# STAT 453: Introduction to Deep Learning and Generative Models | UW–Madison [View on UW Courses](https://uwcourses.com/courses/STAT_453) ## Dataset ### revision e243353dcb7d79b7247ced91d69443ef4c2a6349 ### repository twangodev/uwcourses ### schema version 6 ### importer version 7 ### projection id 52a78527ff09011d88cb04c7d43867d9fbfec2930bf1dd2ec359ebd2844e0b07 ### observed at 2026-09-07T15:55:43.033547+00:00 ### built at 2026-09-10T19:50:42.743001+00:00 ### courses 8951 ### current instructors 5754 ### limited false ### terms * 1272 * 1264 * 1262 * 1254 * 1252 * 1244 * 1242 * 1234 * 1232 * 1224 * 1222 * 1212 * 1204 * 1202 * 1194 * 1192 * 1184 * 1182 * 1174 * 1172 * 1164 * 1162 * 1154 * 1152 * 1144 * 1142 * 1134 * 1132 * 1124 * 1122 * 1114 * 1112 * 1104 * 1102 * 1094 * 1092 * 1084 * 1082 * 1074 * 1072 ### term 1272 ### departments | subject | count | | --------- | ----- | | AAE | 90 | | ABT | 20 | | ACCTIS | 36 | | ACTSCI | 14 | | AFAERO | 10 | | AFRICAN | 87 | | AFROAMER | 71 | | AGROECOL | 21 | | AMERIND | 53 | | ANAT\&PHY | 7 | | ANATOMY | 2 | | ANESTHES | 8 | | ANSCI | 57 | | ANTHRO | 95 | | ART | 125 | | ARTED | 10 | | ARTHIST | 121 | | ASIALANG | 129 | | ASIAN | 109 | | ASIANAM | 28 | | ASTRON | 38 | | ATMOCN | 69 | | BIOCHEM | 51 | | BIOCORE | 10 | | BIOLOGY | 14 | | BIOMDSCI | 18 | | BME | 66 | | BMI | 41 | | BMOLCHEM | 10 | | BOTANY | 69 | | BSE | 44 | | C\&ESOC | 73 | | CBE | 48 | | CHEM | 101 | | CHICLA | 52 | | CIVENGR | 133 | | CLASSICS | 47 | | CNP | 10 | | CNSRSCI | 50 | | COMARTS | 137 | | COMPBIO | 15 | | COMPLIT | 11 | | COMPSCI | 138 | | COUNPSY | 78 | | CRB | 19 | | CS\&D | 71 | | CSCS | 40 | | CURRIC | 193 | | DANCE | 93 | | DERM | 8 | | DS | 88 | | DYSCI | 35 | | ECE | 155 | | ECON | 145 | | EDPOL | 114 | | EDPSYCH | 97 | | ELPA | 70 | | EMA | 53 | | EMERMED | 17 | | ENGL | 206 | | ENTOM | 40 | | ENVIRST | 148 | | EP | 15 | | EPD | 67 | | ESL | 16 | | F\&WECOL | 60 | | FAMMED | 22 | | FINANCE | 50 | | FOLKLORE | 40 | | FOODSCI | 43 | | FRENCH | 63 | | GEN\&WS | 145 | | GENBUS | 72 | | GENECSLR | 17 | | GENETICS | 60 | | GEOG | 113 | | GEOSCI | 83 | | GERMAN | 82 | | GLE | 48 | | GNS | 38 | | GREEK | 27 | | HDFS | 41 | | HEBR-BIB | 13 | | HEBR-MOD | 10 | | HISTORY | 233 | | HISTSCI | 56 | | HONCOL | 13 | | ILS | 43 | | INFOSYS | 9 | | INTEGART | 7 | | INTEGSCI | 22 | | INTER-AG | 18 | | INTER-HE | 11 | | INTER-LS | 22 | | INTEREGR | 16 | | INTLBUS | 21 | | INTLST | 50 | | ISYE | 83 | | ITALIAN | 53 | | JEWISH | 56 | | JOURN | 88 | | KINES | 128 | | LACIS | 26 | | LANDARC | 61 | | LATIN | 24 | | LAW | 120 | | LEGALST | 48 | | LINGUIS | 35 | | LIS | 89 | | LITTRANS | 78 | | LSC | 52 | | M\&ENVTOX | 7 | | MARKETNG | 62 | | MATH | 153 | | MDGENET | 8 | | ME | 130 | | MEDHIST | 43 | | MEDICINE | 60 | | MEDIEVAL | 32 | | MEDPHYS | 39 | | MEDSC-M | 29 | | MEDSC-V | 41 | | MHR | 68 | | MICROBIO | 45 | | MILSCI | 16 | | MM\&I | 22 | | MOLBIOL | 6 | | MS\&E | 59 | | MUSIC | 165 | | MUSPERF | 126 | | NAVSCI | 20 | | NE | 44 | | NEURODPT | 11 | | NEUROL | 7 | | NEURSURG | 4 | | NTP | 11 | | NURSING | 111 | | NUTRSCI | 65 | | OBS\&GYN | 18 | | OCCTHER | 39 | | ONCOLOGY | 14 | | OPHTHALM | 5 | | OTM | 43 | | PATH | 34 | | PATH-BIO | 29 | | PEDIAT | 26 | | PHARMACY | 31 | | PHILOS | 77 | | PHMCOL-M | 11 | | PHMPRAC | 45 | | PHMSCI | 60 | | PHYASST | 37 | | PHYSICS | 88 | | PHYSIOL | 3 | | PHYTHER | 37 | | PLANTSCI | 52 | | PLPATH | 35 | | POLISCI | 192 | | POPHLTH | 58 | | PORTUG | 33 | | PSYCH | 101 | | PSYCHIAT | 22 | | PUBAFFR | 54 | | PUBLHLTH | 23 | | RADIOL | 11 | | REALEST | 41 | | RELIGST | 90 | | RHABMED | 9 | | RMI | 24 | | RP\&SE | 102 | | S\&APHM | 17 | | SCANDST | 73 | | SLAVIC | 89 | | SOC | 149 | | SOCWORK | 87 | | SOILSCI | 46 | | SPANISH | 83 | | SRMED | 21 | | STAT | 94 | | STDYABRD | 52 | | STS | 8 | | SURGERY | 25 | | SURGSCI | 33 | | THEATRE | 91 | | URBRPL | 60 | | UROLOGY | 5 | | ZOOLOGY | 89 | ## course ### run id 20260907T155543-ce3781c4 ### semester 1272 ### observed at 2026-09-07 15:55:43.033547+00:00 ### record version id cb151214aa370ed887f5d181ade656f596ce201a9d851c1344bb67cde8ff1382 ### course id STAT 453 ### course uid course\_b9ca05f3e5db5af2eb30f64a ### catalog version id a6af79cfe3d1ca0547bc5c61053fe1691c5a434428388f3e54b9d0ea82821dd7 ### course number 453 ### subjects * STAT ### title INTRODUCTION TO DEEP LEARNING AND GENERATIVE MODELS ### description Deep learning is a field that specializes in discovering and extracting intricate structures in large, unstructured datasets for parameterizing artificial neural networks with many layers. Since deep learning has pushed the state-of-the-art in many research and application areas, it's become indispensable for modern technology. Focuses on a understanding deep, artificial neural networks by connecting it to related concepts in statistics. Beyond covering deep learning models for predictive modeling, focus on deep generative models. Besides explanations on a mathematical and conceptual level, emphasize the practical aspects of deep learning. Open-source computing provides hands-on experience for implementing deep neural nets, working on supervised learning tasks, and applying generative models for dataset synthesis. ### requirements text MATH 320,321,340,341,345,375, graduate/professional standing, or declared in Statistics VISP ### credits min 3 ### credits max 3 ### credit offering ids * 1272:932:025597 ### llm job id enrich-8b774950c2b6adfdc46d1b82 ### llm output id 3b928b9e469c032827061a90373cb2263e1b2d35f2f4743c4f734666eac294e2 ### llm model nvidia/Qwen3.6-35B-A3B-NVFP4 ### llm model revision 1355db6a052410cfd62085d94b58866fd0f2c3c5 ### llm task version 14 ### llm search status valid ### llm summary Introduction to deep learning and generative models connecting neural networks to statistical concepts. ### llm topics * Predictive modeling * Deep generative models * Artificial neural networks ### llm skills * Implementing deep neural networks * Applying generative models * Supervised learning tasks ### llm assumed background * Linear algebra and multivariable calculus * Programming and computational implementation ### llm search phrases * deep learning course * generative models statistics * neural networks math background * STAT 453 prerequisites ### llm requirements status valid ### llm student summary status valid ### llm experience status insufficient\_evidence ### catalog variants None recorded. ### student summary #### context hash d085c42130f56558838212596d0aa5e95eacf040e0dd85e3a7b51400fceae487 #### course id STAT 453 #### current instructors ```json [ { "instructor_uid": "instructor_4270353ff74ae497a4f645e4", "message": "No course-specific reviews available", "name": "Baiheng Chen", "review_status": "no_course_reviews", "rmp_instructor_id": null, "summary": [ { "citations": [ { "course_id": "STAT 453", "run_id": "20260907T155543-ce3781c4", "section_number": 1, "source_course_id": "9687c303-6cbb-39b1-9ffb-0b9254ce24bc", "source_record": { "entity_id": "9687c303-6cbb-39b1-9ffb-0b9254ce24bc", "file": "tables/observations.parquet", "kind": "grades", "source": "madgrades" }, "table": "section_grades_latest", "term_id": "1262", "type": "grade" }, { "course_id": "STAT 453", "run_id": "20260907T155543-ce3781c4", "section_number": 2, "source_course_id": "9687c303-6cbb-39b1-9ffb-0b9254ce24bc", "source_record": { "entity_id": "9687c303-6cbb-39b1-9ffb-0b9254ce24bc", "file": "tables/observations.parquet", "kind": "grades", "source": "madgrades" }, "table": "section_grades_latest", "term_id": "1262", "type": "grade" } ], "text": "Recent recorded grades — Fall 2025: 3.91 GPA, 95.4% A/AB (n=87 letter grades). Includes jointly taught sections." } ] }, { "instructor_uid": "instructor_816ff1547ceb6ebc8284e15f", "message": "No course-specific reviews available", "name": "Benjamin Lengerich", "review_status": "no_course_reviews", "rmp_instructor_id": null, "summary": [ { "citations": [ { "course_id": "STAT 453", "run_id": "20260907T155543-ce3781c4", "section_number": 1, "source_course_id": "9687c303-6cbb-39b1-9ffb-0b9254ce24bc", "source_record": { "entity_id": "9687c303-6cbb-39b1-9ffb-0b9254ce24bc", "file": "tables/observations.parquet", "kind": "grades", "source": "madgrades" }, "table": "section_grades_latest", "term_id": "1262", "type": "grade" }, { "course_id": "STAT 453", "run_id": "20260907T155543-ce3781c4", "section_number": 2, "source_course_id": "9687c303-6cbb-39b1-9ffb-0b9254ce24bc", "source_record": { "entity_id": "9687c303-6cbb-39b1-9ffb-0b9254ce24bc", "file": "tables/observations.parquet", "kind": "grades", "source": "madgrades" }, "table": "section_grades_latest", "term_id": "1262", "type": "grade" } ], "text": "Recent recorded grades — Fall 2025: 3.91 GPA, 95.4% A/AB (n=87 letter grades). Includes jointly taught sections." } ] } ] ``` #### difficulty workload Historical reviews of Yiqiao Zhong: Reviewers note low overall workload, though exams can be confusing if lecture concepts are not understood. One student found the difficulty manageable with effort, while another cited flexible deadlines and fine tests. ```json { "citations": [ { "instructor_name": "Yiqiao Zhong", "review_date": "2024-05-07 09:52:37 +0000 UTC", "review_id": "1214b9801760e077473ae090", "run_id": "20260907T155543-ce3781c4", "source_instructor_id": "rmp:2889232", "source_review_id": "UmF0aW5nLTM5Mzg4OTE4", "source_url": "https://www.ratemyprofessors.com/professor/2889232", "type": "review" }, { "instructor_name": "Yiqiao Zhong", "review_date": "2025-05-09 17:47:23 +0000 UTC", "review_id": "a26e2fa8c871ae1797eb8560", "run_id": "20260907T155543-ce3781c4", "source_instructor_id": "rmp:2889232", "source_review_id": "UmF0aW5nLTQxMjI3NzA0", "source_url": "https://www.ratemyprofessors.com/professor/2889232", "type": "review" } ] } ``` #### errors None recorded. #### historical context Historical reviews of Yiqiao Zhong: Yiqiao Zhong receives mixed reviews regarding lecture quality, with some students finding them unprepared and difficult to follow while one reviewer praises them. Grading is frequently described as arbitrary and lacking clear rubrics, particularly for projects, though one student found the exams easy. Workload is generally considered manageable, and flexibility with deadlines is noted by at least one reviewer. ```json { "citations": [ { "instructor_name": "Yiqiao Zhong", "review_date": "2023-03-21 21:50:09 +0000 UTC", "review_id": "ef4d09bf13bd1313defe0402", "run_id": "20260907T155543-ce3781c4", "source_instructor_id": "rmp:2889232", "source_review_id": "UmF0aW5nLTM3NTI1Njg1", "source_url": "https://www.ratemyprofessors.com/professor/2889232", "type": "review" }, { "instructor_name": "Yiqiao Zhong", "review_date": "2024-03-18 06:13:51 +0000 UTC", "review_id": "a79d88db6cc12edea799601b", "run_id": "20260907T155543-ce3781c4", "source_instructor_id": "rmp:2889232", "source_review_id": "UmF0aW5nLTM5MDU4OTU5", "source_url": "https://www.ratemyprofessors.com/professor/2889232", "type": "review" }, { "instructor_name": "Yiqiao Zhong", "review_date": "2024-05-07 09:52:37 +0000 UTC", "review_id": "1214b9801760e077473ae090", "run_id": "20260907T155543-ce3781c4", "source_instructor_id": "rmp:2889232", "source_review_id": "UmF0aW5nLTM5Mzg4OTE4", "source_url": "https://www.ratemyprofessors.com/professor/2889232", "type": "review" }, { "instructor_name": "Yiqiao Zhong", "review_date": "2024-05-13 15:55:58 +0000 UTC", "review_id": "85dc11bca0cfaa198d670778", "run_id": "20260907T155543-ce3781c4", "source_instructor_id": "rmp:2889232", "source_review_id": "UmF0aW5nLTM5NDQ5ODA0", "source_url": "https://www.ratemyprofessors.com/professor/2889232", "type": "review" }, { "instructor_name": "Yiqiao Zhong", "review_date": "2025-01-19 21:55:16 +0000 UTC", "review_id": "6979012806b97331fbc17efe", "run_id": "20260907T155543-ce3781c4", "source_instructor_id": "rmp:2889232", "source_review_id": "UmF0aW5nLTQwNTczOTIy", "source_url": "https://www.ratemyprofessors.com/professor/2889232", "type": "review" }, { "instructor_name": "Yiqiao Zhong", "review_date": "2025-03-13 02:00:17 +0000 UTC", "review_id": "75b712cd23922fa37293194c", "run_id": "20260907T155543-ce3781c4", "source_instructor_id": "rmp:2889232", "source_review_id": "UmF0aW5nLTQwNzY1MjM0", "source_url": "https://www.ratemyprofessors.com/professor/2889232", "type": "review" }, { "instructor_name": "Yiqiao Zhong", "review_date": "2025-05-09 17:47:23 +0000 UTC", "review_id": "a26e2fa8c871ae1797eb8560", "run_id": "20260907T155543-ce3781c4", "source_instructor_id": "rmp:2889232", "source_review_id": "UmF0aW5nLTQxMjI3NzA0", "source_url": "https://www.ratemyprofessors.com/professor/2889232", "type": "review" }, { "instructor_name": "Yiqiao Zhong", "review_date": "2025-05-18 03:55:49 +0000 