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Data Science (DSCI)
- datascience.usc.edu/ D class assignments are only avaialable online at: myviterbi.usc.edu. Once you create your myViterbi profile, select the "D-Clearance Request Manager" to submit requests for DSCI courses. To be enrolled in an off-campus course, you MUST also be enrolled in the Distance Education Network (DEN). For more information, call 740-4488 or go to den.usc.edu. DEN courses are indicated by a location of DEN@Viterbi. For general questions regarding DSCI courses, you may email datasci@usc.edu.
Fundamentals of data science: representation of data and knowledge, role of a data scientist, data storage/processing/analytics, machine learning, big data and data visualization.
- Corequisite: ITP 115
| Section | Session | Type | Time | Days | Registered | Instructor | Location | Syllabus | Info |
|---|---|---|---|---|---|---|---|---|---|
| 32446R | 001 | Lecture | 5:00-8:20pm | Thursday | 137 of 144 | Sathyanaraya Raghavachary | GFS106 |  |
Data modeling, data storage, indexing, relational databases, key-value/document store, NoSQL, distributed file system, parallel computation and big-data analytics.
| Section | Session | Type | Time | Days | Registered | Instructor | Location | Syllabus | Info |
|---|---|---|---|---|---|---|---|---|---|
| 32402R | 001 | Lecture | 10:00-11:50am | Mon, Wed | 23 of 45 | Wensheng Wu | CPA152 | PDF (308994 KB) | |
Basic concepts in information security and privacy; implications of security and privacy breaches; security and privacy policies, threats and protection mechanisms; security and privacy laws, regulations and ethics.
| Section | Session | Type | Time | Days | Registered | Instructor | Location | Syllabus | Info |
|---|---|---|---|---|---|---|---|---|---|
| 32403R | 001 | Lecture | 4:00-7:20pm | Wednesday | 24 of 30 | Clifford Neuman | RTH217 | |
Programming in Python for retrieving, searching and analyzing data from the Web. Learning to manipulate large data sets.
| Section | Session | Type | Time | Days | Registered | Instructor | Location | Syllabus | Info |
|---|---|---|---|---|---|---|---|---|---|
| 32404D | 048 | Lecture | 10:00-11:50am | Tuesday | 45 of 60 | Anna Farzindar | SLH100 | PDF (243003 KB) | |
| 32427R | 048 | Lab | 10:00-11:50am | Thursday | 45 of 60 | SLH100 | | ||
| 32433D | 048 | Lecture | 4:00-5:50pm | Tuesday | 54 of 55 | Gleb Satyukov | OHE100D | PDF (81339 KB) | |
| 32434R | 048 | Lab | 4:00-5:50pm | Thursday | 54 of 55 | OHE100D | | ||
| 32405D | 034 | Lecture | 4:00-5:50pm | Tuesday | 13 of 30 | Gleb Satyukov | DEN@Viterbi | PDF (81339 KB) | |
| 32428R | 034 | Lab | 4:00-5:50pm | Thursday | 13 of 30 | DEN@Viterbi | |
Threats to information systems; technical and procedural approaches to threat mitigation; policy specification and foundations of policy for secure systems; mechanisms for building secure security services; risk management. Background in computer security preferred. Recommended previous courses of study include computer science, electrical engineering, computer engineering, management information systems and/or mathematics.
| Section | Session | Type | Time | Days | Registered | Instructor | Location | Syllabus | Info |
|---|---|---|---|---|---|---|---|---|---|
| 32406D | 048 | Lecture | 11:00-2:20pm | Wednesday | 38 of 50 | Tanya Ryutov | OHE100D | PDF (403113 KB) | |
| 32407D | 034 | Lecture | 11:00-2:20pm | Wednesday | 14 of 20 | Tanya Ryutov | DEN@Viterbi | PDF (403113 KB) | |
Assurance that an information system will behave as expected; assurance approaches for fielding secure information systems; case studies. Recommended preparation: Prior degree in computer science, electrical engineering, computer engineering, management information systems and/or mathematics. Some background in computer security preferred.
- Prerequisite: DSCI 519
| Section | Session | Type | Time | Days | Registered | Instructor | Location | Syllabus | Info |
|---|---|---|---|---|---|---|---|---|---|
| 32408D | 048 | Lecture | 1:00-4:20pm | Friday | 25 of 28 | Clifford Neuman | OHE120 | | |
| 32409D | 034 | Lecture | 1:00-4:20pm | Friday | 16 of 20 | Clifford Neuman | DEN@Viterbi | |
Privacy concerns in healthcare; current law and regulations; existing and emerging technologies shaped by ethics, privacy considerations and medical implications; special attention given to genomic data.
