{"id":8175,"date":"2025-10-03T13:52:32","date_gmt":"2025-10-03T20:52:32","guid":{"rendered":"https:\/\/dornsife.usc.edu\/mathematics\/?page_id=8175"},"modified":"2026-01-03T22:28:50","modified_gmt":"2026-01-04T06:28:50","slug":"pdp-in-mathematical-data-science-m-s","status":"publish","type":"page","link":"https:\/\/dornsife.usc.edu\/mathematics\/pdp-in-mathematical-data-science-m-s\/","title":{"rendered":"PDP in Mathematical Data Science M.S."},"content":{"rendered":"\n\n  \n    \n\n\n\n\n\n\n<div\n  class=\"cc--component-container cc--rich-text \"\n\n  \n  \n  \n  \n  \n  \n  >\n  <div class=\"c--component c--rich-text\"\n    \n      >\n\n    \n      \n<div class=\"f--field f--wysiwyg\">\n\n    \n  <h1>Eligibility Requirements<\/h1>\n<ul>\n<li>Minimum Cumulative USC GPA of 3.5<\/li>\n<li>Math 235 or 225, Math 226\/229, and Math 307 or 407 completed by the time of application; completion of Math 308 or 408 is also recommended, but not required<\/li>\n<li>At least 64 total units of undergraduate college course work, excluding any AP, IB or transfer units earned prior to graduation from high school<\/li>\n<\/ul>\n<p>Students must meet the requirements listed above to be eligible to apply for this PDP. Please note that meeting these standards does not guarantee admission. The Department of Mathematics is now accepting applications for a <strong>Fall 2026 start date.<\/strong><\/p>\n<p>&nbsp;<\/p>\n\n\n\n<\/div>\n\n\n  <\/div><\/div>\n\n\n\n\n  \n    \n\n\n\n\n\n\n<div\n  class=\"cc--component-container cc--rich-text \"\n\n  \n  \n  \n  \n  \n  \n  >\n  <div class=\"c--component c--rich-text\"\n    \n      >\n\n    \n      \n<div class=\"f--field f--wysiwyg\">\n\n    \n  <h1>Degree Requirements<\/h1>\n<p style=\"text-align: left;\" align=\"justify\">Students are required to complete a minimum\u00a0 of 32 units of course work. Out of the 32 units, a maximum of 10 units from the elective coursework can be changed to <em>undergraduate credit<\/em>. To graduate, students must maintain a cumulative GPA of 3.0 or higher in the graduate credit applied to the PDP. The 32 units consists of:<\/p>\n<h2><strong>Core Curriculum (5 courses, 19 units)<\/strong><\/h2>\n<table style=\"border-collapse: collapse; width: 100%; height: 72px;\" border=\"1\">\n<tbody>\n<tr style=\"height: 24px;\">\n<td style=\"width: 33.3333%; height: 24px;\"><strong>COURSE<\/strong><\/td>\n<td style=\"width: 33.3333%; height: 24px;\"><strong>COURSE TITLE<\/strong><\/td>\n<td style=\"width: 33.3333%; height: 24px;\"><strong>UNITS<\/strong><\/td>\n<\/tr>\n<tr style=\"height: 24px;\">\n<td style=\"width: 33.3333%; height: 24px;\">MATH 447<\/td>\n<td style=\"width: 33.3333%; height: 24px;\">Mathematics of Machine Learning<\/td>\n<td style=\"width: 33.3333%; height: 24px;\">4<\/td>\n<\/tr>\n<tr style=\"height: 24px;\">\n<td style=\"width: 33.3333%; height: 24px;\">MATH 546<\/td>\n<td style=\"width: 33.3333%; height: 24px;\">Mathematical Statistics for Data Science<\/td>\n<td style=\"width: 33.3333%; height: 24px;\">4<\/td>\n<\/tr>\n<tr>\n<td style=\"width: 33.3333%;\">MATH 549<\/td>\n<td style=\"width: 33.3333%;\">Foundations of Mathematical Data Science<\/td>\n<td style=\"width: 33.3333%;\">4<\/td>\n<\/tr>\n<tr>\n<td style=\"width: 33.3333%;\">MATH 550<\/td>\n<td style=\"width: 33.3333%;\">Statistical Consulting and Data Analysis<\/td>\n<td style=\"width: 33.3333%;\">3<\/td>\n<\/tr>\n<tr>\n<td style=\"width: 33.3333%;\">PHYS 515<\/td>\n<td style=\"width: 33.3333%;\">Python for Data Science and Scientific