Statistics and Data Science

The digital revolution has created vast quantities of data. Extracting knowledge and insight from this avalanche of information is the goal of data science, a rapidly growing field with applications in such areas as marketing, 教育, 和体育, as well as scientific fields such as genomics, 神经科学, 和粒子物理.

职业发展机会

Decision-makers have access to more data than ever before, but deriving meaning and actionable insights from that data requires specialized tools and expertise. For that reason, graduates with degrees in statistics and data science are in high demand.

Currently, there is a global data scientist shortage. It is estimated that within the next two years, there will be twice as many data science jobs as there will be people to fill those roles. This means extensive job opportunities for individuals with the necessary 教育 and skills.

课程

UE’s program in statistics and data science combines state-of-the-art tools and techniques from the field of data science with a mathematically rigorous tradition of classical applied statistics. Students in the program will…

  • Engage through project-driven courses. Data analysis projects offered throughout the curriculum expose students to the entire work cycle of predictive modeling, including problem formulation, acquisition and cleaning of data, model selection and fitting, 解释, 和报告.
  • Master cutting-edge statistical software. Students gain fluency in the statistical software currently in use within business and industry, 包括R, Python, 和BigQuery.
  • Receive a first-class liberal arts 教育. Working with “big data” requires more than quantitative and technological skills—it also requires an ability to frame questions, to bring diverse teams together, to make ethical and informed decisions, and to communicate results to decision-makers. A UE 教育 provides students with broad foundational knowledge in the arts and sciences, as well as the critical thinking and communication skills that employers value.

Details on program requirements and course descriptions can also be found in the 目录.

Additional 信息

  • Sample 4-year Plan Beginning in an Odd Year
    秋天 春天
    大一新生 数学221 ——微积分我 数学222 ——微积分二世
    统计266 – Introductory Statistics with R
    二年级学生 CS 210 ——基金. 我的编程
    统计267 ——实验设计
    数学365 ——概率
    数学341 ——线性代数
    数学466 ——统计
    CS 215 ——基金. 编程的二世
    初级 统计361 ——线性模型
    统计474 – Techniques for Large Data Sets
    Harlaxton
    高级 数学495 – 高级 Seminar: Mathematical Modeling 统计362 ——机器学习
    统计493 – Statistical Modeling

    Note: CS 215* can be replaced by a computer-based course

    Sample 4-year Plan Beginning in an Even Year
    秋天 春天
    大一新生 数学221 ——微积分我 数学222 ——微积分二世
    统计266 – Introductory Statistics with R
    CS 210 ——基金. 我的编程
    二年级学生 统计267 ——实验设计
    数学365 ——概率
    CS 215 ——基金. 编程的二世
    数学341 ——线性代数
    数学466 ——统计
    初级 统计361 ——线性模型 统计362 ——机器学习
    高级 统计474 – Techniques for Large Data Sets
    数学495 – 高级 Seminar: Mathematical Modeling
    统计493 – Statistical Modeling

    Note: CS 215* can be replaced by a computer-based course. Harlaxton: 统计361 can be taking in the fall of the senior year.

  • 统计课程
    统计课程 频率
    统计266 - Introductory Statistics with R 每年春天 2017年春季
    统计267 - Experimental Design 每年在秋天 2017年秋季
    STAT 300 - Data Analysis in Real World 每年在秋天 2018年秋季
    统计361 - Linear Models 每年在秋天 2017年秋季
    统计362 - Machine Learning 每隔一个春天 2018年春季
    统计474 - Techniques for Large Data Sets 每隔一个秋天 2018年秋季
    统计493 - Statistical Modeling 每年春天 2019年春季
    数学与计算机课程 Offerings
    数学与计算机课程 频率
    数学221, 222 - Calculus 秋天, 春天, and Summer
    数学365 - Probability 每年在秋天
    数学466 - Mathematical Statistics 每年春天
    数学341 - Linear Algebra 每年春天
    数学495 - 高级 Seminar: Mathematical Modeling 每年在秋天
    CS 210, 215 - 介绍 to Programming Every 秋天 and 春天
  • Course Dependancy Chart

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