[{"run_id":"20260906T231458-5fdd2fff","semester":"1272","observed_at":"2026-09-06 23:14:58.172943+00:00","record_version_id":"4912d5c4a055f4e22f1c537e4497c9367f8dc9c731d3052b911a6b9420fa8b00","course_id":"ME 737","course_uid":"course_7ab6b3133883319bcb210142","catalog_version_id":"3d4e0fff7dbc919810e8e365ba10951b77100bad266069ff984d7e8eed834444","course_number":737,"subjects":["ME"],"title":"SCIENTIFIC COMPUTING AND MACHINE LEARNING FOR ENGINEERING APPLICATIONS","description":"Key computational topics for engineering applications will be discussed, encompassing both established classical numerical methods and the emerging field of machine learning. Knowledge of calculus [such asMATH 221], linear algebra and differential equations [such asMATH 320], probability [such asMATH 331] and programming in Python or MATLAB [such asCOMP SCI 220] is required.","requirements_text":"Graduate/professional standing"},{"run_id":"20260907T155543-ce3781c4","semester":"1272","observed_at":"2026-09-07 15:55:43.033547+00:00","record_version_id":"4912d5c4a055f4e22f1c537e4497c9367f8dc9c731d3052b911a6b9420fa8b00","course_id":"ME 737","course_uid":"course_7ab6b3133883319bcb210142","catalog_version_id":"3d4e0fff7dbc919810e8e365ba10951b77100bad266069ff984d7e8eed834444","course_number":737,"subjects":["ME"],"title":"SCIENTIFIC COMPUTING AND MACHINE LEARNING FOR ENGINEERING APPLICATIONS","description":"Key computational topics for engineering applications will be discussed, encompassing both established classical numerical methods and the emerging field of machine learning. Knowledge of calculus [such asMATH 221], linear algebra and differential equations [such asMATH 320], probability [such asMATH 331] and programming in Python or MATLAB [such asCOMP SCI 220] is required.","requirements_text":"Graduate/professional standing"},{"run_id":"legacy-08c92e359bbbc110b0778b7e0b15d6f40000e6b1","semester":"1262","observed_at":"2025-08-21 07:05:14.730696+00:00","record_version_id":"f3d6dfd4d1b104dea3815c470c1cbb90825c0d676515a80eec0f7a32dcc35c6f","course_id":"ME 737","course_uid":"course_7ab6b3133883319bcb210142","catalog_version_id":"3d4e0fff7dbc919810e8e365ba10951b77100bad266069ff984d7e8eed834444","course_number":737,"subjects":["ME"],"title":"SCIENTIFIC COMPUTING AND MACHINE LEARNING FOR ENGINEERING APPLICATIONS","description":"Key computational topics for engineering applications will be discussed, encompassing both established classical numerical methods and the emerging field of machine learning. Knowledge of calculus [such asMATH 221], linear algebra and differential equations [such asMATH 320], probability [such asMATH 331] and programming in Python or MATLAB [such asCOMP SCI 220] is required.","requirements_text":"Graduate/professional standing"},{"run_id":"legacy-0a7f4bce29c816ef4d3d71b4eb8a2a3e15e33cc1","semester":"1262","observed_at":"2025-06-18 20:04:02.695444+00:00","record_version_id":"dd5b0a2e1b773d92cf174a394ba5942d4182974ab69a0386f085d05261caf185","course_id":"ME 737","course_uid":"course_7ab6b3133883319bcb210142","catalog_version_id":"3d4e0fff7dbc919810e8e365ba10951b77100bad266069ff984d7e8eed834444","course_number":737,"subjects":["ME"],"title":"SCIENTIFIC COMPUTING AND MACHINE LEARNING FOR ENGINEERING APPLICATIONS","description":"Key computational topics for engineering applications will be discussed, encompassing both established classical numerical methods and the emerging field of machine learning. Knowledge of calculus [such asMATH 221], linear algebra and differential equations [such asMATH 320], probability [such asMATH 331] and programming in Python or MATLAB [such asCOMP SCI 220] is required.","requirements_text":"Graduate/professional standing"},{"run_id":"legacy-0cb4d29a588ec7f11c7e00b7cf5dc3a0d23d0349","semester":"1266","observed_at":"2026-01-22 01:00:26.555427+00:00","record_version_id":"68eda98be5910a346f0ca6a98695c908b28282935317e4e9aa5c42adeb3670d0","course_id":"ME 737","course_uid":"course_7ab6b3133883319bcb210142","catalog_version_id":"3d4e0fff7dbc919810e8e365ba10951b77100bad266069ff984d7e8eed834444","course_number":737,"subjects":["ME"],"title":"SCIENTIFIC COMPUTING AND MACHINE LEARNING FOR ENGINEERING APPLICATIONS","description":"Key computational topics for engineering applications will be discussed, encompassing both established classical numerical methods and the emerging field of machine learning. Knowledge of calculus [such asMATH 221], linear algebra and differential equations [such asMATH 320], probability [such asMATH 331] and programming in Python or MATLAB [such asCOMP SCI 220] is required.","requirements_text":"Graduate/professional standing"},{"run_id":"legacy-11c30ec39e91498cbfcf3a923c53a4b03e387280","semester":"1262","observed_at":"2025-07-20 04:58:26.847117+00:00","record_version_id":"4a54c9ea675621809392278351f22ab3f67fcd5cf69ec163e44f1bba3c1c41c9","course_id":"ME 737","course_uid":"course_7ab6b3133883319bcb210142","catalog_version_id":"3d4e0fff7dbc919810e8e365ba10951b77100bad266069ff984d7e8eed834444","course_number":737,"subjects":["ME"],"title":"SCIENTIFIC COMPUTING AND MACHINE LEARNING FOR ENGINEERING APPLICATIONS","description":"Key computational topics for engineering applications will be discussed, encompassing both established classical numerical methods and the emerging field of machine learning. Knowledge of calculus [such asMATH 221], linear algebra and differential equations [such asMATH 320], probability [such asMATH 331] and programming in Python or MATLAB [such asCOMP SCI 220] is required.","requirements_text":"Graduate/professional standing"},{"run_id":"legacy-13cd500edf2587e9a3428f326253738fbea965ea","semester":"1264","observed_at":"2025-12-14 