Computing<\/td>\n<td style=\"width: 33.3333%;\">4<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<h2><strong>Electives (12 units, selected from the following list)<\/strong><\/h2>\n<p><strong>NOTE:<\/strong> Some of these courses have prerequisites. You are expected to have learned the prerequisite&#8217;s topic from your previous undergraduate institution or from self-studying in order to waive the prerequisite. If you prefer to take the prerequisite at USC, units for prerequisite courses do not count towards the degree.<\/p>\n<p>Although all of the courses listed below are approved electives for this degree, we are not able to give departmental authorization or permission for you to register in courses outside of the Mathematics department. Students will need to request D-clearance and prerequisite waivers from the department who offers the course. If you are not sure how to contact the department, email the MDS academic advisor, Dr. Patil (upatil@usc.edu).<\/p>\n<p style=\"text-align: center;\"><strong>COMPUTER SCIENCE (CSCI)<\/strong><\/p>\n<table style=\"border-collapse: collapse; width: 100%;\" border=\"1\">\n<tbody>\n<tr style=\"height: 24px;\">\n<td style=\"width: 33.3333%; height: 24px;\"><strong>COURSE<\/strong><\/td>\n<td style=\"width: 33.3333%; height: 24px;\"><strong>COURSE TITLE<\/strong><\/td>\n<td style=\"width: 33.3333%; height: 24px;\"><strong>UNITS<\/strong><\/td>\n<\/tr>\n<tr>\n<td style=\"width: 33.3333%;\"><span data-olk-copy-source=\"MessageBody\">CSCI 551<\/span><\/td>\n<td style=\"width: 33.3333%;\"><span data-olk-copy-source=\"MessageBody\">Computer Networking<\/span><\/td>\n<td style=\"width: 33.3333%;\">4<\/td>\n<\/tr>\n<tr>\n<td style=\"width: 33.3333%;\"><span data-olk-copy-source=\"MessageBody\">CSCI 566<\/span><\/td>\n<td style=\"width: 33.3333%;\"><span data-olk-copy-source=\"MessageBody\">Deep Learning and Its Applications<\/span><\/td>\n<td style=\"width: 33.3333%;\">4<\/td>\n<\/tr>\n<tr>\n<td style=\"width: 33.3333%;\"><span data-olk-copy-source=\"MessageBody\">CSCI 567<\/span><\/td>\n<td style=\"width: 33.3333%;\"><span data-olk-copy-source=\"MessageBody\">Machine Learning<\/span><\/td>\n<td style=\"width: 33.3333%;\">4<\/td>\n<\/tr>\n<tr>\n<td style=\"width: 33.3333%;\">CSCI 570<\/td>\n<td style=\"width: 33.3333%;\">Analysis of Algorithms<\/td>\n<td style=\"width: 33.3333%;\">4<\/td>\n<\/tr>\n<tr>\n<td style=\"width: 33.3333%;\">CSCI 585<\/td>\n<td style=\"width: 33.3333%;\">Database Systems<\/td>\n<td style=\"width: 33.3333%;\">4<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<p style=\"text-align: center;\"><strong>DATA SCIENCE (DSCI)<\/strong><\/p>\n<table style=\"border-collapse: collapse; width: 100%;\" border=\"1\">\n<tbody>\n<tr style=\"height: 24px;\">\n<td style=\"width: 33.3333%; height: 24px;\"><strong>COURSE<\/strong><\/td>\n<td style=\"width: 33.3333%; height: 24px;\"><strong>COURSE TITLE<\/strong><\/td>\n<td style=\"width: 33.3333%; height: 24px;\"><strong>UNITS<\/strong><\/td>\n<\/tr>\n<tr>\n<td style=\"width: 33.3333%;\">DSCI 560<\/td>\n<td style=\"width: 33.3333%;\">Data Science Professional Practicum<\/td>\n<td style=\"width: 33.3333%;\">4<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<p style=\"text-align: center;\"><strong>DATA SCIENCE AND OPERTIONS (DSO)<\/strong><\/p>\n<table style=\"border-collapse: collapse; width: 100%;\" border=\"1\">\n<tbody>\n<tr style=\"height: 24px;\">\n<td style=\"width: 33.3333%; height: 24px;\"><strong>COURSE<\/strong><\/td>\n<td style=\"width: 