UTC", "review_id": "d1f2a590c6f34a3df8dbf4f0", "run_id": "20260907T155543-ce3781c4", "source_instructor_id": "rmp:2889232", "source_review_id": "UmF0aW5nLTQxMzE0NjM2", "source_url": "https://www.ratemyprofessors.com/professor/2889232", "type": "review" }, { "instructor_name": "Yiqiao Zhong", "review_date": "2026-05-12 15:33:53 +0000 UTC", "review_id": "062faa3be86494531f41dd29", "run_id": "20260907T155543-ce3781c4", "source_instructor_id": "rmp:2889232", "source_review_id": "UmF0aW5nLTQzMTAzOTEx", "source_url": "https://www.ratemyprofessors.com/professor/2889232", "type": "review" } ] } ``` #### offered true #### profile hash 5cb4dabf887cdbcd8c00d5a1312e10828b95c63f30bc3ea76aea199565390d02 #### quick take Historical reviews for Yiqiao Zhong describe lectures as unhelpful, vague, and difficult to follow, with arbitrary grading and missing rubrics. While one student found him flexible and nice, the majority report a frustrating experience requiring significant self-study. ```json { "citations": [ { "instructor_name": "Yiqiao Zhong", "review_date": "2023-03-21 21:50:09 +0000 UTC", "review_id": "ef4d09bf13bd1313defe0402", "run_id": "20260907T155543-ce3781c4", "source_instructor_id": "rmp:2889232", "source_review_id": "UmF0aW5nLTM3NTI1Njg1", "source_url": "https://www.ratemyprofessors.com/professor/2889232", "type": "review" }, { "instructor_name": "Yiqiao Zhong", "review_date": "2024-03-18 06:13:51 +0000 UTC", "review_id": "a79d88db6cc12edea799601b", "run_id": "20260907T155543-ce3781c4", "source_instructor_id": "rmp:2889232", "source_review_id": "UmF0aW5nLTM5MDU4OTU5", "source_url": "https://www.ratemyprofessors.com/professor/2889232", "type": "review" }, { "instructor_name": "Yiqiao Zhong", "review_date": "2024-05-07 09:52:37 +0000 UTC", "review_id": "1214b9801760e077473ae090", "run_id": "20260907T155543-ce3781c4", "source_instructor_id": "rmp:2889232", "source_review_id": "UmF0aW5nLTM5Mzg4OTE4", "source_url": "https://www.ratemyprofessors.com/professor/2889232", "type": "review" }, { "instructor_name": "Yiqiao Zhong", "review_date": "2024-05-13 15:55:58 +0000 UTC", "review_id": "85dc11bca0cfaa198d670778", "run_id": "20260907T155543-ce3781c4", "source_instructor_id": "rmp:2889232", "source_review_id": "UmF0aW5nLTM5NDQ5ODA0", "source_url": "https://www.ratemyprofessors.com/professor/2889232", "type": "review" }, { "instructor_name": "Yiqiao Zhong", "review_date": "2025-01-19 21:55:16 +0000 UTC", "review_id": "6979012806b97331fbc17efe", "run_id": "20260907T155543-ce3781c4", "source_instructor_id": "rmp:2889232", "source_review_id": "UmF0aW5nLTQwNTczOTIy", "source_url": "https://www.ratemyprofessors.com/professor/2889232", "type": "review" }, { "instructor_name": "Yiqiao Zhong", "review_date": "2025-03-13 02:00:17 +0000 UTC", "review_id": "75b712cd23922fa37293194c", "run_id": "20260907T155543-ce3781c4", "source_instructor_id": "rmp:2889232", "source_review_id": "UmF0aW5nLTQwNzY1MjM0", "source_url": "https://www.ratemyprofessors.com/professor/2889232", "type": "review" }, { "instructor_name": "Yiqiao Zhong", "review_date": "2026-05-12 15:33:53 +0000 UTC", "review_id": "062faa3be86494531f41dd29", "run_id": "20260907T155543-ce3781c4", "source_instructor_id": "rmp:2889232", "source_review_id": "UmF0aW5nLTQzMTAzOTEx", "source_url": "https://www.ratemyprofessors.com/professor/2889232", "type": "review" } ] } ``` Recent recorded grades — Spring 2025: 3.70 GPA, 90.9% A/AB (n=88 letter grades); Fall 2025: 3.91 GPA, 95.4% A/AB (n=87 letter grades); Spring 2026: 3.62 GPA, 92.2% A/AB (n=64 letter grades). ```json { "citations": [ { "course_id": "STAT 453", "run_id": "20260907T155543-ce3781c4", "source_record": { "entity_id": "9687c303-6cbb-39b1-9ffb-0b9254ce24bc", "file": "tables/observations.parquet", "kind": "grades", "source": "madgrades" }, "table": "grades_latest", "term_id": "1254", "type": "grade" }, { "course_id": "STAT 453", "run_id": "20260907T155543-ce3781c4", "source_record": { "entity_id": "9687c303-6cbb-39b1-9ffb-0b9254ce24bc", "file": "tables/observations.parquet", "kind": "grades", "source": "madgrades" }, "table": "grades_latest", "term_id": "1262", "type": "grade" }, { "course_id": "STAT 453", "run_id": "20260907T155543-ce3781c4", "source_record": { "entity_id": "9687c303-6cbb-39b1-9ffb-0b9254ce24bc", "file": "tables/observations.parquet", "kind": "grades", "source": "madgrades" }, "table": "grades_latest", "term_id": "1264", "type": "grade" } ] } ``` #### student experience Historical reviews of Yiqiao Zhong: Students report that lectures are often ineffective, necessitating independent learning. Some found the professor accommodating regarding deadlines, while others were frustrated by a lack of clarity in assignments and exams, though one review praised the lectures and exams. ```json { "citations": [ { "instructor_name": "Yiqiao Zhong", "review_date": "2024-05-07 09:52:37 +0000 UTC", "review_id": "1214b9801760e077473ae090", "run_id": "20260907T155543-ce3781c4", "source_instructor_id": "rmp:2889232", "source_review_id": "UmF0aW5nLTM5Mzg4OTE4", "source_url": "https://www.ratemyprofessors.com/professor/2889232", "type": "review" }, { "instructor_name": "Yiqiao Zhong", "review_date": "2025-05-09 17:47:23 +0000 UTC", "review_id": "a26e2fa8c871ae1797eb8560", "run_id": "20260907T155543-ce3781c4", "source_instructor_id": "rmp:2889232", "source_review_id": "UmF0aW5nLTQxMjI3NzA0", "source_url": "https://www.ratemyprofessors.com/professor/2889232", "type": "review" }, { "instructor_name": "Yiqiao Zhong", "review_date": "2025-05-18 03:55:49 +0000 UTC", "review_id": "d1f2a590c6f34a3df8dbf4f0", "run_id": "20260907T155543-ce3781c4", "source_instructor_id": "rmp:2889232", "source_review_id": "UmF0aW5nLTQxMzE0NjM2", "source_url": "https://www.ratemyprofessors.com/professor/2889232", "type": "review" } ] } ``` #### task hash 74fb0997943e888960bbc9e47db8c4fd12e4292d55c20509d8d89db6a9910f68 #### teaching history BAIHENG CHEN is recorded teaching in Fall 2025. Recorded history may be incomplete and does not establish a future schedule. ```json { "citations": [ { "course_id": "STAT 453", "run_id": "20260907T155543-ce3781c4", "section_number": 1, "source_course_id": "9687c303-6cbb-39b1-9ffb-0b9254ce24bc", "source_record": { "entity_id": "9687c303-6cbb-39b1-9ffb-0b9254ce24bc", "file": "tables/observations.parquet", "kind": "grades", "source": "madgrades" }, "table": "section_grades_latest", "term_id": "1262", "type": "grade" }, { "course_id": "STAT 