Florida Polytechnic University
数据科学理学学士
Lakeland, 美國
理学学士
期间
4 年
语言
英语
步伐
全职
报名截止日期
最早开始日期
学费
USD 105 / per credit *
学习形式
在校园
* 30 个学分的居民和非居民学费
快速通道咨询
通过联系学校，您可以获得有关任何学习和申请问题的免费优先咨询。
数据科学是一个跨学科领域，融合了统计学、计算机科学和商业领域的工具和技术。我们专注于实际应用，为学生提供分析大型数据集和开发数据解决方案的实践经验，以解决医疗保健、交通运输、金融和其他行业的问题。我们严格而灵活的课程、经验丰富的教师以及对海量数据集的访问，使学生具备毕业后从事数据科学工作所需的技能和经验。
数据科学专业
高级主题
学生与教师顾问合作，制定符合他们兴趣的独特课程。对于不确定自己想学什么或想探索各种科目的学生来说，这是一个很好的选择。学生可以根据自己的学术和职业追求，在专业范围内设计四门课程，这些课程不包含在所提供的课程中。这种独特的课程组合与其他课外活动相辅相成，包括研究经历、实习和我们学生组织中的各种机会。高级主题为学生提供了课程选择的灵活性，使他们能够随着毕业、研究生院和职业努力的兴趣变化而成长。
大数据分析
大数据分析专业的学生将学习收集、管理和优化大规模结构化和非结构化数据集，以促进信息和决策。大数据分析专业的学生将为基本编程技能、定量分析以及硬件和软件解决方案打下坚实的基础，从而促进大数据的有效利用。
智能移动和自主系统
智能移动和自主系统利用数据和技术连接所有交通方式中的人员、地点和货物。智能移动的发展将改变人们的出行方式、与环境的互动方式以及连接货物和服务的方式。
数量经济学和计量经济学
数量经济学和计量经济学侧重于定量分析和对经济现象进行严格的建模。这包括在数据混乱、不完整或不完善的情况下对个人和公司决策的分析、对战略形势的分析以及对市场结果和趋势的分析。数量经济学和计量经济学培训可以磨练批判性推理技能，并为学生从事分析职业或研究生或专业学习做好准备。
我们提供丰厚的基于需求和成绩的奖学金，并参与全州范围的大学资助计划，如“佛罗里达光明未来”和“佛罗里达预付”。
机构奖学金
- 亚历山大学者
- 教务长学者
- Florida Poly优秀学者
- 约翰逊奖学金
- 拉丁美洲加勒比奖学金
- Florida Poly国家优秀学生奖学金决赛入围者
州外奖学金
- 第一代配套补助金
- 佛罗里达州学生援助补助金（FSAG）
- 佛罗里达光明未来奖学金
- 何塞·马蒂奖学助学基金
- 玫瑰木家庭奖学金
Core courses include data visualization, data mining, machine learning, statistics, and database systems. Students learn to clean, integrate, and analyze complex data to gain actionable insights and tell data-driven stories. Elective tracks allow students to specialize in fields like Big Data Analytics, Econometrics, or Autonomous Systems. In the final capstone course, students apply their skills to solve a real challenge for a company or nonprofit. Recent projects include optimizing supply chain management for a retailer, identifying risk factors for hospital readmissions, and designing a recommendation system for an online education platform.
College Skills (1) & Co-Curricular
All majors are required to complete an approved internship/professional experience before graduation.
- EGN 1006 - Career Design for STEM Disciplines (Credits: 1)
- IDS 4941 - Professional Experience Internship (Credits: 0)
Communication (6)
- ENC 1101 - English Composition 1: Expository and Argumentative Writing (Credits: 3)
- ENC 2210 - Technical Writing (Credits: 3)
Arts and Humanities (3-6)
Data Science majors select 12 credits from Art and Humanities and Social Sciences. Three to six credits, as noted below, must be taken in Art and Humanities.
- ARH 2000 - Art Appreciation (Credits: 3)
- LIT 2000 - Introduction to Literature (Credits: 3)
- HUM 2020 - Introduction to the Humanities (Credits: 3)
- PHI 2010 - Introduction to Philosophy (Credits: 3)
- MUL 2010 - Music Appreciation (Credits: 3)
Optional to fulfill Arts & Humanities requirement:
- IDS 2144 - Legal, Ethical, and Management Issues in Technology (Credits: 3)
- HUM 2022 - Explorations in the Humanities (Credits: 3)
Social Sciences (6-9)
Six to nine credits, as noted below, must be taken in Social Sciences.
Required state general education core, select one from the following:
- AMH 2020 - American History Since 1877 (Credits: 3)
- ECO 2013 - Principles of Macroeconomics (Credits: 3)
- PSY 2012 - General Psychology (Credits: 3)
- POS 2041 - American Government (Credits: 3)
Program Required
- ECO 2023 - Principles of Microeconomics (Credits: 3)
Mathematics (8)
- MAC 2311 - Analytic Geometry and Calculus 1 (Credits: 4)
- MAC 2312 - Analytic Geometry and Calculus 2 (Credits: 4)
Natural Sciences (12)
Choose one set from the following:
- CHM 2045 - Chemistry 1 (Credits: 3) + CHM 2045L - Chemistry 1 Laboratory (Credits: 1)
- PHY 2048 - Physics 1 (Credits: 3) + PHY 2048L - Physics 1 Laboratory (Credits: 1)
- PHY 2049 - Physics 2 (Credits: 3) + PHY 2049L - Physics 2 Laboratory (Credits: 1)
- EVR 1001 - Environmental Science (Credits: 3) + EVR 1001L - Environmental Science Lab (Credits: 1)
- CHM 2046 - Chemistry 2 (Credits: 3) + CHM 2046L - Chemistry 2 Laboratory (Credits: 1)
Advanced Math and Analytics (12)
- STA 2023 - Statistics 1 (Credits: 3)
- MAD 2104 - Discrete Mathematics (Credits: 3)
- MAS 3114 - Computational Linear Algebra (Credits: 3)
- STA 3036 - Probability and Statistics 2 for Business, Data Science, and Economics (Credits: 3)
Data Science Core (54)
These courses provide an essential foundation in Data Science.