| Section | Session | Type | Time | Days | Registered | Instructor | Location | Syllabus | Info |
|---|---|---|---|---|---|---|---|---|---|
| 32439D | 048 | Lecture | 2:00-5:20pm | Monday | 36 of 40 | Tanya Ryutov | ONLINE | PDF (476815 KB) | |
Introduction to data analysis techniques and associated computing concepts for non-programmers. Topics include foundations for data analysis, visualization, parallel processing, metadata, provenance and data stewardship. Recommended preparation: mathematics and logic undergraduate courses.
| Section | Session | Type | Time | Days | Registered | Instructor | Location | Syllabus | Info |
|---|---|---|---|---|---|---|---|---|---|
| 32410D | 048 | Lecture | 8:30-11:50am | Monday | 107 of 120 | Gale Lucas | OHE122 | Word (59886 KB) | |
| 32411D | 034 | Lecture | 8:30-11:50am | Monday | 26 of 45 | Gale Lucas | DEN@Viterbi | Word (59886 KB) | |
Fundamentals of big data informatics techniques. Data lifecycle; the data scientist; machine learning; data mining; NoSQL databases; tools for storage/processing/analytics of large data set on clusters; in-data techniques.
| Section | Session | Type | Time | Days | Registered | Instructor | Location | Syllabus | Info |
|---|---|---|---|---|---|---|---|---|---|
| 32412D | 048 | Lecture | 5:30-7:20pm | Mon, Wed | 118 of 120 | Seon Kim | OHE122 | PDF (250973 KB) | |
| 32441D | 034 | Lecture | 5:30-7:20pm | Mon, Wed | 12 of 30 | Seon Kim | DEN@Viterbi | PDF (250973 KB) | |
Function and design of modern storage systems, including cloud; data management techniques; data modeling; network attached storage, clusters and data centers; relational databases; the map-reduce paradigm.
| Section | Session | Type | Time | Days | Registered | Instructor | Location | Syllabus | Info |
|---|---|---|---|---|---|---|---|---|---|
| 32413D | 048 | Lecture | 10:30-1:50pm | Tuesday | 39 of 40 | Wensheng Wu | RTH217 | PDF (316128 KB) | |
| 32414D | 048 | Lecture | 3:30-6:50pm | Tuesday | 101 of 130 | Wensheng Wu | SLH200 | PDF (316128 KB) | |
| 32443D | 034 | Lecture | 10:30-1:50pm | Tuesday | 15 of 30 | Wensheng Wu | DEN@Viterbi | PDF (316128 KB) | |
| 32447D | 048 | Lecture | 10:30-1:50pm | Tuesday | 198 of 215 | Wensheng Wu | RTH217 & ONLINE | PDF (316128 KB) | |
Practical applications of machine learning techniques to real-world problems. Uses in data mining and recommendation systems and for building adaptive user interfaces.
| Section | Session | Type | Time | Days | Registered | Instructor | Location | Syllabus | Info |
|---|---|---|---|---|---|---|---|---|---|
| 32416D | 048 | Lecture | 12:00-1:50pm | Mon, Wed | 40 of 40 | Mohammad Reza Rajati | OHE100B | PDF (200757 KB) | |
| 32417D | 048 | Lecture | 3:30-5:20pm | Mon, Wed | 118 of 120 | Mohammad Reza Rajati | MHP101 | PDF (200757 KB) | |
| 32442D | 034 | Lecture | 12:00-1:50pm | Mon, Wed | 22 of 30 | Mohammad Reza Rajati | DEN@Viterbi | PDF (200757 KB) | |
| 32448D | 048 | Lecture | 12:00-1:50pm | Mon, Wed | 212 of 215 | Mohammad Reza Rajati | OHE100B & ONLINE | PDF (200757 KB) | |
Data mining and machine learning algorithms for analyzing very large data sets. Emphasis on Map Reduce. Case studies.
| Section | Session | Type | Time | Days | Registered | Instructor | Location | Syllabus | Info |
|---|---|---|---|---|---|---|---|---|---|
| 32440D | 048 | Lecture | 6:00-9:20pm | Tuesday | 175 of 195 | Wei-Min Shen | OHE122 | PDF (276166 KB) | |
| 6:00-9:20pm | Tuesday | OHE136 | |||||||
| 32445D | 034 | Lecture | 6:00-9:20pm | Tuesday | 12 of 30 | Wei-Min Shen | DEN@Viterbi | PDF (276166 KB) | |
Graphical depictions of data for communication, analysis and decision support. Cognitive processing and perception of visual data and visualizations. Designing effective visualizations. Implementing interactive visualizations.
| Section | Session | Type | Time | Days | Registered | Instructor | Location | Syllabus | Info |
|---|---|---|---|---|---|---|---|---|---|
| 32422D | 048 | Lecture | 2:00-3:50pm | Mon, Wed | 93 of 94 | Luciano Nocera | WPHB27 | PDF (109337 KB) | |
The practice of User Experience Design and Strategy principles for the creation of unique and compelling digital products and services.