453", "run_id": "20260907T155543-ce3781c4", "section_number": 2, "source_course_id": "9687c303-6cbb-39b1-9ffb-0b9254ce24bc", "source_record": { "entity_id": "9687c303-6cbb-39b1-9ffb-0b9254ce24bc", "file": "tables/observations.parquet", "kind": "grades", "source": "madgrades" }, "table": "section_grades_latest", "term_id": "1262", "type": "grade" } ] } ``` BENJAMIN LENGERICH is recorded teaching in Fall 2025. Recorded history may be incomplete and does not establish a future schedule. ```json { "citations": [ { "course_id": "STAT 453", "run_id": "20260907T155543-ce3781c4", "section_number": 1, "source_course_id": "9687c303-6cbb-39b1-9ffb-0b9254ce24bc", "source_record": { "entity_id": "9687c303-6cbb-39b1-9ffb-0b9254ce24bc", "file": "tables/observations.parquet", "kind": "grades", "source": "madgrades" }, "table": "section_grades_latest", "term_id": "1262", "type": "grade" }, { "course_id": "STAT 453", "run_id": "20260907T155543-ce3781c4", "section_number": 2, "source_course_id": "9687c303-6cbb-39b1-9ffb-0b9254ce24bc", "source_record": { "entity_id": "9687c303-6cbb-39b1-9ffb-0b9254ce24bc", "file": "tables/observations.parquet", "kind": "grades", "source": "madgrades" }, "table": "section_grades_latest", "term_id": "1262", "type": "grade" } ] } ``` YIQIAO ZHONG is recorded teaching in Spring 2023, Spring 2024, Spring 2025, Spring 2026. Recorded history may be incomplete and does not establish a future schedule. ```json { "citations": [ { "course_id": "STAT 453", "run_id": "20260907T155543-ce3781c4", "section_number": 1, "source_course_id": "9687c303-6cbb-39b1-9ffb-0b9254ce24bc", "source_record": { "entity_id": "9687c303-6cbb-39b1-9ffb-0b9254ce24bc", "file": "tables/observations.parquet", "kind": "grades", "source": "madgrades" }, "table": "section_grades_latest", "term_id": "1234", "type": "grade" }, { "course_id": "STAT 453", "run_id": "20260907T155543-ce3781c4", "section_number": 2, "source_course_id": "9687c303-6cbb-39b1-9ffb-0b9254ce24bc", "source_record": { "entity_id": "9687c303-6cbb-39b1-9ffb-0b9254ce24bc", "file": "tables/observations.parquet", "kind": "grades", "source": "madgrades" }, "table": "section_grades_latest", "term_id": "1234", "type": "grade" }, { "course_id": "STAT 453", "run_id": "20260907T155543-ce3781c4", "section_number": 1, "source_course_id": "9687c303-6cbb-39b1-9ffb-0b9254ce24bc", "source_record": { "entity_id": "9687c303-6cbb-39b1-9ffb-0b9254ce24bc", "file": "tables/observations.parquet", "kind": "grades", "source": "madgrades" }, "table": "section_grades_latest", "term_id": "1244", "type": "grade" }, { "course_id": "STAT 453", "run_id": "20260907T155543-ce3781c4", "section_number": 2, "source_course_id": "9687c303-6cbb-39b1-9ffb-0b9254ce24bc", "source_record": { "entity_id": "9687c303-6cbb-39b1-9ffb-0b9254ce24bc", "file": "tables/observations.parquet", "kind": "grades", "source": "madgrades" }, "table": "section_grades_latest", "term_id": "1244", "type": "grade" }, { "course_id": "STAT 453", "run_id": "20260907T155543-ce3781c4", "section_number": 1, "source_course_id": "9687c303-6cbb-39b1-9ffb-0b9254ce24bc", "source_record": { "entity_id": "9687c303-6cbb-39b1-9ffb-0b9254ce24bc", "file": "tables/observations.parquet", "kind": "grades", "source": "madgrades" }, "table": "section_grades_latest", "term_id": "1254", "type": "grade" }, { "course_id": "STAT 453", "run_id": "20260907T155543-ce3781c4", "section_number": 2, "source_course_id": "9687c303-6cbb-39b1-9ffb-0b9254ce24bc", "source_record": { "entity_id": "9687c303-6cbb-39b1-9ffb-0b9254ce24bc", "file": "tables/observations.parquet", "kind": "grades", "source": "madgrades" }, "table": "section_grades_latest", "term_id": "1254", "type": "grade" }, { "course_id": "STAT 453", "run_id": "20260907T155543-ce3781c4", "section_number": 1, "source_course_id": "9687c303-6cbb-39b1-9ffb-0b9254ce24bc", "source_record": { "entity_id": "9687c303-6cbb-39b1-9ffb-0b9254ce24bc", "file": "tables/observations.parquet", "kind": "grades", "source": "madgrades" }, "table": "section_grades_latest", "term_id": "1264", "type": "grade" }, { "course_id": "STAT 453", "run_id": "20260907T155543-ce3781c4", "section_number": 2, "source_course_id": "9687c303-6cbb-39b1-9ffb-0b9254ce24bc", "source_record": { "entity_id": "9687c303-6cbb-39b1-9ffb-0b9254ce24bc", "file": "tables/observations.parquet", "kind": "grades", "source": "madgrades" }, "table": "section_grades_latest", "term_id": "1264", "type": "grade" } ] } ``` #### term id 1272 #### term name 2026 Fall #### version 2 ### requirements #### nodes ```json [ { "children": [ "n1", "n2", "n3", "n4", "n5", "n6", "n7", "n8" ], "condition": null, "course": null, "evidence": "MATH 320,321,340,341,345,375, graduate/professional standing, or declared in Statistics VISP", "id": "n0", "kind": "any" }, { "children": [], "condition": null, "course": { "course_number": 320, "minimum_grade": null, "subjects": [ "MATH" ], "timing": "prior" }, "evidence": "MATH 320", "id": "n1", "kind": "course" }, { "children": [], "condition": null, "course": { "course_number": 321, "minimum_grade": null, "subjects": [ "MATH" ], "timing": "prior" }, "evidence": "321", "id": "n2", "kind": "course" }, { "children": [], "condition": null, "course": { "course_number": 340, "minimum_grade": null, "subjects": [ "MATH" ], "timing": "prior" }, "evidence": "340", "id": "n3", "kind": "course" }, { "children": [], "condition": null, "course": { "course_number": 341, "minimum_grade": null, "subjects": [ "MATH" ], "timing": "prior" }, "evidence": "341", "id": "n4", "kind": "course" }, { "children": [], "condition": null, "course": { "course_number": 345, "minimum_grade": null, "subjects": [ "MATH" ], "timing": "prior" }, "evidence": "345", "id": "n5", "kind": "course" }, { "children": [], "condition": null, "course": { "course_number": 375, "minimum_grade": null, "subjects": [ "MATH" ], "timing": "prior" }, "evidence": "375", "id": "n6", "kind": "course" }, { "children": [], "condition": "graduate/professional standing", "course": null, "evidence": "graduate/professional standing", "id": "n7", "kind": "condition" }, { "children": [], "condition": "declared in Statistics VISP", "course": null, "evidence": "declared in Statistics VISP", "id": "n8", "kind": "condition" } ] ``` #### notes None recorded. #### root n0 #### status parsed ### instructors | instructor\_uid | source | source\_instructor\_id | identity\_basis | identity\_status | name | email | first\_observed\_at | last\_observed\_at | instructor\_url | | ------------------------------------ | ---------- | ---------------------- | --------------- | ------------------ | ------------------ | ------------------- | -------------------------------- | -------------------------------- | -------------------------------- | | instructor\_4270353ff74ae497a4f645e4 | enrollment | bchen342 | netid | source\_identified | Baiheng Chen | BCHEN342\@WISC.EDU | 2026-09-07 15:55:43.033547+00:00 | 2026-09-07 15:55:43.033547+00:00 | /instructors/BAIHENG\_CHEN | | instructor\_816ff1547ceb6ebc8284e15f | enrollment | lengerich | netid | source\_identified | Benjamin Lengerich | LENGERICH\@WISC.EDU | 2026-09-07 15:55:43.033547+00:00 | 2026-09-07 15:55:43.033547+00:00 | /instructors/BENJAMIN\_LENGERICH | ### offerings ```json [ { "run_id": "20260907T155543-ce3781c4", "semester": "1272", "observed_at": "2026-09-07 15:55:43.033547+00:00", "offering_id": "1272:932:025597", "course_id": "STAT 453", "course_uid": "course_b9ca05f3e5db5af2eb30f64a", "term_id": "1272", "source_course_id": "025597", "source_subject_id": "932", "title": "Introduction to Deep Learning and Generative Models", "credits_min": 3, "credits_max": 3, "typically_offered": "Not Applicable" } ] ``` ### sections ```json [ { "run_id": "20260907T155543-ce3781c4", "observed_at": "2026-09-07 15:55:43.033547+00:00", "section_uid": "uw-section:1272:31072", "term_id": "1272", "source_section_id": "31072", "identity_basis": "class_number", "section_number": "001", "section_type": "LEC", "instruction_mode": "Classroom Instruction", "capacity": 80, "enrolled": 76, "waitlisted": 3, "start_date": "2026-09-02 05:00:00+00:00", "end_date": "2026-12-09 06:00:00+00:00" }, { "run_id": "20260907T155543-ce3781c4", "observed_at": "2026-09-07 15:55:43.033547+00:00", "section_uid": "uw-section:1272:31073", "term_id": "1272", "source_section_id": "31073", "identity_basis": "class_number", "section_number": "002", "section_type": "LEC", "instruction_mode": "Classroom Instruction", "capacity": 20, "enrolled": 10, "waitlisted": 0, "start_date": "2026-09-02 05:00:00+00:00", "end_date": "2026-12-09 06:00:00+00:00" } ] ``` ### grade instructors ```json [ { "instructor_uid": "instructor_88663f568ebff1b020dbbc51", "source": "madgrades", "source_instructor_id": "6176658", "identity_basis": "source_id", "identity_status": "source_identified", "name": "SEBASTIAN RASCHKA", "email": null, "first_observed_at": "2026-09-06 23:14:58.172943+00:00", "last_observed_at": "2026-09-07 15:55:43.033547+00:00", "ratings": { "review_count": 7, "quality": 5, "difficulty": 2.86, "quality_count": 7, "difficulty_count": 7, "profile_id": "rmp:2528650", "source_url": "https://www.ratemyprofessors.com/professor/2528650", "match_basis": "exact_name", "observed_at": "2026-09-07 16:06:27.808780+00:00", "courses": { "course_64851c516bf8195a88f81cc4": { "review_count": 6, "quality": 5, "difficulty": 2.83, "quality_count": 6, "difficulty_count": 6 }, "course_1282dc8dbc1e7c5749f7cc41": { "review_count": 1, "quality": 5, "difficulty": 3, "quality_count": 1, "difficulty_count": 1 } }, "bayesian_quality": 4.00717465447896, "prior_mean": 3.6596857835465957, "prior_weight": 20 }, "grade_statistics": { "gpa": 3.702, "graded": 506, "counts": [ 284, 150, 66, 4, 2, 0, 0 ], "sections": 16 }, "instructor_url": "/instructors/SEBASTIAN_RASCHKA--instructor_88663f568ebff1b020dbbc51" }, { "instructor_uid": "instructor_db32a27d5acd033dce683cd2", "source": "madgrades", "source_instructor_id": "5693629", "identity_basis": "source_id", "identity_status": "source_identified", "name": "ZHONGJIE YU", "email": null, "first_observed_at": "2026-09-06 23:14:58.172943+00:00", "last_observed_at": "2026-09-07 15:55:43.033547+00:00", "grade_statistics": { "gpa": 3.814, "graded": 183, "counts": [ 135, 28, 20, 0, 0, 0, 0 ], "sections": 5 }, "instructor_url": "/instructors/ZHONGJIE_YU--instructor_db32a27d5acd033dce683cd2" }, { "instructor_uid": "instructor_53d6506dcfd0a75fd8db60d2", "source": "madgrades", "source_instructor_id": "5833243", "identity_basis": "source_id", "identity_status": "source_identified", "name": "HONGZHI LIU", "email": null, "first_observed_at": "2026-09-06 23:14:58.172943+00:00", "last_observed_at": "2026-09-07 15:55:43.033547+00:00", "grade_statistics": { "gpa": 3.713, "graded": 333, "counts": [ 234, 53, 28, 6, 6, 4, 2 ], "sections": 11 }, "instructor_url": "/instructors/HONGZHI_LIU--instructor_53d6506dcfd0a75fd8db60d2" }, { "instructor_uid": "instructor_ac7e746a7007300142d74289", "source": "madgrades", "source_instructor_id": "5329782", "identity_basis": "source_id", "identity_status": "source_identified", "name": "YIQIAO ZHONG", "email": null, "first_observed_at": "2026-09-06 23:14:58.172943+00:00", "last_observed_at": "2026-09-07 15:55:43.033547+00:00", "ratings": { "review_count": 9, "quality": 1.89, "difficulty": 3.11, "quality_count": 9, "difficulty_count": 9, "profile_id": "rmp:2889232", "source_url": "https://www.ratemyprofessors.com/professor/2889232", "match_basis": "exact_name", "observed_at": "2026-09-07 15:57:42.523182+00:00", "courses": { "course_b9ca05f3e5db5af2eb30f64a": { "review_count": 9, "quality": 1.89, "difficulty": 3.11, "quality_count": 9, "difficulty_count": 9 } }, "bayesian_quality": 3.1104729541700653, "prior_mean": 3.6596857835465957, "prior_weight": 20 }, "grade_statistics": { "gpa": 3.674, "graded": 405, "counts": [ 198, 167, 35, 1, 2, 0, 2 ], "sections": 23 }, "instructor_url": "/instructors/YIQIAO_ZHONG--instructor_ac7e746a7007300142d74289" }, { "instructor_uid": "instructor_3ec25096edd42f69208142ad", "source": "madgrades", "source_instructor_id": "6449135", "identity_basis": "source_id", "identity_status": "source_identified", "name": "ZHEXUAN LIU", "email": null, "first_observed_at": "2026-09-06 23:14:58.172943+00:00", "last_observed_at": "2026-09-07 15:55:43.033547+00:00", "grade_statistics": { "gpa": 3.721, "graded": 356, "counts": [ 208, 113, 24, 6, 5, 0, 0 ], "sections": 8 }, "instructor_url": "/instructors/ZHEXUAN_LIU--instructor_3ec25096edd42f69208142ad" }, { "instructor_uid": "instructor_eeb902c84f921bb8550c1160", "source": "madgrades", "source_instructor_id": "6484577", "identity_basis": "source_id", "identity_status": "source_identified", "name": "BAIHENG