04:50:04.653658+00:00","record_version_id":"14b196226801c45cdd189546e574786d4ed2e17e2e0a8093a33715f780c29277","course_id":"ME 737","course_uid":"course_7ab6b3133883319bcb210142","catalog_version_id":"3d4e0fff7dbc919810e8e365ba10951b77100bad266069ff984d7e8eed834444","course_number":737,"subjects":["ME"],"title":"SCIENTIFIC COMPUTING AND MACHINE LEARNING FOR ENGINEERING APPLICATIONS","description":"Key computational topics for engineering applications will be discussed, encompassing both established classical numerical methods and the emerging field of machine learning. Knowledge of calculus [such asMATH 221], linear algebra and differential equations [such asMATH 320], probability [such asMATH 331] and programming in Python or MATLAB [such asCOMP SCI 220] is required.","requirements_text":"Graduate/professional standing"},{"run_id":"legacy-1da08b2de39f05e6bc877c189fc2fd6eeda563f5","semester":"1262","observed_at":"2025-07-01 00:03:56.707251+00:00","record_version_id":"dda3242353bb78594e4ef23c01605cb3f8d16dbc543bbec0b978c77d9c1a1825","course_id":"ME 737","course_uid":"course_7ab6b3133883319bcb210142","catalog_version_id":"3d4e0fff7dbc919810e8e365ba10951b77100bad266069ff984d7e8eed834444","course_number":737,"subjects":["ME"],"title":"SCIENTIFIC COMPUTING AND MACHINE LEARNING FOR ENGINEERING APPLICATIONS","description":"Key computational topics for engineering applications will be discussed, encompassing both established classical numerical methods and the emerging field of machine learning. Knowledge of calculus [such asMATH 221], linear algebra and differential equations [such asMATH 320], probability [such asMATH 331] and programming in Python or MATLAB [such asCOMP SCI 220] is required.","requirements_text":"Graduate/professional standing"},{"run_id":"legacy-2031af47efe133b0e7877f433286ff07385afc41","semester":"1262","observed_at":"2025-07-02 20:16:45.749584+00:00","record_version_id":"188073f6391958167a454f18d52c563c609a2063266ee044ac2c8fd316057853","course_id":"ME 737","course_uid":"course_7ab6b3133883319bcb210142","catalog_version_id":"3d4e0fff7dbc919810e8e365ba10951b77100bad266069ff984d7e8eed834444","course_number":737,"subjects":["ME"],"title":"SCIENTIFIC COMPUTING AND MACHINE LEARNING FOR ENGINEERING APPLICATIONS","description":"Key computational topics for engineering applications will be discussed, encompassing both established classical numerical methods and the emerging field of machine learning. Knowledge of calculus [such asMATH 221], linear algebra and differential equations [such asMATH 320], probability [such asMATH 331] and programming in Python or MATLAB [such asCOMP SCI 220] is required.","requirements_text":"Graduate/professional standing"},{"run_id":"legacy-238eba6f32fbc30407f616dd0628ff02a2a824dd","semester":"1262","observed_at":"2025-08-17 05:15:07.788352+00:00","record_version_id":"f85e0b36cfd5c8d640345eb7d10c20b64cb31d8ed662cc09f31d01f8ad732d57","course_id":"ME 737","course_uid":"course_7ab6b3133883319bcb210142","catalog_version_id":"3d4e0fff7dbc919810e8e365ba10951b77100bad266069ff984d7e8eed834444","course_number":737,"subjects":["ME"],"title":"SCIENTIFIC COMPUTING AND MACHINE LEARNING FOR ENGINEERING APPLICATIONS","description":"Key computational topics for engineering applications will be discussed, encompassing both established classical numerical methods and the emerging field of machine learning. Knowledge of calculus [such asMATH 221], linear algebra and differential equations [such asMATH 320], probability [such asMATH 331] and programming in Python or MATLAB [such asCOMP SCI 220] is required.","requirements_text":"Graduate/professional standing"},{"run_id":"legacy-2923f91826ce253b7aeefa9f75b4a39fe4c80ff0","semester":"1262","observed_at":"2025-08-10 05:10:25.938416+00:00","record_version_id":"aa98aa63d06fa79c90b7d845b5d2e78b06b73db0d94835822f63d8cd89e43ed7","course_id":"ME 737","course_uid":"course_7ab6b3133883319bcb210142","catalog_version_id":"3d4e0fff7dbc919810e8e365ba10951b77100bad266069ff984d7e8eed834444","course_number":737,"subjects":["ME"],"title":"SCIENTIFIC COMPUTING AND MACHINE LEARNING FOR ENGINEERING APPLICATIONS","description":"Key computational topics for engineering applications will be discussed, encompassing both established classical numerical methods and the emerging field of machine learning. Knowledge of calculus [such asMATH 221], linear algebra and differential equations [such asMATH 320], probability [such asMATH 331] and programming in Python or MATLAB [such asCOMP SCI 220] is required.","requirements_text":"Graduate/professional standing"},{"run_id":"legacy-2a05214a4023e0157fa6f7d188c85308f714176c","semester":"1262","observed_at":"2025-09-07 04:56:38.255315+00:00","record_version_id":"37cf39b18ab263be6c64694d97750058b5be3633bbc2f358be165db8da63b830","course_id":"ME 737","course_uid":"course_7ab6b3133883319bcb210142","catalog_version_id":"3d4e0fff7dbc919810e8e365ba10951b77100bad266069ff984d7e8eed834444","course_number":737,"subjects":["ME"],"title":"SCIENTIFIC COMPUTING AND MACHINE LEARNING FOR ENGINEERING APPLICATIONS","description":"Key computational topics for engineering applications will be discussed, encompassing both established classical numerical methods and the emerging field of machine learning. Knowledge of calculus [such asMATH 221], linear algebra and differential equations [such asMATH 320], probability [such asMATH 331] and programming in Python or MATLAB [such asCOMP SCI 220] is required.","requirements_text":"Graduate/professional standing"},{"run_id":"legacy-33a1225644e5a5855d60f66e65413946e72fedf4","semester":"1262","observed_at":"2025-06-22 01:52:05.152650+00:00","record_version_id":"8d45841099e215929a1e5e281bbe1e1cdb7e7078a9cef2f58d4ac81a9892042d","course_id":"ME 