS211, DAS241 |
| DAS435 | Machine Learning and Artificial Intelligence | 4 | COS331 |
| Senior Synthesis, Career Development and Ethics (9 cr) | |||
| DAS148 | Ethical Topics in Data Science | 1 | None |
| DAS149 | Career Development in Data Science | 1 | None |
| COS431 | Ethics in Computer and Data Science | 3 | None |
| DAS491 | Senior Project | 4 | Permission form |
| Major Electives (16 cr) Select from the following list with at least two courses from 300 or 400 level | |||
| Data Science Electives (at least 8 cr required) | |||
| STA101 | Introduction to Statistics | 3 | None |
| COS105 | Object-Oriented Programming | 4 | COS102 |
| MAT106 | Calculus II | 4 | MAT105 |
| COS141 | Essentials for Software Development in Data Science | 1 | None |
| COS224 | Web Programming: Front-End | 3 | COS102 |
| COS225 | Web Programming: Back-End | 3 | COS102 |
| COS243 | Prompt Engineering and Application of Generative AI | 3 | COS102 |
| STA311 | Applied Regression Analysis | 3 | STA101 or COS211, MAT201 |
| DAS341 | Business Data Analysis | 3 | STA101 or COS211 |
| COS346 | Big Data Engineering | 3 | COS205, COS321 |
| DAS361 | Data Science Internship I | 3 | Permission form |
| DAS362 | Data Science Internship II | 1 | DAS361 |
| STA421 | Design and Analysis of Experiments | 3 | DAS251 |
| STA441 | Survival Analysis | 3 | DAS251 |
| DAS452 | Independent Study for Data Science | 2 | Permission form |
| Computer Science Electives | |||
| COS151 | Introduction to Information Technology | 3 | None |
| COS153 | Networking Technologies and Telecommunications | 3 | COS151 |
| COS161 | Introduction to Cybersecurity | 3 | None |
| COS203 | Discrete Mathematics and Probability Theory | 4 | COS102 |
| COS213 | Computer Architecture | 4 | COS205 |
| COS251 | Linux Systems and Network Administration | 3 | COS153 |
| COS253 | Routing and Switching Essentials | 3 | COS153 |
| COS261 | Cybercrime and Governance | 3 | COS161 |
| COS263 | Network and System Security | 3 | None |
| COS305 | Algorithm Design & Analysis | 4 | COS203, COS205 |
| COS351 | Wireless Technology | 3 | COS253 |
| COS353 | Introduction to Cloud Computing | 3 | COS102 |
| COS361 | Wireless and Mobile Security | 3 | COS263 |
| COS363 | Cyber Forensics | 3 | COS261 |
| COS403 | Computer Operating Systems | 4 | COS213 |
| COS425 | Software Engineering | 4 | COS105, COS213 |
| COS435 | Cryptography | 3 | COS203 |
| COS461 | Ethical Hacking | 3 | COS363 |
| Total Credits Required for Graduation | 65 | ||
General Education Core (42 credits)
Northern requires that all undergraduate students, regardless of major, complete core general education courses in nine distributions. The Gen Ed requirements for Data Science students are 42 credits.