- IDS 1380 - Foundational Lessons in Applications of Mathematics (Credits: 3)
- EGN 1007 - Concepts and Methods for Engineering and Computer Science (Credits: 1)
- COP 2271 - Introduction to Computation and Programming (Credits: 3)
- COP 3337 - Object Oriented Programming (Credits: 3)
- COP 3710 - Database 1 (Credits: 3)
Advanced Courses
- CAP 4770 - Data Mining & Text Mining (Credits: 3)
- EGN 3448 - Operations Research (Credits: 3)
- COP 3530 - Data Structures & Algorithms (Credits: 3)
- COP 2073 - Foundations of Data Analytics (Credits: 3)
- STA 3241 - Statistical Learning (Credits: 3)
- CAP 4612 - Machine Learning (Credits: 3)
- STA 4853 - Time Series Analysis for Business, Data Science, and Economics (Credits: 3)
- CTS 2375 - Cloud Infrastructure and Services (Credits: 3)
- ISC 2310 - Python for Data Analytics (Credits: 3)
- QMB 4690 - Process Design Using Lean Sigma (Credits: 2)
- CAP 4793 - Advanced Data Science (Credits: 3)
- ECO 4422 - Econometrics: Causal Inference, Panel and Survey Data (Credits: 3)
- CAP 4786 - Topics in Big Data Analytics (Credits: 3)
- IDC 3180 - Contemporary Issues and Case Studies in Data Science (Credits: 3)
Application Area (6)
Choose six credits from the list below:
- ECP 3004 - Contemporary Economic Issues (Credits: 3)
- MAR 4705 - Marketing Analytics (Credits: 3)
- ESI 4011 - Data Analytics for Smart City & Transportation (Credits: 3)
- FIN 4501 - Investments, Financial Modeling and Analytics (Credits: 3)
Data Science Electives (3)
Choose three credits from the list below:
- CAI 4304 - Natural Language Processing (Credits: 3)
- CAP 3774 - Data Warehousing (Credits: 3)
- CAP 4410 - Computer Vision (Credits: 3)
- CAP 4630 - Artificial Intelligence (Credits: 3)
- CAP 4613 - Applied Deep Learning (Credits: 3)
- COP 4520 - Introduction to Parallel and Distributed Computing (Credits: 3)
- COP 3729 - Database 2 (Credits: 3)
- CEN 4721 - Human-Computer Interaction (Credits: 3)
- CEN 4033 - Secure Software Engineering (Credits: 3)
- CNT 4403 - Data Security (Credits: 3)
- ECO 4400 - Game Theory and Strategic Decisions (Credits: 3)
- ECP 4031 - Benefit-Cost Analysis (Credits: 3)
- EGS 3625 - Engineering & Technology Project Management (Credits: 3)
- ENT 2112 - Entrepreneurial Opportunity Analysis (Credits: 3)
Program Capstone Sequence (6)
- IDC 4942 - Data Analytics Capstone I (Credits: 3)
- IDC 4943 - Data Analytics Capstone II (Credits: 3)
Graduates from the Data Science Bachelor of Science program will be prepared to:
- Provide effective solutions to complex problems, based on technical knowledge, methods, and practices of the dynamic data science field.
- Serve and work as effective and ethical data science professionals to contribute to their community and society.
- Assume positions of leadership in industry, academia, public service, and entrepreneurship.
Student outcomes describe what students are expected to know and be able to do by the time of graduation. Upon completion of the Data Science program, graduates will have the ability to
- Identify, formulate, and solve broadly-defined technical or scientific problems by applying knowledge of mathematics and science and/or technical topics to areas relevant to the discipline.
- Formulate or design a system, process, procedure, or program to meet desired needs.
- Develop and conduct experiments or test hypotheses, analyze and interpret data, and use scientific judgment to conclude.
- Communicate effectively with a range of audiences.
- Understand ethical and professional responsibilities and the impact of technical and/or scientific solutions in global, economic, environmental, and societal contexts.
- Function effectively on teams that establish goals, plan tasks, meet deadlines, and analyze risk and uncertainty.
数据科学学士学位结合了应用数学、计算机科学、统计学、优化、数据挖掘和机器学习，为您提供广泛且备受期待的技能。您将获得使用 Excel、Python、R、SQL 数据库和 Tableau 等工具的实践经验，并为数据科学领域的新兴职业和未来的高级学习做好准备。
让你的激情成为事业
我们在这里为您提供资源，让您获得梦想的实习机会，与教师一起进行开创性的研究，并培养领导技能，在工作场所脱颖而出。
实习机会
实习是你大学毕业后取得成功的重要组成部分，也是你毕业的必要条件。
研究机会
与教师一起开展研究，改善生活、改变企业，其影响范围从当地的湖区社区到太空边缘。
职业发展
我们理解做好准备的重要性，我们致力于帮助您在职场和未来取得成功。因此，我们拥有资源来支持您持续的职业发展。