# COMPSCI 774: Data Exploration, Cleaning, and Integration for Data Science | UW–Madison [View on UW Courses](https://uwcourses.com/courses/COMPSCI_774) ## 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 eb268fdc467307ea0c137ea3860f5d99f24b181a6db75d82789383649711347c ### course id COMPSCI 774 ### course uid course\_5ab2d4759486b00da0bb13b5 ### catalog version id e85f05ffd2d4f4c4902d449fe531a33d9165f7a5e3e29cb93fc655ca4b14f4b9 ### course number 774 ### subjects * COMPSCI ### title DATA EXPLORATION, CLEANING, AND INTEGRATION FOR DATA SCIENCE ### description Big Data is often said to deal with four Vs: volume, velocity, variety, and veracity. The focus is on variety and veracity challenges, which often arise in data science projects. In many such projects, data is often incorrect, hard to understand, and come from a variety of sources. Data scientists often spend 80% of their effort to explore, clean, and integrate this data, before analysis can be carried out to extract insights. As a result, managing variety and veracity has received significant attention. Study these topics, understand their challenges, and discuss solutions. These solutions often require data management, machine learning, big data scaling, cloud, crowdsourcing, and user interaction techniques. Knowledge of machine learning/AI \[COMP SCI 540], databases \[COMP SCI 564] and Python \[COMP SCI 320] recommended. ### requirements text Graduate/professional standing ### credit offering ids None recorded. ### llm job id enrich-8b774950c2b6adfdc46d1b82 ### llm output id 3ec64fe09ace5b599429d3f424b0a433a43f0b35829af5d6fa841dc2b28b41aa ### llm model nvidia/Qwen3.6-35B-A3B-NVFP4 ### llm model revision 1355db6a052410cfd62085d94b58866fd0f2c3c5 ### llm task version 14 ### llm search status valid ### llm summary This course covers data exploration, cleaning, and integration for data science, focusing on variety and veracity challenges using data management, machine learning, and cloud techniques. ### llm topics * Big Data variety and veracity challenges * Data exploration, cleaning, and integration * Data management, machine learning, big data scaling, cloud, crowdsourcing, and user interaction techniques ### llm skills * Data management, machine learning, big data scaling, cloud, crowdsourcing, and user interaction techniques * Data exploration, cleaning, and integration ### llm assumed background * Machine learning, databases, and Python programming * Machine learning and probabilistic reasoning * Database management systems and data models * Intermediate Python programming and data structures ### llm search phrases * big data variety veracity * data cleaning integration * data science programming python * machine learning databases graduate ### llm requirements status valid ### llm student summary status valid ### llm experience status insufficient\_evidence ### catalog variants None recorded. ### student summary #### context hash 1608782ef9e92e5b74ff80ed987c381ff15c2b0d20c25f6a185aa004e9ad7f84 #### course id COMPSCI 774 #### current instructors None recorded. #### difficulty workload None recorded. #### errors None recorded. #### historical context None recorded. #### message No course-specific reviews available #### offered false #### profile hash 5cb4dabf887cdbcd8c00d5a1312e10828b95c63f30bc3ea76aea199565390d02 #### quick take Recent recorded grades — Spring 2025: 3.97 GPA, 100.0% A/AB (n=51 letter grades); Spring 2026: 3.77 GPA, 81.8% A/AB (n=66 letter grades). ```json { "citations": [ { "course_id": "COMPSCI 774", "run_id": "20260907T155543-ce3781c4", "source_record": { "entity_id": "777078ea-c43e-380d-9c7f-50d97ec7ddbb", "file": "tables/observations.parquet", "kind": "grades", "source": "madgrades" }, "table": "grades_latest", "term_id": "1254", "type": "grade" }, { "course_id": "COMPSCI 774", "run_id": "20260907T155543-ce3781c4", "source_record": { "entity_id": "777078ea-c43e-380d-9c7f-50d97ec7ddbb", "file": "tables/observations.parquet", "kind": "grades", "source": "madgrades" }, "table": "grades_latest", "term_id": "1264", "type": "grade" } ] } ``` #### student experience None recorded. #### task hash 74fb0997943e888960bbc9e47db8c4fd12e4292d55c20509d8d89db6a9910f68 #### teaching history None recorded. #### term id 1272 #### term name 2026 Fall #### version 2 ### requirements #### nodes ```json [ { "children": [], "condition": "Graduate/professional standing", "course": null, "evidence": "Graduate/professional standing", "id": "n0", "kind": "condition" } ] ``` #### notes None recorded. #### root n0 #### status parsed ### instructors None recorded. ### offerings None recorded. ### sections None recorded. ### grade instructors ```json [ { "instructor_uid": "instructor_8a8d069a7cfff58ad5a275b4", "source": "madgrades", "source_instructor_id": "4195805", "identity_basis": "source_id", "identity_status": "source_identified", "name": "AN H DOAN", "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": 3.693, "graded": 1832, "counts": [ 1122, 428, 196, 66, 10, 6, 4 ], "sections": 152 }, "instructor_url": "/instructors/AN_H_DOAN" }, { "instructor_uid": "instructor_e485342c7375f6ab43cf133d", "source": "madgrades", "source_instructor_id": "6657792", "identity_basis": "source_id", "identity_status": "source_identified", "name": "DEV