737","course_uid":"course_7ab6b3133883319bcb210142","catalog_version_id":"3d4e0fff7dbc919810e8e365ba10951b77100bad266069ff984d7e8eed834444","course_number":737,"subjects":["ME"],"title":"SCIENTIFIC COMPUTING AND MACHINE LEARNING FOR ENGINEERING APPLICATIONS","description":"Key computational topics for engineering applications will be discussed, encompassing both established classical numerical methods and the emerging field of machine learning. Knowledge of calculus [such asMATH 221], linear algebra and differential equations [such asMATH 320], probability [such asMATH 331] and programming in Python or MATLAB [such asCOMP SCI 220] is required.","requirements_text":"Graduate/professional standing"},{"run_id":"legacy-3b89c83dbf5208e13756184de1f2b2d0c09af35f","semester":"1262","observed_at":"2025-06-30 06:40:10.235522+00:00","record_version_id":"345969ed4dc2623a6cd0bc484961da385af58cb3452632e5c18e81882212a203","course_id":"ME 737","course_uid":"course_7ab6b3133883319bcb210142","catalog_version_id":"3d4e0fff7dbc919810e8e365ba10951b77100bad266069ff984d7e8eed834444","course_number":737,"subjects":["ME"],"title":"SCIENTIFIC COMPUTING AND MACHINE LEARNING FOR ENGINEERING APPLICATIONS","description":"Key computational topics for engineering applications will be discussed, encompassing both established classical numerical methods and the emerging field of machine learning. Knowledge of calculus [such asMATH 221], linear algebra and differential equations [such asMATH 320], probability [such asMATH 331] and programming in Python or MATLAB [such asCOMP SCI 220] is required.","requirements_text":"Graduate/professional standing"},{"run_id":"legacy-486f091e051fdb4ccdb80ee7b4fb0a5814510324","semester":"1264","observed_at":"2025-11-16 05:32:31.273726+00:00","record_version_id":"d1ee9d46aa5b0866c422537281d07a8395519c3c922fd0980042e40b0631b3a6","course_id":"ME 737","course_uid":"course_7ab6b3133883319bcb210142","catalog_version_id":"3d4e0fff7dbc919810e8e365ba10951b77100bad266069ff984d7e8eed834444","course_number":737,"subjects":["ME"],"title":"SCIENTIFIC COMPUTING AND MACHINE LEARNING FOR ENGINEERING APPLICATIONS","description":"Key computational topics for engineering applications will be discussed, encompassing both established classical numerical methods and the emerging field of machine learning. Knowledge of calculus [such asMATH 221], linear algebra and differential equations [such asMATH 320], probability [such asMATH 331] and programming in Python or MATLAB [such asCOMP SCI 220] is required.","requirements_text":"Graduate/professional standing"},{"run_id":"legacy-50393cfc5fd5598d4f4731ef1919f2ff53af07d9","semester":"1262","observed_at":"2025-06-30 06:05:57.438846+00:00","record_version_id":"8c19287c5358b3ba7434af7816c0a0d2a7f451852c24d677c759567141200a14","course_id":"ME 737","course_uid":"course_7ab6b3133883319bcb210142","catalog_version_id":"3d4e0fff7dbc919810e8e365ba10951b77100bad266069ff984d7e8eed834444","course_number":737,"subjects":["ME"],"title":"SCIENTIFIC COMPUTING AND MACHINE LEARNING FOR ENGINEERING APPLICATIONS","description":"Key computational topics for engineering applications will be discussed, encompassing both established classical numerical methods and the emerging field of machine learning. Knowledge of calculus [such asMATH 221], linear algebra and differential equations [such asMATH 320], probability [such asMATH 331] and programming in Python or MATLAB [such asCOMP SCI 220] is required.","requirements_text":"Graduate/professional standing"},{"run_id":"legacy-50f6947786b208c800db8bbd0cec84a8f0f187d2","semester":"1262","observed_at":"2025-06-02 03:49:42.915428+00:00","record_version_id":"c85fabf1479a038d9f4810a9544e8f774878300da8f21d51c36a2c0a67d1afed","course_id":"ME 737","course_uid":"course_7ab6b3133883319bcb210142","catalog_version_id":"3d4e0fff7dbc919810e8e365ba10951b77100bad266069ff984d7e8eed834444","course_number":737,"subjects":["ME"],"title":"SCIENTIFIC COMPUTING AND MACHINE LEARNING FOR ENGINEERING APPLICATIONS","description":"Key computational topics for engineering applications will be discussed, encompassing both established classical numerical methods and the emerging field of machine learning. Knowledge of calculus [such asMATH 221], linear algebra and differential equations [such asMATH 320], probability [such asMATH 331] and programming in Python or MATLAB [such asCOMP SCI 220] is required.","requirements_text":"Graduate/professional standing"},{"run_id":"legacy-51d86ed4082dced3803c295419b0ec8440942016","semester":"1264","observed_at":"2025-11-12 04:50:41.141307+00:00","record_version_id":"f44395eb9e89595c95440605c00636eeca0d1861fe1a36fce50989eaca838cd1","course_id":"ME 737","course_uid":"course_7ab6b3133883319bcb210142","catalog_version_id":"3d4e0fff7dbc919810e8e365ba10951b77100bad266069ff984d7e8eed834444","course_number":737,"subjects":["ME"],"title":"SCIENTIFIC COMPUTING AND MACHINE LEARNING FOR ENGINEERING APPLICATIONS","description":"Key computational topics for engineering applications will be discussed, encompassing both established classical numerical methods and the emerging field of machine learning. Knowledge of calculus [such asMATH 221], linear algebra and differential equations [such asMATH 320], probability [such asMATH 331] and programming in Python or MATLAB [such asCOMP SCI 220] is required.","requirements_text":"Graduate/professional standing"},{"run_id":"legacy-53101bd1c10db0d00d094e4c9154d4c244ff23d9","semester":"1262","observed_at":"2025-10-05 04:58:05.366968+00:00","record_version_id":"15906ee3ee68784e2b3d56724060d02b9f92ba91b9fa8efe03e6d689518325ce","course_id":"ME 737","course_uid":"course_7ab6b3133883319bcb210142","catalog_version_id":"3d4e0fff7dbc919810e8e365ba10951b77100bad266069ff984d7e8eed834444","course_number":737,"subjects":["ME"],"title":"SCIENTIFIC