


Offered by the University of Colorado Boulder
30 courses total (30 credit hours) full or part-time, 4–6 hours per week per course
Each time you take a course, pay tuition for that course only ($525/credit hour)
Start learning and show us you’re ready, regardless of your background
Lecture videos, hands-on projects, and connection with instructors and peers
Position yourself at the intersection of computer science, statistics, and business applications with the Master of Science in Data Science (MS-DS). This degree is ideal for learners who want to do more than build models; it prepares you to translate data into strategic insights and drive real-world impact.
Uniquely co-taught across five university departments, this program trains you to be the crucial translator between technical teams and business leaders. You will learn to build predictive models, design experiments, and, most importantly, interpret and communicate your findings to shape organizational decisions. This interdisciplinary approach ensures you're prepared not just for a technical role, but for analytics leadership.
Program admission is performance-based, determined by your success in three preliminary courses, not your academic history, making a career in the high-growth field of data science accessible. You’ll graduate from a top-ranked global university, prepared for essential roles like Data Scientist, Business Intelligence Analyst, or Analytics Manager.
为确保顺利开始,请开始注册并预留两周时间完成注册。
敬请关注!
立即开始注册或索取更多信息。
为确保顺利开始,请在两周内完成注册。
Offered by the University of Colorado Boulder
30 courses total (30 credit hours) full or part-time, 4–6 hours per week per course
Each time you take a course, pay tuition for that course only ($525/credit hour)
Start learning and show us you’re ready, regardless of your background
Lecture videos, hands-on projects, and connection with instructors and peers
Offered by the University of Colorado Boulder
30 courses total (30 credit hours) full or part-time, 4–6 hours per week per course
Each time you take a course, pay tuition for that course only ($525/credit hour)
Start learning and show us you’re ready, regardless of your background
Lecture videos, hands-on projects, and connection with instructors and peers
Position yourself at the intersection of computer science, statistics, and business applications with the Master of Science in Data Science (MS-DS). This degree is ideal for learners who want to do more than build models; it prepares you to translate data into strategic insights and drive real-world impact.
Uniquely co-taught across five university departments, this program trains you to be the crucial translator between technical teams and business leaders. You will learn to build predictive models, design experiments, and, most importantly, interpret and communicate your findings to shape organizational decisions. This interdisciplinary approach ensures you're prepared not just for a technical role, but for analytics leadership.
Program admission is performance-based, determined by your success in three preliminary courses, not your academic history, making a career in the high-growth field of data science accessible. You’ll graduate from a top-ranked global university, prepared for essential roles like Data Scientist, Business Intelligence Analyst, or Analytics Manager.
为确保顺利开始,请开始注册并预留两周时间完成注册。
敬请关注!

Not ready to commit to a full degree? Start with a course. When you complete eligible courses, you may be able to have your learning recognized for credit if you are admitted and enroll in the Master of Science in Data Science. Gain in-demand skills while building towards a degree.
Get started with the following eligible specialization and build your progress toward a future degree.
*Successful application and enrollment are required. Eligibility requirements apply. Each institution determines the number of credits recognized by completing this content that may count towards degree requirements, considering any existing credits you may have. Click on a specific course for more information.


Even if you don’t have a bachelor’s degree or extensive work experience, you can become part of the MS-DS. You’ll never have to apply to gain admission into the program. After passing three for-credit courses in the MS-DS program with grades of 3.0 or higher, you’ll be qualified.

Don’t miss your chance to join the cohort!
当您完成这些课程时,如果您被录取并注册,您所学到的知识可被承认为本学位的学分¹。

必须成功申请并注册。资格要求适用。各院校会根据您现有的学分情况,确定完成本课程后可计入学位要求的学分。单击特定课程了解更多信息。
这些课程是学位课程的一部分。如果您被录取并注册,您已完成的课程可以计入您的学位学习,您的学习进度也可以随之转移。


Get Started in Algorithms for Battery Management
中级 · 专项课程
必须成功申请并注册。资格要求适用。各院校会根据您现有的学分情况,确定完成本课程后可计入学位要求的学分。单击特定课程了解更多信息。
这些课程可让您预览相关学位课程计划中的主题、材料和授课教师,以便您确定该主题或大学是否适合您。

University of Colorado Boulder
Learn Mathematical Foundations for Data Science
中级 · 专项课程
是的,与校内课程相同。 课程结束后,您将获得毕业证书。 这是一个授予数据科学理学硕士的学位,它没有任何"在线" 或"Coursera" 称号。
拥有数据科学学位的毕业生已做好充分准备,可以进入数据架构师、分析师和工程师、机器学习架构师和工程师、商业智能开发人员和统计人员等职业。
根据美国劳工统计局(U.S. Bureau of Labor Statistics)的数据,在 2021 年至 2031 年期间,数据科学家职位的数量预计将增长 36%,是所有职位平均增长率的七倍多。
是。科罗拉多大学博尔德分校的在线 MS-DS 课程通过了高等教育委员会 (HLC) 的全面认证。
无需提交申请。 录取以成绩为基础,这意味着您只需证明自己能胜任工作。
要开始注册,请在注册窗口填写注册表。 如果适用,请注明您希望获得硕士学位,并支付该学期所选课程的学费。 完成三门学分课程,GPA 达到或超过 3.0,您将自动获得硕士学位。
是的,您只需报名参加任何课程,想学多少就学多少。 无需承诺。 您也可以在 Coursera 平台上注册非学分课程,然后支付相关学费升级到学分课程。
您可以随时随地访问 Coursera 平台上的课程资料,包括授课视频、测验和阅读材料。 课程由中大博尔德分校的教师专为在线学习环境设计。
如果课程使用期末考试监考,则考试将由 ProctorU 进行,该监考服务允许您在线完成考试或基于项目的评估。
该计划旨在为上班族提供灵活性。 学生如果每学期选修三门课程,将在两年左右的时间内完成理学硕士-理学博士学位的学习。 每年有六次为期八周的课程。 学位是灵活的。 如果想更快地完成学业,可以在每个学段选修更多的课程;如果喜欢慢节奏,也可以在每个学段选修较少的课程。 请注意,您必须在八年内完成所有课程。
是的。一旦被录取,您就可以访问 Handshake(一个提供所有职业相关信息的综合资源)和 VMock 在线简历审查。 毕业生还可以加入 "永远的水牛 "校友会。
每个学分的学费为 525 美元,全部 30 个学分的硕士学位学费为 15,750 美元。 对于 "现收现付 "学费,您只需在注册时支付下一学期所选课程的学费。
不接受从其他机构转入的学分。
在 Coursera 上,两个或两个以上的中大博尔德学位课程提供交叉列出的课程。 例如,"动态编程、贪婪算法 "既作为 CSCA 5414(MS-CS)课程提供,也作为 DTSA 5503(MS-DS)课程提供。
外部选修课(有时称为 "外部 "选修课)是由 Coursera 上其他中大博尔德学位课程提供的课程。 您可以将从外部选修课程中获得的学分用于完成学位选修要求。 学费因课程而异。 学分有限制,并非所有课程都适用于所有学位课程。 详情和限制条件请参阅您所在专业的学生手册。
以下课程不被视为校外选修课:
例如,"数据挖掘管道 "是一门一学分的交叉课程,可作为 DTSA 5504 和 CSCA 5502 课程使用。 CSCA 5502 不被视为数据科学专业学生的校外选修课,DTSA 5504 不被视为计算机科学专业学生的校外选修课。 这些课程将被视为电气工程和工程管理专业学生的校外选修课,因为它们没有分别与 ECEA 或 EMEA 课程交叉列出。
Don’t miss your chance to join the cohort!