CHEN", "email": null, "first_observed_at": "2026-09-06 23:14:58.172943+00:00", "last_observed_at": "2026-09-07 15:55:43.033547+00:00", "grade_statistics": { "gpa": 3.691, "graded": 217, "counts": [ 133, 45, 29, 9, 1, 0, 0 ], "sections": 6 }, "instructor_url": "/instructors/BAIHENG_CHEN--instructor_eeb902c84f921bb8550c1160" }, { "instructor_uid": "instructor_fd85f5d3f8c46ff150625ca3", "source": "madgrades", "source_instructor_id": "6687440", "identity_basis": "source_id", "identity_status": "source_identified", "name": "BENJAMIN LENGERICH", "email": null, "first_observed_at": "2026-09-06 23:14:58.172943+00:00", "last_observed_at": "2026-09-07 15:55:43.033547+00:00", "grade_statistics": { "gpa": 3.912, "graded": 125, "counts": [ 109, 10, 6, 0, 0, 0, 0 ], "sections": 6 }, "instructor_url": "/instructors/BENJAMIN_LENGERICH--instructor_fd85f5d3f8c46ff150625ca3" }, { "instructor_uid": "instructor_d6a6887610be7fa84afa2035", "source": "madgrades", "source_instructor_id": "6487604", "identity_basis": "source_id", "identity_status": "source_identified", "name": "FUXIN WANG", "email": null, "first_observed_at": "2026-09-06 23:14:58.172943+00:00", "last_observed_at": "2026-09-07 15:55:43.033547+00:00", "grade_statistics": { "gpa": 3.617, "graded": 64, "counts": [ 26, 33, 4, 0, 0, 0, 1 ], "sections": 2 }, "instructor_url": "/instructors/FUXIN_WANG--instructor_d6a6887610be7fa84afa2035" }, { "instructor_uid": "instructor_4270353ff74ae497a4f645e4", "source": "enrollment", "source_instructor_id": "bchen342", "identity_basis": "netid", "identity_status": "source_identified", "name": "Baiheng Chen", "email": "BCHEN342@WISC.EDU", "first_observed_at": "2026-09-07 15:55:43.033547+00:00", "last_observed_at": "2026-09-07 15:55:43.033547+00:00", "instructor_url": "/instructors/BAIHENG_CHEN" }, { "instructor_uid": "instructor_816ff1547ceb6ebc8284e15f", "source": "enrollment", "source_instructor_id": "lengerich", "identity_basis": "netid", "identity_status": "source_identified", "name": "Benjamin Lengerich", "email": "LENGERICH@WISC.EDU", "first_observed_at": "2026-09-07 15:55:43.033547+00:00", "last_observed_at": "2026-09-07 15:55:43.033547+00:00", "instructor_url": "/instructors/BENJAMIN_LENGERICH" } ] ``` ### grades ```json [ { "run_id": "20260907T155543-ce3781c4", "semester": "1272", "observed_at": "2026-09-07 15:55:43.033547+00:00", "course_id": "STAT 453", "course_uid": "course_b9ca05f3e5db5af2eb30f64a", "term_id": "1204", "term_name": "Spring 2020", "instructors": [ "SEBASTIAN RASCHKA", "ZHONGJIE YU" ], "a": 33, "ab": 13, "b": 10, "bc": 0, "c": 0, "d": 0, "f": 0, "satisfactory": 7, "unsatisfactory": 0, "credit": 0, "no_credit": 0, "passed": 0, "incomplete": 0, "no_work": 0, "not_reported": 0, "other": 0, "total": 63, "source_aliases": [ "STAT 453" ] }, { "run_id": "20260907T155543-ce3781c4", "semester": "1272", "observed_at": "2026-09-07 15:55:43.033547+00:00", "course_id": "STAT 453", "course_uid": "course_b9ca05f3e5db5af2eb30f64a", "term_id": "1234", "term_name": "Spring 2023", "instructors": [ "HONGZHI LIU", "Yiqiao Zhong" ], "a": 31, "ab": 25, "b": 2, "bc": 0, "c": 0, "d": 0, "f": 1, "satisfactory": 1, "unsatisfactory": 0, "credit": 0, "no_credit": 0, "passed": 0, "incomplete": 0, "no_work": 0, "not_reported": 1, "other": 0, "total": 61, "source_aliases": [ "STAT 453" ] }, { "run_id": "20260907T155543-ce3781c4", "semester": "1272", "observed_at": "2026-09-07 15:55:43.033547+00:00", "course_id": "STAT 453", "course_uid": "course_b9ca05f3e5db5af2eb30f64a", "term_id": "1244", "term_name": "Spring 2024", "instructors": [ "Yiqiao Zhong", "Zhexuan Liu" ], "a": 36, "ab": 35, "b": 12, "bc": 1, "c": 1, "d": 0, "f": 0, "satisfactory": 0, "unsatisfactory": 0, "credit": 0, "no_credit": 0, "passed": 0, "incomplete": 0, "no_work": 0, "not_reported": 0, "other": 0, "total": 85, "source_aliases": [ "STAT 453" ] }, { "run_id": "20260907T155543-ce3781c4", "semester": "1272", "observed_at": "2026-09-07 15:55:43.033547+00:00", "course_id": "STAT 453", "course_uid": "course_b9ca05f3e5db5af2eb30f64a", "term_id": "1254", "term_name": "Spring 2025", "instructors": [ "Yiqiao Zhong", "Zhexuan Liu" ], "a": 45, "ab": 35, "b": 7, "bc": 0, "c": 1, "d": 0, "f": 0, "satisfactory": 0, "unsatisfactory": 0, "credit": 0, "no_credit": 0, "passed": 0, "incomplete": 0, "no_work": 1, "not_reported": 0, "other": 0, "total": 89, "source_aliases": [ "STAT 453" ] }, { "run_id": "20260907T155543-ce3781c4", "semester": "1272", "observed_at": "2026-09-07 15:55:43.033547+00:00", "course_id": "STAT 453", "course_uid": "course_b9ca05f3e5db5af2eb30f64a", "term_id": "1262", "term_name": "Fall 2025", "instructors": [ "Baiheng Chen", "Benjamin Lengerich" ], "a": 76, "ab": 7, "b": 4, "bc": 0, "c": 0, "d": 0, "f": 0, "satisfactory": 2, "unsatisfactory": 0, "credit": 0, "no_credit": 0, "passed": 0, "incomplete": 1, "no_work": 0, "not_reported": 0, "other": 0, "total": 90, "source_aliases": [ "STAT 453" ] }, { "run_id": "20260907T155543-ce3781c4", "semester": "1272", "observed_at": "2026-09-07 15:55:43.033547+00:00", "course_id": "STAT 453", "course_uid": "course_b9ca05f3e5db5af2eb30f64a", "term_id": "1264", "term_name": "Spring 2026", "instructors": [ "Fuxin Wang", "Yiqiao Zhong" ], "a": 26, "ab": 33, "b": 4, "bc": 0, "c": 0, "d": 0, "f": 1, "satisfactory": 0, "unsatisfactory": 0, "credit": 0, "no_credit": 0, "passed": 0, "incomplete": 0, "no_work": 0, "not_reported": 0, "other": 0, "total": 64, "source_aliases": [ "STAT 453" ] } ] ``` ### statistics #### gpa 3.712 #### graded 439 #### counts * 247 * 148 * 39 * 1 * 2 * 0 * 2 ### grade conflicts None recorded. ### evidence #### history * [/data/e243353dcb7d79b7247ced91d69443ef4c2a6349/history/course\_b9ca05f3e5db5af2eb30f64a-0.json](https://uwcourses.com/data/e243353dcb7d79b7247ced91d69443ef4c2a6349/history/course_b9ca05f3e5db5af2eb30f64a-0.json) #### traces * [/data/e243353dcb7d79b7247ced91d69443ef4c2a6349/traces/course\_b9ca05f3e5db5af2eb30f64a-0.json](https://uwcourses.com/data/e243353dcb7d79b7247ced91d69443ef4c2a6349/traces/course_b9ca05f3e5db5af2eb30f64a-0.json) #### reviews * [/data/e243353dcb7d79b7247ced91d69443ef4c2a6349/reviews/course\_b9ca05f3e5db5af2eb30f64a-0.json](https://uwcourses.com/data/e243353dcb7d79b7247ced91d69443ef4c2a6349/reviews/course_b9ca05f3e5db5af2eb30f64a-0.json) #### meetings * [/data/e243353dcb7d79b7247ced91d69443ef4c2a6349/meetings/course\_b9ca05f3e5db5af2eb30f64a-0.json](https://uwcourses.com/data/e243353dcb7d79b7247ced91d69443ef4c2a6349/meetings/course_b9ca05f3e5db5af2eb30f64a-0.json) #### results * [/data/e243353dcb7d79b7247ced91d69443ef4c2a6349/results/course\_b9ca05f3e5db5af2eb30f64a-0.json](https://uwcourses.com/data/e243353dcb7d79b7247ced91d69443ef4c2a6349/results/course_b9ca05f3e5db5af2eb30f64a-0.json) ### revision e243353dcb7d79b7247ced91d69443ef4c2a6349 ## context ### all #### term #### gpa 3.711845102505695 #### count 439 #### university ##### size 3454 ##### gpa Percentile 43 ##### count Percentile 86 ##### median Count 106 ##### histogram | range | count | current | | ------- | ----- | ------- | | 0.0–0.4 | 0 | false | | 0.4–0.8 | 0 | false | | 0.8–1.2 | 0 | false | | 1.2–1.6 | 0 | false | | 1.6–2.0 | 0 | false | | 2.0–2.4 | 1 | false | | 2.4–2.8 | 10 | false | | 2.8–3.2 | 171 | false | | 3.2–3.6 | 827 | false | | 3.6–4.0 | 2445 | true | #### departments ```json [ { "subject": "STAT", "comparison": { "size": 60, "gpaPercentile": 63, "countPercentile": 83, "medianCount": 135, "histogram": [ { "range": "0.0–0.4", "count": 0, "current": false }, { "range": "0.4–0.8", "count": 0, "current": false }, { "range": "0.8–1.2", "count": 0, "current": false }, { "range": "1.2–1.6", "count": 0, "current": false }, { "range": "1.6–2.0", "count": 0, "current": false }, { "range": "2.0–2.4", "count": 0, "current": false }, { "range": "2.4–2.8", "count": 0, "current": false }, { "range": "2.8–3.2", "count": 6, "current": false }, { "range": "3.2–3.6", "count": 23, "current": false }, { "range": "3.6–4.0", "count": 31, "current": true } ] } } ] ``` ### terms #### 1204 ##### term 1204 ##### gpa 3.705357142857143 ##### count 56 ##### university ###### size 1012 ###### gpa Percentile 46 ###### count Percentile 43 ###### median Count 65.5 ###### histogram | range | count | current | | ------- | ----- | ------- | | 0.0–0.4 | 0 | false | | 0.4–0.8 | 0 | false | | 0.8–1.2 | 0 | false | | 1.2–1.6 | 0 | false | | 1.6–2.0 | 0 | false | | 2.0–2.4 | 0 | false | | 2.4–2.8 | 1 | false | | 2.8–3.2 | 25 | false | | 3.2–3.6 | 301 | false | | 3.6–4.0 | 685 | true | ##### departments ```json [ { "subject": "STAT", "comparison": { "size": 27, "gpaPercentile": 58, "countPercentile": 46, "medianCount": 56, "histogram": [ { "range": "0.0–0.4", "count": 0, "current": false }, { "range": "0.4–0.8", "count": 0, "current": false }, { "range": "0.8–1.2", "count": 0, "current": false }, { "range": "1.2–1.6", "count": 0, "current": false }, { "range": "1.6–2.0", "count": 0, "current": false }, { "range": "2.0–2.4", "count": 0, "current": false }, { "range": "2.4–2.8", "count": 0, "current": false }, { "range": "2.8–3.2", "count": 0, "current": false }, { "range": "3.2–3.6", "count": 11, "current": false }, { "range": "3.6–4.0", "count": 16, "current": true } ] } } ] ``` #### 1234 ##### term 1234 ##### gpa 3.6864406779661016 ##### count 59 ##### university ###### size 1188 ###### gpa Percentile 54 ###### count Percentile 44 ###### median Count 65 ###### histogram | range | count | current | | ------- | ----- | ------- | | 0.0–0.4 | 0 | false | | 0.4–0.8 | 0 | false | | 0.8–1.2 | 0 | false | | 1.2–1.6 | 0 | false | | 1.6–2.0 | 0 | false | | 2.0–2.4 | 3 | false | | 2.4–2.8 | 17 | false | | 2.8–3.2 | 144 | false | | 3.2–3.6 | 374 | false | | 3.6–4.0 | 650 | true | ##### departments ```json [ { "subject": "STAT", "comparison": { "size": 25, "gpaPercentile": 79, "countPercentile": 25, "medianCount": 67, "histogram": [ { "range": "0.0–0.4", "count": 0, "current": false }, { "range": "0.4–0.8", "count": 0, "current": false }, { "range": "0.8–1.2", "count": 0, "current": false }, { "range": "1.2–1.6", "count": 0, "current": false }, { "range": "1.6–2.0", "count": 0, "current": false }, { "range": "2.0–2.4", "count": 0, "current": false }, { "range": "2.4–2.8", "count": 1, "current": false }, { "range": "2.8–3.2", "count": 5, "current": false }, { "range": "3.2–3.6", "count": 12, "current": false }, { "range": "3.6–4.0", "count": 7, "current": true } ] } } ] ``` #### 1244 ##### term 1244 ##### gpa 3.611764705882353 ##### count 85 ##### university ###### size 1241 ###### gpa Percentile 44 ###### count Percentile 61 ###### median Count 65 ###### histogram | range | count | current | | ------- | ----- | ------- | | 0.0–0.4 | 0 | false | | 0.4–0.8 | 0 | false | | 0.8–1.2 | 0 | false | | 1.2–1.6 | 0 | false | | 1.6–2.0 | 0 | false | | 2.0–2.4 | 2 | false | | 2.4–2.8 | 9 | false | | 2.8–3.2 | 151 | false | | 3.2–3.6 | 373 | false | | 3.6–4.0 | 706 | true | ##### departments ```json [ { "subject": "STAT", "comparison": { "size": 29, "gpaPercentile": 75, "countPercentile": 64, "medianCount": 62, "histogram": [ { "range": "0.0–0.4", "count": 0, "current": false }, { "range": "0.4–0.8", "count": 0, "current": false }, { "range": "0.8–1.2", "count": 0, "current": false }, { "range": "1.2–1.6", "count": 0, "current": false }, { "range": "1.6–2.0", "count": 0, "current": false }, { "range": "2.0–2.4", "count": 0, "current": false }, { "range": "2.4–2.8", "count": 0, "current": false }, { "range": "2.8–3.2", "count": 8, "current": false }, { "range": "3.2–3.6", "count": 13, "current": false }, { "range": "3.6–4.0", "count": 8, "current": true } ] } } ] ``` #### 1254 ##### term 1254 ##### gpa 3.6988636363636362 ##### count 88 ##### university ###### size 1289 ###### gpa Percentile 51 ###### count Percentile 63 ###### median Count 66 ###### histogram | range | count | current | | ------- | ----- | ------- | | 0.0–0.4 | 0 | false | | 0.4–0.8 | 0 | false | | 0.8–1.2 | 0 | false | | 1.2–1.6 | 0 | false | | 1.6–2.0 | 0 | false | | 2.0–2.4 | 0 | false | | 2.4–2.8 | 17 | false | | 2.8–3.2 | 128 | false | | 3.2–3.6 | 379 | false | | 3.6–4.0 | 765 | true | ##### departments ```json [ { "subject": "STAT", "comparison": { "size": 28, "gpaPercentile": 70, "countPercentile": 63, "medianCount": 70, "histogram": [ { "range": "0.0–0.4", "count": 0, "current": false }, { "range": "0.4–0.8", "count": 0, "current": false }, { "range": "0.8–1.2", "count": 0, "current": false }, { "range": "1.2–1.6", "count": 0, "current": false }, { "range": "1.6–2.0", "count": 0, "current": false }, { "range": "2.0–2.4", "count": 0, "current": false }, { "range": "2.4–2.8", "count": 0, "current": false }, { "range": "2.8–3.2", "count": 