COMPUTING AND MACHINE LEARNING FOR ENGINEERING APPLICATIONS","description":"Key computational topics for engineering applications will be discussed, encompassing both established classical numerical methods and the emerging field of machine learning. Knowledge of calculus [such asMATH 221], linear algebra and differential equations [such asMATH 320], probability [such asMATH 331] and programming in Python or MATLAB [such asCOMP SCI 220] is required.","requirements_text":"Graduate/professional standing"},{"run_id":"legacy-60949965544fce098cc006354e201149005fb77b","semester":"1264","observed_at":"2025-10-26 05:07:14.077864+00:00","record_version_id":"ec32cfeda6479eef29ec93b1a72cd685d96d88a71b32eb97a87fa5108bcf0435","course_id":"ME 737","course_uid":"course_7ab6b3133883319bcb210142","catalog_version_id":"3d4e0fff7dbc919810e8e365ba10951b77100bad266069ff984d7e8eed834444","course_number":737,"subjects":["ME"],"title":"SCIENTIFIC COMPUTING AND MACHINE LEARNING FOR ENGINEERING APPLICATIONS","description":"Key computational topics for engineering applications will be discussed, encompassing both established classical numerical methods and the emerging field of machine learning. Knowledge of calculus [such asMATH 221], linear algebra and differential equations [such asMATH 320], probability [such asMATH 331] and programming in Python or MATLAB [such asCOMP SCI 220] is required.","requirements_text":"Graduate/professional standing"},{"run_id":"legacy-6885b56099f55e08aa0205546369fb0381d50e13","semester":"1262","observed_at":"2025-07-13 04:59:22.367394+00:00","record_version_id":"37375e50fe0fd48d626a467c01643f33a14f5f364ad0c166951f24fd7d0c3b62","course_id":"ME 737","course_uid":"course_7ab6b3133883319bcb210142","catalog_version_id":"3d4e0fff7dbc919810e8e365ba10951b77100bad266069ff984d7e8eed834444","course_number":737,"subjects":["ME"],"title":"SCIENTIFIC COMPUTING AND MACHINE LEARNING FOR ENGINEERING APPLICATIONS","description":"Key computational topics for engineering applications will be discussed, encompassing both established classical numerical methods and the emerging field of machine learning. Knowledge of calculus [such asMATH 221], linear algebra and differential equations [such asMATH 320], probability [such asMATH 331] and programming in Python or MATLAB [such asCOMP SCI 220] is required.","requirements_text":"Graduate/professional standing"},{"run_id":"legacy-69d4b2b16e8268f75b6390b3a0e2ce8bf73999da","semester":"1262","observed_at":"2025-06-30 03:21:29.925498+00:00","record_version_id":"25ef88d7d11a686ff1c8e4a98818c9f030809b37b5a650b2a23a34193c6e0b72","course_id":"ME 737","course_uid":"course_7ab6b3133883319bcb210142","catalog_version_id":"3d4e0fff7dbc919810e8e365ba10951b77100bad266069ff984d7e8eed834444","course_number":737,"subjects":["ME"],"title":"SCIENTIFIC COMPUTING AND MACHINE LEARNING FOR ENGINEERING APPLICATIONS","description":"Key computational topics for engineering applications will be discussed, encompassing both established classical numerical methods and the emerging field of machine learning. Knowledge of calculus [such asMATH 221], linear algebra and differential equations [such asMATH 320], probability [such asMATH 331] and programming in Python or MATLAB [such asCOMP SCI 220] is required.","requirements_text":"Graduate/professional standing"},{"run_id":"legacy-6b29c3e0673b2f9a736d2363db5409e03d5b3ed4","semester":"1264","observed_at":"2025-12-03 12:33:41.418072+00:00","record_version_id":"4b34531a6c0748137688835cc7133ba2d7984d7a1fdaf1cc0c359ff07040d337","course_id":"ME 737","course_uid":"course_7ab6b3133883319bcb210142","catalog_version_id":"3d4e0fff7dbc919810e8e365ba10951b77100bad266069ff984d7e8eed834444","course_number":737,"subjects":["ME"],"title":"SCIENTIFIC COMPUTING AND MACHINE LEARNING FOR ENGINEERING APPLICATIONS","description":"Key computational topics for engineering applications will be discussed, encompassing both established classical numerical methods and the emerging field of machine learning. Knowledge of calculus [such asMATH 221], linear algebra and differential equations [such asMATH 320], probability [such asMATH 331] and programming in Python or MATLAB [such asCOMP SCI 220] is required.","requirements_text":"Graduate/professional standing"},{"run_id":"legacy-73259984748de484976ef2ad56ad7ab3d4cb4518","semester":"1262","observed_at":"2025-06-26 08:27:56.461216+00:00","record_version_id":"3fb0c51ce8f13f0e1d421bcb0a1cc7f06dceade965cfc31fb4e69583c86a5d0c","course_id":"ME 737","course_uid":"course_7ab6b3133883319bcb210142","catalog_version_id":"3d4e0fff7dbc919810e8e365ba10951b77100bad266069ff984d7e8eed834444","course_number":737,"subjects":["ME"],"title":"SCIENTIFIC COMPUTING AND MACHINE LEARNING FOR ENGINEERING APPLICATIONS","description":"Key computational topics for engineering applications will be discussed, encompassing both established classical numerical methods and the emerging field of machine learning. Knowledge of calculus [such asMATH 221], linear algebra and differential equations [such asMATH 320], probability [such asMATH 331] and programming in Python or MATLAB [such asCOMP SCI 220] is required.","requirements_text":"Graduate/professional standing"},{"run_id":"legacy-741602fbc6252c232a0b9e6bc1a9ae3101625f5a","semester":"1262","observed_at":"2025-06-30 22:49:32.522034+00:00","record_version_id":"2b5699c97057c68af9cec750d19c6ec247bd22616fc39edfcce9d3ed9e1d330a","course_id":"ME 737","course_uid":"course_7ab6b3133883319bcb210142","catalog_version_id":"3d4e0fff7dbc919810e8e365ba10951b77100bad266069ff984d7e8eed834444","course_number":737,"subjects":["ME"],"title":"SCIENTIFIC COMPUTING AND MACHINE LEARNING FOR ENGINEERING