- Note: Students outside the DSCI/CSCI programs may request this course via myViterbi.usc.edu beginning in August.
| Section | Session | Type | Time | Days | Registered | Instructor | Location | Syllabus | Info |
|---|---|---|---|---|---|---|---|---|---|
| 32424D | 048 | Lecture | 1:00-4:20pm | Friday | 40 of 40 | David Chan | THH102 | PDF (230161 KB) |  |
| 32449D | 048 | Lecture | 2:00-5:20pm | Thursday | 38 of 40 | David Chan | THH208 | |
Foundations, techniques and algorithms for building knowledge graphs and doing so at scale. Topics include information extraction, data alignment, entity linking and the Semantic Web.
- Corequisite: 1 from (DSCI 551 or INF 551 or CSCI 585) and 1 from (DSCI 552 or INF 552 or CSCI 567)
- Note: This is not a CSCI course and will count as a non-CSCI course for any CS MS student.
| Section | Session | Type | Time | Days | Registered | Instructor | Location | Syllabus | Info |
|---|---|---|---|---|---|---|---|---|---|
| 32425D | 048 | Lecture | 3:30-5:20pm | Mon, Wed | 57 of 60 | Jay Pujara,Filip Ilievski | THH116 | |
Function, design, and use of modern data management systems, including cloud; data management techniques; data modeling; network attached storage, clusters and data centers; relational databases; the map-reduce paradigm.
- Note: This course is only for students in the ISE analytics program. This course is not open to Applied Data Science or CS students.
| Section | Session | Type | Time | Days | Registered | Instructor | Location | Syllabus | Info |
|---|---|---|---|---|---|---|---|---|---|
| 32435D | 048 | Lecture | 4:00-6:50pm | Wednesday | 107 of 110 | Bruce Wilcox | SAL101 | PDF (318288 KB) | |
Student teams working on external customer data analytic challenges; project/presentation based; real client data and implementable solutions for delivery to actual stakeholders; capstone to degree.
| Section | Session | Type | Time | Days | Registered | Instructor | Location | Syllabus | Info |
|---|---|---|---|---|---|---|---|---|---|
| 32426D | 048 | Lecture | 3:30-6:50pm | Monday | 45 of 45 | Anna Farzindar | SGM601 | PDF (293912 KB) | |
Analytics for supervised and unsupervised statistical learning. Generalized linear models, discriminant analysis, support vector machines. Nonparametric classification, trees, ensemble methods, k-nearest neighbors. Principal components, clustering.
- Crosslist: This course is offered by the ISE department but may qualify for major credit in DSCI. To register, enroll in ISE 529.
| Section | Session | Type | Time | Days | Registered | Instructor | Location | Syllabus | Info |
|---|---|---|---|---|---|---|---|---|---|
| 31529D | 048 | Lecture | 3:30-6:20pm | Monday | 40 of 45 | Cesar Acosta-Mejia | OHE100C | PDF (309372 KB) | |
| 31546D | 048 | Lecture | 11:00-12:20pm | Tue, Thu | 73 of 75 | Bruce Wilcox | ZHS352 | PDF (341560 KB) | |
| 31726D | 048 | Lecture | 5:00-7:50pm | Thursday | 88 of 90 | Cesar Acosta-Mejia | SLH100 | PDF (309216 KB) | |
| 31729D | 034 | Lecture | 3:30-6:20pm | Monday | 9 of 40 | Cesar Acosta-Mejia | DEN@Viterbi | PDF (309372 KB) | |
Introduce basic concepts of Medical Imaging Informatics with an introduction to clinical information systems (eg, PACS, RIS, EMR) related to the imaging workflow in a clinical healthcare enterprise
- Crosslist: This course is offered by the BME department but may qualify for major credit in DSCI. To register, enroll in BME 527.
| Section | Session | Type | Time | Days | Registered | Instructor | Location | Syllabus | Info |
|---|---|---|---|---|---|---|---|---|---|
| 29305D | 034 | Lecture | 11:30-1:20pm | Tue, Thu | 4 of 20 | Brent Liu | DEN@Viterbi | | |
| 29306D | 048 | Lecture | 11:30-1:20pm | Tue, Thu | 16 of 28 | Brent Liu | OHE120 | |
Research leading to the masters degree; maximum units which may be applied to the degree to be determined by the department.
| Section | Session | Units | Type | Time | Days | Registered | Instructor | Location | Syllabus | Info |
|---|---|---|---|---|---|---|---|---|---|---|
| 32429D | 048 | 1.0-6.0 | Lecture | TBA | TBA | 0 of 30 | OFFICE | |