| Code | Course Title | Credits | Prerequisite(s) |
|---|---|---|---|
| Humanities (6 cr) Select two from the following | |||
| HUM101 | Introduction to Humanities | 3 | None1 |
| CIV111 | Western Civilization | 3 | None1 |
| CIV112 | Chinese Civilization | 3 | CLC112 or instructor approval |
| CIV113 | World Civilization | 3 | None1 |
| HIS231 | Topics in Chinese History | 3 | CIV112 |
| HUM231 | Western Religious Study | 3 | None1 |
| Writing and Rhetoric (9 cr) | |||
| ENG101 | English Composition I | 3 | None |
| Select one from the following (3 cr) | |||
| ENG102 | English Composition II | 3 | ENG101 |
| ENG201 | Academic Writing | 3 | ENG101 |
| ENG205 | Writing for Media | 3 | ENG101 |
| Select one from the following (3 cr) | |||
| ENG231 | Survey of Western Literature | 3 | ENG101 |
| ENG104 | Public Speaking | 3 | None |
| ENG221 | Debate and Argumentation | 3 | ENG101 |
| Quantitative Reasoning (0 cr) Fulfilled by major requirements | |||
| Social Sciences (6 cr) Select two from the following | |||
| ECO101 | Principles of Economics | 3 | None |
| PSY101 | Introduction to Psychology | 3 | None |
| SOC101 | Introduction to Sociology | 3 | None |
| POL101 | Introduction to Political Science | 3 | None |
| POL201 | The U. S. Constitution | 3 | None |
| POL102 | US Society and Government | 3 | None |
| Natural Sciences (4 cr) Select one sequence from the following | |||
| PHY101 | General Physics I | 3 | Co-requisite with PHY101L |
| PHY101L | General Physics I Lab | 1 | Co-requisite with PHY101 |
| CHM100 | Principles of Chemistry | 3 | Co-requisite with CHM101L |
| CHM100L | Principles of Chemistry Lab | 1 | Co-requisite with CHM101 |
| BSC100 | Principles of Biology | 3 | Co-requisite with BSC101L |
| BSC100L | Principles of Biology Lab | 1 | Co-requisite with BSC101 |
| Art and Aesthetics (5 cr) Select at least 5 credits from the following | |||
| ARH131 | History of Graphic Design | 3 | None |
| DAN242 | History of Dance: East and West | 2 | None |
| MUS204 | History of Music | 3 | None |
| MUS243 | History of Chinese Music | 3 | None |
| ARH211 | History of Cinema and Video | 2 | ARH131 or instructor approval |
| ARH101 | Art History I | 3 | None1 |
| ARH102 | Art History II | 3 | None1 |
| ARH111 | Visual Literacy I | 2 | None |
| MUS111A | Western Music Theory A | 2 | Instructor approval |
| MUS111B | Western Music Theory B | 2 | MUS111A |
| Values and Ethics (3 cr) | |||
| PHL130 | Philosophical Perspectives I | 1 | None |
| PHL131 | Philosophical Perspectives II | 1 | None |
| PHL231 | Philosophical Perspectives III | 1 | PHL130 and 131 |
| World Languages (6 cr）Select one sequence from the following | |||
| CLC111 | Elementary Chinese I | 3 | Placement test |
| CLC112 | Elementary Chinese II | 3 | CLC111 |
| CLC211 | Intermediate Chinese I | 3 | Placement test |
| CLC212 | Intermediate Chinese II | 3 | CLC211 |
| CLC311 | Advanced Chinese I | 3 | Placement test |
| CLC312 | Advanced Chinese II | 3 | CLC311 |
| SPN101 | Elementary Spanish I | 3 | None |
| SPN102 | Elementary Spanish II | 3 | None |
| Personal Management (3 cr) Select at least 3 credits from the following | |||
| LAS101 | College Success2 | 1 | None |
| LAS102 | Career Development3 | 1 | None |
| LAS103 | Cultivation Practice | 0 | None |
| PSY100 | Happiness – Positive Psychology | 1 | None |
| HSC130 | Nutrition, Health and Wellness | 2 | None |
| PEW101 | Wellness through Dance | 1 | None |
| PEW102 | Wellness through Pilates | 1 | None |
| Total Credits Required for Graduation | 42 | ||
1 Theses courses require either the student’s Evidence-Based Reading and Writing section of SAT score is above 570 or the student passes FTC Northern’s English placement test unless the student receives consent from both his/her advisor and the course instructor.
2 Required for freshmen students.
3. Required for all undergraduates.
Free Electives (13 credits)
Students are free to choose 13 credits beyond major and Generation Education requirements from any university level courses offered by FTC Northern.