APPLICATIONS","description":"Key computational topics for engineering applications will be discussed, encompassing both established classical numerical methods and the emerging field of machine learning. Knowledge of calculus [such asMATH 221], linear algebra and differential equations [such asMATH 320], probability [such asMATH 331] and programming in Python or MATLAB [such asCOMP SCI 220] is required.","requirements_text":"Graduate/professional standing"},{"run_id":"legacy-7774f45558276ec29bf626e58fffb4a27bdbb2a9","semester":"1264","observed_at":"2025-11-01 11:49:36.359151+00:00","record_version_id":"5bc263d502e36dfeeabd806f3e601c6ee3563389158275f3d8650c7acc194907","course_id":"ME 737","course_uid":"course_7ab6b3133883319bcb210142","catalog_version_id":"3d4e0fff7dbc919810e8e365ba10951b77100bad266069ff984d7e8eed834444","course_number":737,"subjects":["ME"],"title":"SCIENTIFIC COMPUTING AND MACHINE LEARNING FOR ENGINEERING APPLICATIONS","description":"Key computational topics for engineering applications will be discussed, encompassing both established classical numerical methods and the emerging field of machine learning. Knowledge of calculus [such asMATH 221], linear algebra and differential equations [such asMATH 320], probability [such asMATH 331] and programming in Python or MATLAB [such asCOMP SCI 220] is required.","requirements_text":"Graduate/professional standing"},{"run_id":"legacy-7ab7c5e783fc8ebef8b8ee8cea019ee37a72ce74","semester":"1262","observed_at":"2025-09-28 04:58:07.340658+00:00","record_version_id":"5844c413b720d6d297820e1afda65989a90599ab3472fd81e2799a21f3d621cd","course_id":"ME 737","course_uid":"course_7ab6b3133883319bcb210142","catalog_version_id":"3d4e0fff7dbc919810e8e365ba10951b77100bad266069ff984d7e8eed834444","course_number":737,"subjects":["ME"],"title":"SCIENTIFIC COMPUTING AND MACHINE LEARNING FOR ENGINEERING APPLICATIONS","description":"Key computational topics for engineering applications will be discussed, encompassing both established classical numerical methods and the emerging field of machine learning. Knowledge of calculus [such asMATH 221], linear algebra and differential equations [such asMATH 320], probability [such asMATH 331] and programming in Python or MATLAB [such asCOMP SCI 220] is required.","requirements_text":"Graduate/professional standing"},{"run_id":"legacy-7ca1175502be18eb51f7b016818a884a43fd4ebb","semester":"1262","observed_at":"2025-07-29 06:28:23.644795+00:00","record_version_id":"ab6480871f97910cfa439f3138aff082bb76167b8f39e72a55328d4f91ef97b5","course_id":"ME 737","course_uid":"course_7ab6b3133883319bcb210142","catalog_version_id":"3d4e0fff7dbc919810e8e365ba10951b77100bad266069ff984d7e8eed834444","course_number":737,"subjects":["ME"],"title":"SCIENTIFIC COMPUTING AND MACHINE LEARNING FOR ENGINEERING APPLICATIONS","description":"Key computational topics for engineering applications will be discussed, encompassing both established classical numerical methods and the emerging field of machine learning. Knowledge of calculus [such asMATH 221], linear algebra and differential equations [such asMATH 320], probability [such asMATH 331] and programming in Python or MATLAB [such asCOMP SCI 220] is required.","requirements_text":"Graduate/professional standing"},{"run_id":"legacy-82f31c08c746a214872494cde6ecaeb9330441b4","semester":"1262","observed_at":"2025-06-17 21:26:08.547156+00:00","record_version_id":"3a215636cca431a9eb30091ed7fbed2e8cce22d374c622029a170e45ed65ac75","course_id":"ME 737","course_uid":"course_7ab6b3133883319bcb210142","catalog_version_id":"3d4e0fff7dbc919810e8e365ba10951b77100bad266069ff984d7e8eed834444","course_number":737,"subjects":["ME"],"title":"SCIENTIFIC COMPUTING AND MACHINE LEARNING FOR ENGINEERING APPLICATIONS","description":"Key computational topics for engineering applications will be discussed, encompassing both established classical numerical methods and the emerging field of machine learning. Knowledge of calculus [such asMATH 221], linear algebra and differential equations [such asMATH 320], probability [such asMATH 331] and programming in Python or MATLAB [such asCOMP SCI 220] is required.","requirements_text":"Graduate/professional standing"},{"run_id":"legacy-84c248343c5a99ab42c5616c594812a5e3e31cbb","semester":"1262","observed_at":"2025-07-04 06:00:07.487827+00:00","record_version_id":"bb6cb04ad8bb29c27190a5c832a92725b5f6a1de3ff52f8322e0858d26cb9c60","course_id":"ME 737","course_uid":"course_7ab6b3133883319bcb210142","catalog_version_id":"3d4e0fff7dbc919810e8e365ba10951b77100bad266069ff984d7e8eed834444","course_number":737,"subjects":["ME"],"title":"SCIENTIFIC COMPUTING AND MACHINE LEARNING FOR ENGINEERING APPLICATIONS","description":"Key computational topics for engineering applications will be discussed, encompassing both established classical numerical methods and the emerging field of machine learning. Knowledge of calculus [such asMATH 221], linear algebra and differential equations [such asMATH 320], probability [such asMATH 331] and programming in Python or MATLAB [such asCOMP SCI 220] is required.","requirements_text":"Graduate/professional standing"},{"run_id":"legacy-86d941366886c9a14a2581c04e20d0bdd25e1b02","semester":"1262","observed_at":"2025-08-31 04:54:14.656039+00:00","record_version_id":"80baa2d31f1f24b3c441331cb2b0de67f262c952ff2805c6cd2bdd747ff210e0","course_id":"ME 737","course_uid":"course_7ab6b3133883319bcb210142","catalog_version_id":"3d4e0fff7dbc919810e8e365ba10951b77100bad266069ff984d7e8eed834444","course_number":737,"subjects":["ME"],"title":"SCIENTIFIC COMPUTING AND MACHINE LEARNING FOR ENGINEERING APPLICATIONS","description":"Key computational topics for engineering applications will be discussed, encompassing both established