33.3333%; height: 24px;\"><strong>COURSE TITLE<\/strong><\/td>\n<td style=\"width: 33.3333%; height: 24px;\"><strong>UNITS<\/strong><\/td>\n<\/tr>\n<tr>\n<td style=\"width: 33.3333%;\">DSO 528<\/td>\n<td style=\"width: 33.3333%;\">Blended Data Business Analytics for Efficient Decisions<\/td>\n<td style=\"width: 33.3333%;\">3<\/td>\n<\/tr>\n<tr>\n<td style=\"width: 33.3333%;\">DSO 545<\/td>\n<td style=\"width: 33.3333%;\">Statistical Computing and Data Visualization<\/td>\n<td style=\"width: 33.3333%;\">3<\/td>\n<\/tr>\n<tr>\n<td style=\"width: 33.3333%;\">DSO 530<\/td>\n<td style=\"width: 33.3333%;\">Applied Modern Statistical Learning Methods<\/td>\n<td style=\"width: 33.3333%;\">3<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<p style=\"text-align: center;\"><strong>ELECTRICAL AND COMPUTER ENGINEERING (EE)<\/strong><\/p>\n<table style=\"border-collapse: collapse; width: 100%;\" border=\"1\">\n<tbody>\n<tr style=\"height: 24px;\">\n<td style=\"width: 33.3333%; height: 24px;\"><strong>COURSE<\/strong><\/td>\n<td style=\"width: 33.3333%; height: 24px;\"><strong>COURSE TITLE<\/strong><\/td>\n<td style=\"width: 33.3333%; height: 24px;\"><strong>UNITS<\/strong><\/td>\n<\/tr>\n<tr>\n<td style=\"width: 33.3333%;\">EE 546<\/td>\n<td style=\"width: 33.3333%;\">Mathematics of High Dimensional Data<\/td>\n<td style=\"width: 33.3333%;\">4<\/td>\n<\/tr>\n<tr>\n<td style=\"width: 33.3333%;\">EE 553<\/td>\n<td style=\"width: 33.3333%;\">Computational Solution of Optimization problems<\/td>\n<td style=\"width: 33.3333%;\">3<\/td>\n<\/tr>\n<tr>\n<td style=\"width: 33.3333%;\">EE 660<\/td>\n<td style=\"width: 33.3333%;\">Machine Learning II: Mathematical Foundations and Methods<\/td>\n<td style=\"width: 33.3333%;\">4<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<p style=\"text-align: center;\"><strong>INDUSTRIAL SYSTEMS ENGINEERING (ISE)<\/strong><\/p>\n<table style=\"border-collapse: collapse; width: 100%;\" border=\"1\">\n<tbody>\n<tr style=\"height: 24px;\">\n<td style=\"width: 33.3333%; height: 24px;\"><strong>COURSE<\/strong><\/td>\n<td style=\"width: 33.3333%; height: 24px;\"><strong>COURSE TITLE<\/strong><\/td>\n<td style=\"width: 33.3333%; height: 24px;\"><strong>UNITS<\/strong><\/td>\n<\/tr>\n<tr>\n<td style=\"width: 33.3333%;\">ISE 520<\/td>\n<td style=\"width: 33.3333%;\">Optimization: Theory and Algorithms<\/td>\n<td style=\"width: 33.3333%;\">3<\/td>\n<\/tr>\n<tr>\n<td style=\"width: 33.3333%;\">ISE 530<\/td>\n<td style=\"width: 33.3333%;\">Optimization Methods for Analytics<\/td>\n<td style=\"width: 33.3333%;\">4<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<p style=\"text-align: center;\"><strong>MATHEMATICS (MATH)<\/strong><\/p>\n<table style=\"border-collapse: collapse; width: 100%;\" border=\"1\">\n<tbody>\n<tr style=\"height: 24px;\">\n<td style=\"width: 33.3333%; height: 24px;\"><strong>COURSE<\/strong><\/td>\n<td style=\"width: 33.3333%; height: 24px;\"><strong>COURSE TITLE<\/strong><\/td>\n<td style=\"width: 33.3333%; height: 24px;\"><strong>UNITS<\/strong><\/td>\n<\/tr>\n<tr>\n<td style=\"width: 33.3333%;\">MATH 446<\/td>\n<td style=\"width: 33.3333%;\">Data Science with Python<\/td>\n<td style=\"width: 33.3333%;\">4<\/td>\n<\/tr>\n<tr>\n<td style=\"width: 33.3333%;\">MATH 505a<\/td>\n<td style=\"width: 33.3333%;\">Applied Probability<\/td>\n<td style=\"width: 33.3333%;\">3<\/td>\n<\/tr>\n<tr>\n<td style=\"width: 33.3333%;\">MATH 542<\/td>\n<td style=\"width: 33.3333%;\">Analysis of Variance and Design<\/td>\n<td style=\"width: 