The mathematics program at High Point University seeks to provide courses that will introduce students to the logic and foundations of mathematics so that they will build skills in problem solving and deductive and analytical reasoning. These are the skills that are in demand in many of today’s most sought-after career fields.
Data scientists, data engineers and business analysts are among the most sought-after positions in America. Yet, many existing and emerging workers don’t have the full skillset employers need.
Requirements for data science and analytics jobs are often multidisciplinary and they all require an ability to link analytics to creating value for the organization. The analytics and technology skills vary widely, but candidates must also demonstrate skills related to problem-solving in the workplace, including soft skills such as communication, creativity and teamwork. This holistic skill set is rare, so you should expect to compete fiercely for T-shaped individuals, as they are now often called, meaning those with a principle competency, plus well-honed broad skills to help them cross functions or domains.–PwC
The World Economic Forum released a study in 2018 indicating that by 2022, data analysts and scientists will be the highest job in demand.
So what is data analytics? Data analytics informs fact-based decision making by combining advancements in technology, mathematical and statistical reasoning, and machine learning methodologies to identify patterns and make predictions using large existing data sets.
The ability to collaborate in order to help others find answers to their
questions lies at the heart of data analytics. An effective data analyst not
only has the ability to discover structure within the data but also excels
at communicating ideas and results to audiences with varying levels of
technical knowledge. At HPU, our analytics students take courses in
statistics, mathematics, and computer programming. The data analysis skills
honed in our program will be applicable to any industry.
- In our program, students begin by building a solid foundation in
mathematics and basic statistics. As they progress through the statistics
courses, they learn to apply statistical models to detect patterns in large
data sets and draw inferences accordingly. - Student take courses in both R and SAS programming, both of which are
industry standards in statistics and data analysis. - Our program culminates with a data analytics capstone sequence, in
which students apply what they have learned to a data analysis project
over two semesters. - Students receive one-on-one mentorship from expert faculty.
| Degree Requirements | Credits |
|---|---|
| Major Requirements | 56 |
| University Core Requirements | 36-44 |
| Electives | 28-36 |
| Total | 128 |
| Minor Requirements | Credits |
|---|---|
| Required Courses | 26-28 |
| Total | 26-28 |
| Course | Course Title | Credits |
|---|---|---|
| CSC 1710 | Introduction to Computer Programming | 4 |
| CSC 1720 | Advanced Programming with Data Structures | 4 |
| DSC 2110 | Data Visualization | 4 |
| MTH 1410 | Calculus I | 4 |
| MTH 1420 | Calculus II | 4 |
| MTH 2350 | Math for Data Analytics | 4 |
| MTH 3150 | Probability | 4 |
| STS /CSC 1600 | Introduction to Data | 4 |
| STS 2910 | Introduction to Statistical Analysis | 4 |
| STS 3110 | Intermediate Statistical Analysis | 4 |
| STS 3130 | Data Mining and Predictive Analytics I | 4 |
| STS 3710 | Collaboration in Data Analytics | 2 |
| STS 4210 | Data Mining and Predictive Analytics II | 4 |
| STS 4710 | Data Analytics and Statistics Capstone | 4 |
| Select three courses from the following list (12): | ||
| CSC 2212 | Database Systems | 4 |
| CSC 2710 | Advanced Data Structures | 4 |
| CSC 3250 | Artificial Intelligence | 4 |
| ECO 4150 | Econometrics | 4 |
| MTH/CSC 3910 | Numerical Methods | 4 |
| MTH 4150 | Stochastic Processes | 4 |
| STS 2920 | Introduction to SAS Programming | 4 |
| STS 2950 | Biostatistics | 4 |
| STS 3109 | Nonparametric Statistics | 4 |
| STS 3120 | Applied Multivariate Statistics | 4 |
| STS 3250 | Time Series and Forecasting | 4 |
| STS 3410 | Surveys and Sampling | 4 |
| STS 4120 | Mathematical Statistics | 4 |
| Course Descriptions | ||
Students who complete STS 2910, STS 3110, and STS 3130 with a grade of C or higher will be awarded a joint HPU/SAS Certificate in Data Analytics and Statistics. This certificate will inform future prospective employers that the student has developed marketable statistical and data analytic skills using SAS.
| Course | Course Title | Credits |
|---|---|---|
| MTH 1410 / MTH1310 | Calculus I or Applied Mathematical Concepts for Business | 4 |
| STS/CSC 1600 | Introduction to Data | 4 |
| STS 2910 | Introduction to Statistical Analysis | 4 |
| STS 3110 | Intermediate Statistical Analysis | 4 |
| STS | One STS elective course above STS 2910 | 4 |
| Select one of the following DAS Electives (2-4): | ||
| CSC 1720 | Advanced Programming with Data Structures | 4 |
| CSC 2212 | Database Systems | 4 |
| CSC 2710 | Advanced Data Structures | 4 |
| CSC 3250 | Artificial Intelligence | 4 |
| ECO 4150 | Econometrics | 4 |
| MTH/CSC 3910 | Numerical Methods | 4 |
| MTH 4150 | Stochastic Processes | 4 |
| STS 2920 | Introduction to SAS Programming | 4 |
| STS 2950 | Biostatistics | 4 |
| STS 3109 | Nonparametric Statistics | 4 |
| STS 3120 | Applied Multivariate Statistics | 4 |
| STS 3130 | Data Mining and Predictive Analytics | 4 |
| STS 3250 | Time Series and Forecasting | 4 |
| STS 3410 | Surveys and Sampling | 4 |
| STS 3710 | Collaboration in Data Analytics | 2 |
| STS 4120 | Mathematical Statistics | 4 |
| STS 4210 | Data Mining and Predictive Analytics II | 4 |
| DAS | One DAS Elective Course | 4 |
| Course Descriptions | ||
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