classical numerical methods and the emerging field of machine learning. Knowledge of calculus [such asMATH 221], linear algebra and differential equations [such asMATH 320], probability [such asMATH 331] and programming in Python or MATLAB [such asCOMP SCI 220] is required.","requirements_text":"Graduate/professional standing"},{"run_id":"legacy-8ba1d2e6cfbb1525b4f9f769ec164fb6ad0f237a","semester":"1262","observed_at":"2025-06-02 05:22:45.010398+00:00","record_version_id":"4ab0082a01bfe01b6c84c621d38f198b3a408c64a134df1ad3d0026ec2c78618","course_id":"ME 737","course_uid":"course_7ab6b3133883319bcb210142","catalog_version_id":"3d4e0fff7dbc919810e8e365ba10951b77100bad266069ff984d7e8eed834444","course_number":737,"subjects":["ME"],"title":"SCIENTIFIC COMPUTING AND MACHINE LEARNING FOR ENGINEERING APPLICATIONS","description":"Key computational topics for engineering applications will be discussed, encompassing both established classical numerical methods and the emerging field of machine learning. Knowledge of calculus [such asMATH 221], linear algebra and differential equations [such asMATH 320], probability [such asMATH 331] and programming in Python or MATLAB [such asCOMP SCI 220] is required.","requirements_text":"Graduate/professional standing"},{"run_id":"legacy-92d960aa7e4cd6e4c9ac8b2e232092904038e9e4","semester":"1262","observed_at":"2025-06-08 01:50:46.451351+00:00","record_version_id":"12228711a02c55afcbb5be874fc9b0b40db6b08a5835f7d06cc8c1baf151ee04","course_id":"ME 737","course_uid":"course_7ab6b3133883319bcb210142","catalog_version_id":"3d4e0fff7dbc919810e8e365ba10951b77100bad266069ff984d7e8eed834444","course_number":737,"subjects":["ME"],"title":"SCIENTIFIC COMPUTING AND MACHINE LEARNING FOR ENGINEERING APPLICATIONS","description":"Key computational topics for engineering applications will be discussed, encompassing both established classical numerical methods and the emerging field of machine learning. Knowledge of calculus [such asMATH 221], linear algebra and differential equations [such asMATH 320], probability [such asMATH 331] and programming in Python or MATLAB [such asCOMP SCI 220] is required.","requirements_text":"Graduate/professional standing"},{"run_id":"legacy-9dd575e013c5c6e000ab3ad2d1288cc1dd9c96dc","semester":"1264","observed_at":"2025-12-21 04:47:46.589081+00:00","record_version_id":"6d58aa58ab519506ea887908659297884cf7b124349b32973363963627e3663a","course_id":"ME 737","course_uid":"course_7ab6b3133883319bcb210142","catalog_version_id":"3d4e0fff7dbc919810e8e365ba10951b77100bad266069ff984d7e8eed834444","course_number":737,"subjects":["ME"],"title":"SCIENTIFIC COMPUTING AND MACHINE LEARNING FOR ENGINEERING APPLICATIONS","description":"Key computational topics for engineering applications will be discussed, encompassing both established classical numerical methods and the emerging field of machine learning. Knowledge of calculus [such asMATH 221], linear algebra and differential equations [such asMATH 320], probability [such asMATH 331] and programming in Python or MATLAB [such asCOMP SCI 220] is required.","requirements_text":"Graduate/professional standing"},{"run_id":"legacy-b285d591f6acf3aa1910e02edc297664db86eb8c","semester":"1262","observed_at":"2025-06-10 22:48:22.460295+00:00","record_version_id":"a28c83fff33b0efb6a7a34e3f7f5b1aaac7d782de97aa852f431ee6c95507566","course_id":"ME 737","course_uid":"course_7ab6b3133883319bcb210142","catalog_version_id":"3d4e0fff7dbc919810e8e365ba10951b77100bad266069ff984d7e8eed834444","course_number":737,"subjects":["ME"],"title":"SCIENTIFIC COMPUTING AND MACHINE LEARNING FOR ENGINEERING APPLICATIONS","description":"Key computational topics for engineering applications will be discussed, encompassing both established classical numerical methods and the emerging field of machine learning. Knowledge of calculus [such asMATH 221], linear algebra and differential equations [such asMATH 320], probability [such asMATH 331] and programming in Python or MATLAB [such asCOMP SCI 220] is required.","requirements_text":"Graduate/professional standing"},{"run_id":"legacy-b89e05b94730c6471439082d9279c0a834a4aeec","semester":"1262","observed_at":"2025-08-26 20:25:42.325239+00:00","record_version_id":"1bb77f2e5b2038d567eb52385a9cc525d6b0407b3410c6ff43833805b77b96f7","course_id":"ME 737","course_uid":"course_7ab6b3133883319bcb210142","catalog_version_id":"3d4e0fff7dbc919810e8e365ba10951b77100bad266069ff984d7e8eed834444","course_number":737,"subjects":["ME"],"title":"SCIENTIFIC COMPUTING AND MACHINE LEARNING FOR ENGINEERING APPLICATIONS","description":"Key computational topics for engineering applications will be discussed, encompassing both established classical numerical methods and the emerging field of machine learning. Knowledge of calculus [such asMATH 221], linear algebra and differential equations [such asMATH 320], probability [such asMATH 331] and programming in Python or MATLAB [such asCOMP SCI 220] is required.","requirements_text":"Graduate/professional standing"},{"run_id":"legacy-b9279a12d1f2688df9e556183c94d41a89e431dc","semester":"1262","observed_at":"2025-07-06 01:49:47.203835+00:00","record_version_id":"ec8c3b877165b4dfbb3e51a28f5afbe8913b320e584062c5e661784054a8d6dd","course_id":"ME 737","course_uid":"course_7ab6b3133883319bcb210142","catalog_version_id":"3d4e0fff7dbc919810e8e365ba10951b77100bad266069ff984d7e8eed834444","course_number":737,"subjects":["ME"],"title":"SCIENTIFIC COMPUTING AND MACHINE LEARNING FOR ENGINEERING APPLICATIONS","description":"Key computational topics for engineering applications will be discussed, encompassing both established classical numerical methods and the emerging field of machine learning. Knowledge of calculus [such asMATH 