33.3333%;\">3<\/td>\n<\/tr>\n<tr>\n<td style=\"width: 33.3333%;\">MATH 545<\/td>\n<td style=\"width: 33.3333%;\">Introduction to Time Series<\/td>\n<td style=\"width: 33.3333%;\">3<\/td>\n<\/tr>\n<tr>\n<td style=\"width: 33.3333%;\">MATH 547<\/td>\n<td style=\"width: 33.3333%;\">Mathematical Foundations of Statistical Learning Theory<\/td>\n<td style=\"width: 33.3333%;\">3<\/td>\n<\/tr>\n<tr>\n<td style=\"width: 33.3333%;\">MATH 548<\/td>\n<td style=\"width: 33.3333%;\">Machine Learning in Quantitative Finance<\/td>\n<td style=\"width: 33.3333%;\">3<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<p style=\"text-align: center;\"><strong>QUANTITATIVE AND COMPUTATIONAL BIOLOGY (QBIO)<\/strong><\/p>\n<table style=\"border-collapse: collapse; width: 100%;\" border=\"1\">\n<tbody>\n<tr style=\"height: 24px;\">\n<td style=\"width: 33.3333%; height: 24px;\"><strong>COURSE<\/strong><\/td>\n<td style=\"width: 33.3333%; height: 24px;\"><strong>COURSE TITLE<\/strong><\/td>\n<td style=\"width: 33.3333%; height: 24px;\"><strong>UNITS<\/strong><\/td>\n<\/tr>\n<tr>\n<td style=\"width: 33.3333%;\">QBIO 578a<\/td>\n<td style=\"width: 33.3333%;\">Computational Molecular Biology<\/td>\n<td style=\"width: 33.3333%;\">3<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<p style=\"text-align: center;\"><strong>SPATIAL SCIENCES (SSCI)<\/strong><\/p>\n<table style=\"border-collapse: collapse; width: 100%;\" border=\"1\">\n<tbody>\n<tr style=\"height: 24px;\">\n<td style=\"width: 33.3333%; height: 24px;\"><strong>COURSE<\/strong><\/td>\n<td style=\"width: 33.3333%; height: 24px;\"><strong>COURSE TITLE<\/strong><\/td>\n<td style=\"width: 33.3333%; height: 24px;\"><strong>UNITS<\/strong><\/td>\n<\/tr>\n<tr>\n<td style=\"width: 33.3333%;\">SSCI 581<\/td>\n<td style=\"width: 33.3333%;\">Concepts for Spatial Thinking<\/td>\n<td style=\"width: 33.3333%;\">4<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<p><strong>Courses that do NOT satisfy the elective requirement:<\/strong><\/p>\n<p><span data-olk-copy-source=\"MessageBody\">CSCI 512 Testing and Analysis of Software Systems<br \/>\nCSCI 548 Machine Learning<br \/>\nCSCI 555L Advanced Operating Systems<br \/>\nMATH 541a\/b Introduction to Mathematical Statistics<\/span><\/p>\n<p>For all other courses that are not included in the lists above, please contact the academic advisor, Dr. Patil (upatil@usc.edu) to request the course to be reviewed.<\/p>\n<h2><strong>Additional Requirements<\/strong><\/h2>\n<p>To complete the program, students enroll in at least 1 unit of MATH 590 Directed Research and submit a summative report at the end of the term. Note: enrollment in MATH 590 will often be concurrent with enrollment in MATH 550. Students should consult with their advisor for details.<\/p>\n\n\n\n<\/div>\n\n\n  <\/div><\/div>\n\n\n\n\n\n\n      \n  \n    \n\n\n\n\n\n\n<div\n  class=\"cc--component-container cc--accordions \"\n\n  \n  \n  \n  \n  \n  \n  >\n  <div class=\"c--component c--accordions\"\n    \n      >\n\n    \n      <div class=\"header-container\">\n\n                  \n<div class=\"f--field f--section-title\">\n\n    \n  <h2>\n          Sample Course Plans\n      <\/h2>\n\n\n<\/div>\n      \n                  \n<div class=\"f--field f--description\">\n\n    \n  <p>The Mathematical Data Science M.S. program is designed to be completed in 3-4 semesters, or 1.5-2 years.