AHLUWALIA", "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": 3.304, "graded": 441, "counts": [ 180, 81, 80, 53, 36, 9, 2 ], "sections": 3 }, "instructor_url": "/instructors/DEV_AHLUWALIA--instructor_e485342c7375f6ab43cf133d" } ] ``` ### grades ```json [ { "run_id": "20260907T155543-ce3781c4", "semester": "1272", "observed_at": "2026-09-07 15:55:43.033547+00:00", "course_id": "COMPSCI 774", "course_uid": "course_5ab2d4759486b00da0bb13b5", "term_id": "1254", "term_name": "Spring 2025", "instructors": [ "AN H DOAN" ], "a": 48, "ab": 3, "b": 0, "bc": 0, "c": 0, "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": 51, "source_aliases": [ "COMPSCI 774" ] }, { "run_id": "20260907T155543-ce3781c4", "semester": "1272", "observed_at": "2026-09-07 15:55:43.033547+00:00", "course_id": "COMPSCI 774", "course_uid": "course_5ab2d4759486b00da0bb13b5", "term_id": "1264", "term_name": "Spring 2026", "instructors": [ "AN H DOAN", "DEV AHLUWALIA" ], "a": 48, "ab": 6, "b": 12, "bc": 0, "c": 0, "d": 0, "f": 0, "satisfactory": 1, "unsatisfactory": 0, "credit": 0, "no_credit": 0, "passed": 0, "incomplete": 0, "no_work": 0, "not_reported": 0, "other": 0, "total": 67, "source_aliases": [ "COMPSCI 774" ] } ] ``` ### statistics #### gpa 3.859 #### graded 117 #### counts * 96 * 9 * 12 * 0 * 0 * 0 * 0 ### grade conflicts None recorded. ### evidence #### history * [/data/e243353dcb7d79b7247ced91d69443ef4c2a6349/history/course\_5ab2d4759486b00da0bb13b5-0.json](https://uwcourses.com/data/e243353dcb7d79b7247ced91d69443ef4c2a6349/history/course_5ab2d4759486b00da0bb13b5-0.json) #### traces * [/data/e243353dcb7d79b7247ced91d69443ef4c2a6349/traces/course\_5ab2d4759486b00da0bb13b5-0.json](https://uwcourses.com/data/e243353dcb7d79b7247ced91d69443ef4c2a6349/traces/course_5ab2d4759486b00da0bb13b5-0.json) #### results * [/data/e243353dcb7d79b7247ced91d69443ef4c2a6349/results/course\_5ab2d4759486b00da0bb13b5-0.json](https://uwcourses.com/data/e243353dcb7d79b7247ced91d69443ef4c2a6349/results/course_5ab2d4759486b00da0bb13b5-0.json) ### revision e243353dcb7d79b7247ced91d69443ef4c2a6349 ## context ### all #### term #### gpa 3.858974358974359 #### count 117 #### university ##### size 2021 ##### gpa Percentile 69 ##### count Percentile 65 ##### median Count 77 ##### 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 | 21 | false | | 2.8–3.2 | 152 | false | | 3.2–3.6 | 521 | false | | 3.6–4.0 | 1327 | true | #### departments ```json [ { "subject": "COMPSCI", "comparison": { "size": 65, "gpaPercentile": 83, "countPercentile": 45, "medianCount": 126, "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": 8, "current": false }, { "range": "3.2–3.6", "count": 28, "current": false }, { "range": "3.6–4.0", "count": 28, "current": true } ] } } ] ``` ### terms #### 1254 ##### term 1254 ##### gpa 3.9705882352941178 ##### count 51 ##### university ###### size 1289 ###### gpa Percentile 92 ###### count Percentile 37 ###### 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": "COMPSCI", "comparison": { "size": 52, "gpaPercentile": 98, "countPercentile": 20, "medianCount": 105, "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": 10, "current": false }, { "range": "3.2–3.6", "count": 24, "current": false }, { "range": "3.6–4.0", "count": 17, "current": true } ] } } ] ``` #### 1264 ##### term 1264 ##### gpa 3.772727272727273 ##### count 66 ##### university ###### size 1283 ###### gpa Percentile 59 ###### count Percentile 49 ###### 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": "COMPSCI", "comparison": { "size": 48, "gpaPercentile": 74, "countPercentile": 32, "medianCount": 105.5, "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": 7, "current": false }, { "range": "3.2–3.6", "count": 21, "current": false }, { "range": "3.6–4.0", "count": 19, "current": true } ] } } ] ``` ### benchmarks #### all ##### school ###### size 2021 ###### gpa 3.660373947354374 ###### top Share 82.25902967226666 ###### count 77 ##### COMPSCI ###### size 65 ###### gpa 3.54676671421842 ###### top Share 75.29768070134821 ###### count 126 #### terms ##### 1254 ###### school ###### size 1289 ###### gpa 3.6126423469389106 ###### top Share 79.48050408754871 ###### count 66 ###### COMPSCI ###### size 52 ###### gpa 3.482652727664103 ###### top Share 71.33786483648515 ###### count 105 ##### 1264 ###### school ###### size 1283 ###### gpa 3.6229729166451925 ###### top Share 80.13669149396227 ###### count 66 ###### COMPSCI ###### size 48 ###### gpa 3.5022746140005943 ###### top Share 73.13318776233326 ###### count 105.5 ## instructor Trends ```json [ { "uid": "instructor_8a8d069a7cfff58ad5a275b4", "name": "AN H DOAN", "count": 117, "terms": [ { "term": "1254", "count": 51, "sections": 1, "gpa": 3.9705882352941178 }, { "term": "1264", "count": 66, "sections": 1, "gpa": 3.772727272727273 } ] }, { "uid": "instructor_e485342c7375f6ab43cf133d", "name": "DEV AHLUWALIA", "count": 66, "terms": [ { "term": "1264", "count": 66, "sections": 1, "gpa": 3.772727272727273 } ] } ] ``` ## following | code | title | | ----------- | ------------------- | | COMPSCI 739 | DISTRIBUTED SYSTEMS |