221], linear algebra and differential equations [such asMATH 320], probability [such asMATH 331] and programming in Python or MATLAB [such asCOMP SCI 220] is required.","requirements_text":"Graduate/professional standing"},{"run_id":"legacy-bbdc905e96cc681a5e9a8b02c795b682206e36d1","semester":"1262","observed_at":"2025-06-25 08:02:45.445730+00:00","record_version_id":"0c91d2c21702c81e94282c0a5499b20ef85371206e9499f91ad54638c6123890","course_id":"ME 737","course_uid":"course_7ab6b3133883319bcb210142","catalog_version_id":"3d4e0fff7dbc919810e8e365ba10951b77100bad266069ff984d7e8eed834444","course_number":737,"subjects":["ME"],"title":"SCIENTIFIC COMPUTING AND MACHINE LEARNING FOR ENGINEERING APPLICATIONS","description":"Key computational topics for engineering applications will be discussed, encompassing both established classical numerical methods and the emerging field of machine learning. Knowledge of calculus [such asMATH 221], linear algebra and differential equations [such asMATH 320], probability [such asMATH 331] and programming in Python or MATLAB [such asCOMP SCI 220] is required.","requirements_text":"Graduate/professional standing"},{"run_id":"legacy-c6b62be45f8a13cba109ef2a7741b9cd9a6b8272","semester":"1262","observed_at":"2025-08-24 08:48:09.035112+00:00","record_version_id":"d0601199f2929f0fb5db7ecc3d85721ae2160ed2d39fa6115818328b3a452862","course_id":"ME 737","course_uid":"course_7ab6b3133883319bcb210142","catalog_version_id":"3d4e0fff7dbc919810e8e365ba10951b77100bad266069ff984d7e8eed834444","course_number":737,"subjects":["ME"],"title":"SCIENTIFIC COMPUTING AND MACHINE LEARNING FOR ENGINEERING APPLICATIONS","description":"Key computational topics for engineering applications will be discussed, encompassing both established classical numerical methods and the emerging field of machine learning. Knowledge of calculus [such asMATH 221], linear algebra and differential equations [such asMATH 320], probability [such asMATH 331] and programming in Python or MATLAB [such asCOMP SCI 220] is required.","requirements_text":"Graduate/professional standing"},{"run_id":"legacy-d33818a01b6b4c5e2902e704da6e5b713742d4dc","semester":"1262","observed_at":"2025-10-13 10:46:24.251475+00:00","record_version_id":"4b4f400f2a0465595e0b2225f4317e7fb0b373cbcfbc5fb322eebd9bb0321ea4","course_id":"ME 737","course_uid":"course_7ab6b3133883319bcb210142","catalog_version_id":"3d4e0fff7dbc919810e8e365ba10951b77100bad266069ff984d7e8eed834444","course_number":737,"subjects":["ME"],"title":"SCIENTIFIC COMPUTING AND MACHINE LEARNING FOR ENGINEERING APPLICATIONS","description":"Key computational topics for engineering applications will be discussed, encompassing both established classical numerical methods and the emerging field of machine learning. Knowledge of calculus [such asMATH 221], linear algebra and differential equations [such asMATH 320], probability [such asMATH 331] and programming in Python or MATLAB [such asCOMP SCI 220] is required.","requirements_text":"Graduate/professional standing"},{"run_id":"legacy-d3c17db9832d3064916046caf891dd23f10b1bb9","semester":"1262","observed_at":"2025-08-26 11:30:42.288639+00:00","record_version_id":"077e6e835dd2a9969866a675cd98d340a2518e9576675db2f0ca4450824b1387","course_id":"ME 737","course_uid":"course_7ab6b3133883319bcb210142","catalog_version_id":"3d4e0fff7dbc919810e8e365ba10951b77100bad266069ff984d7e8eed834444","course_number":737,"subjects":["ME"],"title":"SCIENTIFIC COMPUTING AND MACHINE LEARNING FOR ENGINEERING APPLICATIONS","description":"Key computational topics for engineering applications will be discussed, encompassing both established classical numerical methods and the emerging field of machine learning. Knowledge of calculus [such asMATH 221], linear algebra and differential equations [such asMATH 320], probability [such asMATH 331] and programming in Python or MATLAB [such asCOMP SCI 220] is required.","requirements_text":"Graduate/professional standing"},{"run_id":"legacy-d4ee226dc44268e9b6767fb9f5f20343322f494b","semester":"1262","observed_at":"2025-06-15 01:52:23.911697+00:00","record_version_id":"b4e42bdd1eccdd4bb5030760d37c1ef7a488455a105787c4ec6185713a5da2d2","course_id":"ME 737","course_uid":"course_7ab6b3133883319bcb210142","catalog_version_id":"3d4e0fff7dbc919810e8e365ba10951b77100bad266069ff984d7e8eed834444","course_number":737,"subjects":["ME"],"title":"SCIENTIFIC COMPUTING AND MACHINE LEARNING FOR ENGINEERING APPLICATIONS","description":"Key computational topics for engineering applications will be discussed, encompassing both established classical numerical methods and the emerging field of machine learning. Knowledge of calculus [such asMATH 221], linear algebra and differential equations [such asMATH 320], probability [such asMATH 331] and programming in Python or MATLAB [such asCOMP SCI 220] is required.","requirements_text":"Graduate/professional standing"},{"run_id":"legacy-dbe5f2d24b48c3177297a3d69c553cc9d1194bac","semester":"1262","observed_at":"2025-09-14 05:00:27.366070+00:00","record_version_id":"7a64849e005003206351c4bfc3549d2ed468bfbcb9f70dc22eee146173a9b183","course_id":"ME 737","course_uid":"course_7ab6b3133883319bcb210142","catalog_version_id":"3d4e0fff7dbc919810e8e365ba10951b77100bad266069ff984d7e8eed834444","course_number":737,"subjects":["ME"],"title":"SCIENTIFIC COMPUTING AND MACHINE LEARNING FOR ENGINEERING APPLICATIONS","description":"Key computational topics for engineering applications will be discussed, encompassing both established classical numerical methods and the emerging field of machine learning. Knowledge of calculus [such asMATH 221], linear algebra and differential equations [such asMATH 320], probability [such asMATH 331] and programming