6, "current": false }, { "range": "3.2–3.6", "count": 11, "current": false }, { "range": "3.6–4.0", "count": 11, "current": true } ] } } ] ``` #### 1262 ##### term 1262 ##### gpa 3.913793103448276 ##### count 87 ##### university ###### size 1320 ###### gpa Percentile 81 ###### count Percentile 58 ###### median Count 70 ###### histogram | range | count | current | | ------- | ----- | ------- | | 0.0–0.4 | 0 | false | | 0.4–0.8 | 0 | false | | 0.8–1.2 | 0 | false | | 1.2–1.6 | 0 | false | | 1.6–2.0 | 0 | false | | 2.0–2.4 | 1 | false | | 2.4–2.8 | 8 | false | | 2.8–3.2 | 133 | false | | 3.2–3.6 | 381 | false | | 3.6–4.0 | 797 | true | ##### departments ```json [ { "subject": "STAT", "comparison": { "size": 29, "gpaPercentile": 93, "countPercentile": 54, "medianCount": 81, "histogram": [ { "range": "0.0–0.4", "count": 0, "current": false }, { "range": "0.4–0.8", "count": 0, "current": false }, { "range": "0.8–1.2", "count": 0, "current": false }, { "range": "1.2–1.6", "count": 0, "current": false }, { "range": "1.6–2.0", "count": 0, "current": false }, { "range": "2.0–2.4", "count": 0, "current": false }, { "range": "2.4–2.8", "count": 0, "current": false }, { "range": "2.8–3.2", "count": 9, "current": false }, { "range": "3.2–3.6", "count": 12, "current": false }, { "range": "3.6–4.0", "count": 8, "current": true } ] } } ] ``` #### 1264 ##### term 1264 ##### gpa 3.6171875 ##### count 64 ##### university ###### size 1283 ###### gpa Percentile 41 ###### count Percentile 47 ###### median Count 66 ###### histogram | range | count | current | | ------- | ----- | ------- | | 0.0–0.4 | 0 | false | | 0.4–0.8 | 0 | false | | 0.8–1.2 | 0 | false | | 1.2–1.6 | 0 | false | | 1.6–2.0 | 0 | false | | 2.0–2.4 | 1 | false | | 2.4–2.8 | 20 | false | | 2.8–3.2 | 130 | false | | 3.2–3.6 | 343 | false | | 3.6–4.0 | 789 | true | ##### departments ```json [ { "subject": "STAT", "comparison": { "size": 26, "gpaPercentile": 76, "countPercentile": 44, "medianCount": 66, "histogram": [ { "range": "0.0–0.4", "count": 0, "current": false }, { "range": "0.4–0.8", "count": 0, "current": false }, { "range": "0.8–1.2", "count": 0, "current": false }, { "range": "1.2–1.6", "count": 0, "current": false }, { "range": "1.6–2.0", "count": 0, "current": false }, { "range": "2.0–2.4", "count": 0, "current": false }, { "range": "2.4–2.8", "count": 0, "current": false }, { "range": "2.8–3.2", "count": 10, "current": false }, { "range": "3.2–3.6", "count": 9, "current": false }, { "range": "3.6–4.0", "count": 7, "current": true } ] } } ] ``` ### benchmarks #### all ##### school ###### size 3454 ###### gpa 3.70077356028132 ###### top Share 84.45274506236886 ###### count 106 ##### STAT ###### size 60 ###### gpa 3.575772244096442 ###### top Share 76.67132306928164 ###### count 135 #### terms ##### 1204 ###### school ###### size 1012 ###### gpa 3.703747431523761 ###### top Share 84.59811226304916 ###### count 65.5 ###### STAT ###### size 27 ###### gpa 3.6537351147420534 ###### top Share 80.87794592686507 ###### count 56 ##### 1234 ###### school ###### size 1188 ###### gpa 3.5799441677552393 ###### top Share 77.18256448537606 ###### count 65 ###### STAT ###### size 25 ###### gpa 3.396227416481204 ###### top Share 66.8429997070879 ###### count 67 ##### 1244 ###### school ###### size 1241 ###### gpa 3.5975573126929192 ###### top Share 78.29036874847135 ###### count 65 ###### STAT ###### size 29 ###### gpa 3.390846810323202 ###### top Share 64.2629736611174 ###### count 62 ##### 1254 ###### school ###### size 1289 ###### gpa 3.6126423469389106 ###### top Share 79.48050408754871 ###### count 66 ###### STAT ###### size 28 ###### gpa 3.4752654121860003 ###### top Share 68.35873780152826 ###### count 70 ##### 1262 ###### school ###### size 1320 ###### gpa 3.628825763035853 ###### top Share 80.21118846327654 ###### count 70 ###### STAT ###### size 29 ###### gpa 3.415022952129974 ###### top Share 64.95385808199006 ###### count 81 ##### 1264 ###### school ###### size 1283 ###### gpa 3.6229729166451925 ###### top Share 80.13669149396227 ###### count 66 ###### STAT ###### size 26 ###### gpa 3.343399816676682 ###### top Share 63.23102425546245 ###### count 66 ## instructor Trends ```json [ { "uid": "instructor_ac7e746a7007300142d74289", "name": "YIQIAO ZHONG", "count": 296, "terms": [ { "term": "1234", "count": 59, "sections": 2, "gpa": 3.6864406779661016 }, { "term": "1244", "count": 85, "sections": 2, "gpa": 3.611764705882353 }, { "term": "1254", "count": 88, "sections": 2, "gpa": 3.6988636363636362 }, { "term": "1264", "count": 64, "sections": 2, "gpa": 3.6171875 } ] }, { "uid": "instructor_3ec25096edd42f69208142ad", "name": "ZHEXUAN LIU", "count": 173, "terms": [ { "term": "1244", "count": 85, "sections": 2, "gpa": 3.611764705882353 }, { "term": "1254", "count": 88, "sections": 2, "gpa": 3.6988636363636362 } ] }, { "uid": "instructor_eeb902c84f921bb8550c1160", "name": "BAIHENG CHEN", "count": 87, "terms": [ { "term": "1262", "count": 87, "sections": 2, "gpa": 3.913793103448276 } ] }, { "uid": "instructor_fd85f5d3f8c46ff150625ca3", "name": "BENJAMIN LENGERICH", "count": 87, "terms": [ { "term": "1262", "count": 87, "sections": 2, "gpa": 3.913793103448276 } ] }, { "uid": "instructor_d6a6887610be7fa84afa2035", "name": "FUXIN WANG", "count": 64, "terms": [ { "term": "1264", "count": 64, "sections": 2, "gpa": 3.6171875 } ] }, { "uid": "instructor_53d6506dcfd0a75fd8db60d2", "name": "HONGZHI LIU", "count": 59, "terms": [ { "term": "1234", "count": 59, "sections": 2, "gpa": 3.6864406779661016 } ] }, { "uid": "instructor_88663f568ebff1b020dbbc51", "name": "SEBASTIAN RASCHKA", "count": 56, "terms": [ { "term": "1204", "count": 56, "sections": 2, "gpa": 3.705357142857143 } ] }, { "uid": "instructor_db32a27d5acd033dce683cd2", "name": "ZHONGJIE YU", "count": 56, "terms": [ { "term": "1204", "count": 56, "sections": 2, "gpa": 3.705357142857143 } ] } ] ``` ## following None recorded. ## projection ### target 1272 ### gpa 3.749932435576857 ### grades | grade | percentage | | ----- | ------------------- | | A | 61.59372584687568 | | AB | 30.836431617046937 | | B | 6.5633267974765435 | | BC | 0.14474071058642607 | | C | 0.3194986708115144 | | D | 0 | | F | 0.5422763572029011 | ### source Terms * 1264 * 1262 * 1254 * 1244 * 1234 ### source Count 383 ### same Season false ### historical Range * 3.6117647058823525 * 3.913793103448276