<\/p>\n<div>Core courses offered *ONLY* in Fall semester: MATH 546, MATH 549, MATH550<br \/>\nCore courses\u00a0offered *ONLY* in Spring semester: PHYS 515<br \/>\nCore courses\u00a0offered in *BOTH* Fall &amp; Spring semesters: MATH 447<\/div>\n\n\n\n<\/div>\n      \n      \n    <\/div>\n  \n      <ul>\n              <li>\n          <button type=\"button\" class=\"accordion-trigger \" id=\"heading-1-1-YC27yFECN0\" aria-controls=\"section-1-1-YC27yFECN0\" aria-expanded=\"false\" aria-disabled=\"false\">\n                          <span class=\"item-title\">3 semesters, Fall Start<\/span>\n            \n                      <\/button>\n\n          <div id=\"section-1-1-YC27yFECN0\" role=\"region\" aria-labelledby=\"heading-1-1-YC27yFECN0\" class=\"accordion-panel\">\n\n                            \n    \n\n\n\n\n\n\n<div\n  class=\"cc--component-container cc--rich-text \"\n\n  \n  \n  \n  \n  \n  \n  >\n  <div class=\"c--component c--rich-text\"\n    \n      >\n\n    \n      \n<div class=\"f--field f--wysiwyg\">\n\n    \n  <p><span style=\"text-decoration: underline;\"><strong>Fall semester #1<br \/>\n<\/strong><\/span>MATH 546<br \/>\nMATH 549<br \/>\nElective<\/p>\n<p><span style=\"text-decoration: underline;\"><strong>Spring semester #2<br \/>\n<\/strong><\/span>PHYS 515<br \/>\nMATH 447<br \/>\nElective<br \/>\nElective<\/p>\n<p><span style=\"text-decoration: underline;\"><strong>Fall semester #3<br \/>\n<\/strong><\/span>MATH 550<br \/>\nMATH 590<br \/>\nElective<\/p>\n<p>&nbsp;<\/p>\n\n\n\n<\/div>\n\n\n  <\/div><\/div>\n            \n                      <\/div>\n        <\/li>\n\n              <li>\n          <button type=\"button\" class=\"accordion-trigger \" id=\"heading-1-2-YC27yFECN0\" aria-controls=\"section-1-2-YC27yFECN0\" aria-expanded=\"false\" aria-disabled=\"false\">\n                          <span class=\"item-title\">4 semesters, Fall Start<\/span>\n            \n                      <\/button>\n\n          <div id=\"section-1-2-YC27yFECN0\" role=\"region\" aria-labelledby=\"heading-1-2-YC27yFECN0\" class=\"accordion-panel\">\n\n                            \n    \n\n\n\n\n\n\n<div\n  class=\"cc--component-container cc--rich-text \"\n\n  \n  \n  \n  \n  \n  \n  >\n  <div class=\"c--component c--rich-text\"\n    \n      >\n\n    \n      \n<div class=\"f--field f--wysiwyg\">\n\n    \n  <p><span style=\"text-decoration: underline;\"><strong>Fall semester #1<br \/>\n<\/strong><\/span>MATH 546<br \/>\nMATH 549<\/p>\n<p><span style=\"text-decoration: underline;\"><strong>Spring semester #2<br \/>\n<\/strong><\/span>PHYS 515<br \/>\nMATH 447<\/p>\n<p><span style=\"text-decoration: underline;\"><strong>Fall semester #3<br \/>\n<\/strong><\/span>MATH 550<br \/>\nMATH 590<br \/>\n2 Electives<\/p>\n<p><span style=\"text-decoration: underline;\"><strong>Spring semester #4<br \/>\n<\/strong><\/span>2 Electives*<\/p>\n<p><em>*International Students should apply for a final semester Reduced Course Load approval if they do not need 8 units to graduate in their final semester<\/em><\/p>\n\n\n\n<\/div>\n\n\n  <\/div><\/div>\n            \n                      <\/div>\n        <\/li>\n\n              <li>\n          <button type=\"button\" class=\"accordion-trigger \" id=\"heading-1-3-YC27yFECN0\" aria-controls=\"section-1-3-YC27yFECN0\" aria-expanded=\"false\" aria-disabled=\"false\">\n                          <span class=\"item-title\">4 semesters, Spring Start<\/span>\n            \n                      <\/button>\n\n          <div id=\"section-1-3-YC27yFECN0\" role=\"region\" aria-labelledby=\"heading-1-3-YC27yFECN0\" class=\"accordion-panel\">\n\n                            \n    \n\n\n\n\n\n\n<div\n  