in Python or MATLAB [such asCOMP SCI 220] is required.","requirements_text":"Graduate/professional standing"},{"run_id":"legacy-dd357dc2758e9e282c30988a527ce37de92593b9","semester":"1264","observed_at":"2025-10-19 01:39:41.951404+00:00","record_version_id":"ac16b028183223699e62650d00ae2d450ad311a96f950690618e91d8cbf76093","course_id":"ME 737","course_uid":"course_7ab6b3133883319bcb210142","catalog_version_id":"3d4e0fff7dbc919810e8e365ba10951b77100bad266069ff984d7e8eed834444","course_number":737,"subjects":["ME"],"title":"SCIENTIFIC COMPUTING AND MACHINE LEARNING FOR ENGINEERING APPLICATIONS","description":"Key computational topics for engineering applications will be discussed, encompassing both established classical numerical methods and the emerging field of machine learning. Knowledge of calculus [such asMATH 221], linear algebra and differential equations [such asMATH 320], probability [such asMATH 331] and programming in Python or MATLAB [such asCOMP SCI 220] is required.","requirements_text":"Graduate/professional standing"},{"run_id":"legacy-de74de559e409a3fe668685e28043b888d2e6841","semester":"1262","observed_at":"2025-06-27 07:38:50.882897+00:00","record_version_id":"dc5a3ac900e65d079e7f304b7e5a3876af851ea894b385239553fb4cf945ad37","course_id":"ME 737","course_uid":"course_7ab6b3133883319bcb210142","catalog_version_id":"3d4e0fff7dbc919810e8e365ba10951b77100bad266069ff984d7e8eed834444","course_number":737,"subjects":["ME"],"title":"SCIENTIFIC COMPUTING AND MACHINE LEARNING FOR ENGINEERING APPLICATIONS","description":"Key computational topics for engineering applications will be discussed, encompassing both established classical numerical methods and the emerging field of machine learning. Knowledge of calculus [such asMATH 221], linear algebra and differential equations [such asMATH 320], probability [such asMATH 331] and programming in Python or MATLAB [such asCOMP SCI 220] is required.","requirements_text":"Graduate/professional standing"},{"run_id":"legacy-deca7188cf536ade3203cd88b52a45e92a059617","semester":"1262","observed_at":"2025-06-27 00:37:46.087071+00:00","record_version_id":"6d87d2dbea36ca0cebfd623fff5218528a275711187f237fd0e4c08a56e0bf25","course_id":"ME 737","course_uid":"course_7ab6b3133883319bcb210142","catalog_version_id":"3d4e0fff7dbc919810e8e365ba10951b77100bad266069ff984d7e8eed834444","course_number":737,"subjects":["ME"],"title":"SCIENTIFIC COMPUTING AND MACHINE LEARNING FOR ENGINEERING APPLICATIONS","description":"Key computational topics for engineering applications will be discussed, encompassing both established classical numerical methods and the emerging field of machine learning. Knowledge of calculus [such asMATH 221], linear algebra and differential equations [such asMATH 320], probability [such asMATH 331] and programming in Python or MATLAB [such asCOMP SCI 220] is required.","requirements_text":"Graduate/professional standing"},{"run_id":"legacy-e339da2d849aaf8bb4dceca07a84728af23cf755","semester":"1262","observed_at":"2025-07-23 08:49:22.748925+00:00","record_version_id":"99fef918a7634ee5e15efb5d5f0ff26895b1eeef1efab7a0ab13cfa47516df26","course_id":"ME 737","course_uid":"course_7ab6b3133883319bcb210142","catalog_version_id":"3d4e0fff7dbc919810e8e365ba10951b77100bad266069ff984d7e8eed834444","course_number":737,"subjects":["ME"],"title":"SCIENTIFIC COMPUTING AND MACHINE LEARNING FOR ENGINEERING APPLICATIONS","description":"Key computational topics for engineering applications will be discussed, encompassing both established classical numerical methods and the emerging field of machine learning. Knowledge of calculus [such asMATH 221], linear algebra and differential equations [such asMATH 320], probability [such asMATH 331] and programming in Python or MATLAB [such asCOMP SCI 220] is required.","requirements_text":"Graduate/professional standing"},{"run_id":"legacy-ef471690c082448deebd2687eab84b0b78813c36","semester":"1262","observed_at":"2025-06-29 01:47:56.317645+00:00","record_version_id":"9fdd0c121e594e0f62897b84154ea48aec006ed8741879c54799e7e31354e99c","course_id":"ME 737","course_uid":"course_7ab6b3133883319bcb210142","catalog_version_id":"3d4e0fff7dbc919810e8e365ba10951b77100bad266069ff984d7e8eed834444","course_number":737,"subjects":["ME"],"title":"SCIENTIFIC COMPUTING AND MACHINE LEARNING FOR ENGINEERING APPLICATIONS","description":"Key computational topics for engineering applications will be discussed, encompassing both established classical numerical methods and the emerging field of machine learning. Knowledge of calculus [such asMATH 221], linear algebra and differential equations [such asMATH 320], probability [such asMATH 331] and programming in Python or MATLAB [such asCOMP SCI 220] is required.","requirements_text":"Graduate/professional standing"},{"run_id":"legacy-efc4e8e2cd7c3f68e059a308990c00c77c7611eb","semester":"1264","observed_at":"2025-10-16 05:48:13.935141+00:00","record_version_id":"b3e370ef9b2b026a7add0a77e36e4f715ac9a62b9ec61c0115180ee375936c02","course_id":"ME 737","course_uid":"course_7ab6b3133883319bcb210142","catalog_version_id":"3d4e0fff7dbc919810e8e365ba10951b77100bad266069ff984d7e8eed834444","course_number":737,"subjects":["ME"],"title":"SCIENTIFIC COMPUTING AND MACHINE LEARNING FOR ENGINEERING APPLICATIONS","description":"Key computational topics for engineering applications will be discussed, encompassing both established classical numerical methods and the emerging field of machine learning. Knowledge of calculus [such asMATH 221], linear algebra and differential equations [such asMATH 320], probability [such asMATH 331] and programming in Python or MATLAB [such asCOMP SCI 220] is required.","requirements_text":"Graduate/professional standing"}]