collapse allexpand all
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: 1 from (ITP 115 or ITP 116)
- Note: D-Clearance Request Form: forms.gle/yBRDmMLTHo6ZSHdr7
| Section | Session | Type | Time | Days | Registered | Instructor | Location | Syllabus | Info |
|---|---|---|---|---|---|---|---|---|---|
| 32401D | 001 | Lecture | 2:00-3:50pm | Tue, Thu | 0 of 263 | SAL101 |   |
Data modeling, data storage, indexing, relational databases, key-value/document store, NoSQL, distributed file system, parallel computation and big-data analytics.
- Prerequisite: DSCI 250 and 1 from (ITP 115 or ITP 116)
- Note: D-Clearance Request Form: forms.gle/CcaaaLtCW7zT4NuP8
| Section | Session | Type | Time | Days | Registered | Instructor | Location | Syllabus | Info |
|---|---|---|---|---|---|---|---|---|---|
| 32402D | 001 | Lecture | 10:00-11:50am | Mon, Wed | 0 of 98 | SOSB2 | |
Foundational course focusing on the understanding, application and evaluation of machine learning and data mining approaches in data-intensive scenarios.
- Prerequisite: DSCI 250 and MATH 208
- Note: D-Clearance Request Form: forms.gle/7BFewAHxg94dx9B5A
| Section | Session | Type | Time | Days | Registered | Instructor | Location | Syllabus | Info |
|---|---|---|---|---|---|---|---|---|---|
| 32459D | 001 | Lecture | 3:30-5:20pm | Tue, Thu | 0 of 60 | DMC156 | |
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.
- Note: D-Clearance Request Form: forms.gle/jGBiT6y1iWKmJoMA9
| Section | Session | Type | Time | Days | Registered | Instructor | Location | Syllabus | Info |
|---|---|---|---|---|---|---|---|---|---|
| 32403D | 001 | Lecture | 4:00-7:20pm | Wednesday | 0 of 30 | 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 | 0 of 93 | SLH100 | | ||
| 32427R | 048 | Lab | 10:00-11:50am | Thursday | 0 of 93 | SLH100 | | ||
| 32433D | 048 | Lecture | 4:00-5:50pm | Tuesday | 0 of 120 | OHE122 | | ||
| 32434R | 048 | Lab | 4:00-5:50pm | Thursday | 0 of 120 | OHE122 | | ||
| 32405D | 034 | Lecture | 4:00-5:50pm | Tuesday | 0 of 30 | DEN@Viterbi | | ||
| 32428R | 034 | Lab | 4:00-5:50pm | Thursday | 0 of 30 | DEN@Viterbi | |
Introduction to research methods and data analysis techniques for human subject research; experimental research design, correlational research, data analysis, ensuring validity and ethics.
| Section | Session | Type | Time | Days | Registered | Instructor | Location | Syllabus | Info |
|---|---|---|---|---|---|---|---|---|---|
| 32454D | 048 | Lecture | 8:00-11:20am | Monday | 0 of 120 | OHE122 | | ||
| 32456D | 034 | Lecture | 8:00-11:20am | Monday | 0 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 | 12:00-3:20pm | Wednesday | 0 of 56 | OHE100D | | ||
| 32407D | 034 | Lecture | 12:00-3:20pm | Wednesday | 0 of 20 | DEN@Viterbi | |
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 | 0 of 45 | RTH109 | | ||
| 32409D | 034 | Lecture | 1:00-4:20pm | Friday | 0 of 20 | 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.
- Note: International students cannot take the ONLINE section.
| Section | Session | Type | Time | Days | Registered | Instructor | Location | