<?xml version="1.0" encoding="UTF-8"?>
<item dsn="programs"
       href="https://dev.farmingdale.edu/curriculum/minor-datascience.shtml">
   <program-title>Data Science Minor</program-title>
   <program-department>Computer Systems</program-department>
   <program-department-building>Whitman Hall</program-department-building>
   <program-department-room>112</program-department-room>
   <program-department-hours>Monday-Friday 8:30am-5:00pm</program-department-hours>
   <program-department-email>cpis@farmingdale.edu</program-department-email>
   <program-department-phone>934-420-2190</program-department-phone>
   <program-chair-name>Dr. David S. Gerstl</program-chair-name>
   <program-overview>
      <p xmlns:ouc="http://omniupdate.com/XSL/Variables">The Data Science minor equips students with the skills to apply mathematical techniques and computer programming to process and analyze large data sets across various fields. This minor is ideal for students from diverse majors who want to enhance their data-driven decision-making abilities, provided they have a solid foundation in mathematics to undertake the required course sequence. </p>
      <h2 xmlns:ouc="http://omniupdate.com/XSL/Variables">Student Learning Outcomes</h2>
      <ul xmlns:ouc="http://omniupdate.com/XSL/Variables">
         <li>Write computer programs to assist in the analysis and visualization of large data sets</li>
         <li>Apply machine learning techniques to data analysis</li>
         <li>Verify that the insights gained from large data sets are statistically significant</li>
      </ul>
   </program-overview>
   <program-semester-year>
      <h3 xmlns:ouc="http://omniupdate.com/XSL/Variables">Fall 2026</h3>
      <p xmlns:ouc="http://omniupdate.com/XSL/Variables">Subject to revision</p>
   </program-semester-year>
   <program-courses>
      <table xmlns:ouc="http://omniupdate.com/XSL/Variables">
         <tbody>
            <tr>
               <th>Required Courses</th>
               <th>(18 credits)</th>
            </tr>
            <tr>
               <td>Course Name</td>
               <td>Credits</td>
            </tr>
            <tr>
               <td>CSC 111 Computer Programming I</td>
               <td>3</td>
            </tr>
            <tr>
               <td>CSC 211 Computer Programming II</td>
               <td>3</td>
            </tr>
            <tr>
               <td>CSC 366 Principles of Data Science*</td>
               <td>3</td>
            </tr>
            <tr>
               <td>MTH 360 Applied Probability and Statistics*</td>
               <td>3</td>
            </tr>
            <tr>
               <td>MTH 380 Experimental Design</td>
               <td>3</td>
            </tr>
            <tr>
               <td>MTH 420 Statistical Data Mining</td>
               <td>3</td>
            </tr>
         </tbody>
      </table>
   </program-courses>
   <program-summary>
      <p xmlns:ouc="http://omniupdate.com/XSL/Variables">*The following courses have prerequisites outside of this program:</p>
      <ul xmlns:ouc="http://omniupdate.com/XSL/Variables">
         <li>CSC 366 Principles of Data Science</li>
         <li>MTH 360 Applied Probability and Statistics</li>
      </ul>
      <p xmlns:ouc="http://omniupdate.com/XSL/Variables">Total Required Credits: 18</p>
      <p xmlns:ouc="http://omniupdate.com/XSL/Variables">Please refer to the General Education, Applied Learning, and Writing Intensive requirement sections of the College Catalog and consult with your advisor to ensure that graduation requirements are satisfied.</p>
      <p xmlns:ouc="http://omniupdate.com/XSL/Variables">As a part of the SUNY General Education Framework, all first-time full time Freshman at Farmingdale State College (FSC) beginning Fall 2023, are required to develop knowledge and skills in Diversity: Equity, Inclusion, and Social Justice (DEISJ). Students will be able to fulfill this requirement at FSC by taking a specially designated DEISJ course that has been developed by faculty and approved by the DEISJ Review Board. DEISJ-approved courses will be developed in accordance with the guiding principles and criteria outlined below. DEISJ-approved courses may meet other General Education Knowledge and Skills areas and/or core competencies and thus be dually designated. DEISJ-approved courses may also earn other special designations such as those for Applied Learning or Writing Intensive.</p>
   </program-summary>
   <program-notes/>
</item>