class=\"cc--component-container cc--rich-text \"\n\n  \n  \n  \n  \n  \n  \n  >\n  <div class=\"c--component c--rich-text\"\n    \n      >\n\n    \n      \n<div class=\"f--field f--wysiwyg\">\n\n    \n  <div data-olk-copy-source=\"MessageBody\"><span style=\"text-decoration: underline;\"><strong>Spring Semester #1<\/strong><\/span><br \/>\nPHYS 515<br \/>\nMATH 447<\/div>\n<div data-olk-copy-source=\"MessageBody\"><\/div>\n<div><span style=\"text-decoration: underline;\"><strong>Fall Semester #2<\/strong><\/span><br \/>\nMATH 546<br \/>\nMATH 549<\/div>\n<div><\/div>\n<div><span style=\"text-decoration: underline;\"><strong>Spring Semester #3<\/strong><\/span><br \/>\n3 Electives<\/div>\n<div><\/div>\n<div><span style=\"text-decoration: underline;\"><strong>Fall Semester #4<\/strong><\/span><br \/>\nMATH 590<br \/>\nMATH 550<br \/>\n1 Elective*<\/div>\n\n\n\n<\/div>\n\n\n  <\/div><\/div>\n            \n                      <\/div>\n        <\/li>\n\n          <\/ul>\n  \n  \n\n  <\/div><\/div>\n\n\n\n\n  \n    \n\n\n\n\n\n\n<div\n  class=\"cc--component-container cc--rich-text \"\n\n  \n  \n  \n  \n  \n  \n  >\n  <div class=\"c--component c--rich-text\"\n    \n      >\n\n    \n      \n<div class=\"f--field f--wysiwyg\">\n\n    \n  <h1>Steps to Apply<\/h1>\n<p>We are now accepting applications for a <strong>Fall 2026 start date. <\/strong>Beginning Fall 2026, applications are accepted on a rolling basis.<\/p>\n<ol>\n<li>Fill out the <a href=\"https:\/\/academicprograms.usc.edu\/wp-content\/uploads\/2025\/04\/2024-Progressive-Degree-Application.pdf\" target=\"_blank\" rel=\"noopener\">PDP application form<\/a> with your remaining undergraduate degree requirements and PDP requirements. <em>Courses that fulfill your undergraduate degree requirements should have an X or check mark for &#8220;UG&#8221; = undergraduate credit. Courses that fulfill your PDP degree requirements should have an X or check mark for &#8220;GR&#8221; = graduate credit. A course cannot be marked for both UG and GR credit.<\/em><\/li>\n<li>Send the completed form to the PDP advisor and undergraduate advisor(s) for review. If no corrections need to be made to the PDP course plan, advisors will sign the form. If corrections need to be made, advisors will discuss changes with you via email or during a scheduled meeting.<\/li>\n<li>Ask professors to send a letter of recommendation to the PDP advisor. Two letters of recommendation from professors are required for applicants with a cumulative GPA below 3.5. One letter of recommendation is required for applicants with a cumulative GPA of 3.5 or higher.<\/li>\n<li>Once all application materials are submitted, you will receive admission results within 2 weeks.<\/li>\n<\/ol>\n\n\n\n<\/div>\n\n\n  <\/div><\/div>\n","protected":false},"excerpt":{"rendered":"","protected":false},"author":77,"featured_media":0,"parent":0,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"_acf_changed":false,"footnotes":""},"class_list":["post-8175","page","type-page","status-publish","hentry"],"acf":[],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v27.1.1 - https:\/\/yoast.com\/product\/yoast-seo-wordpress\/ -->\n<title>PDP in Mathematical Data Science M.S. - Department of Mathematics<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/dornsife.usc.edu\/mathematics\/pdp-in-mathematical-data-science-m-s\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"PDP in Mathematical Data Science M.S. - 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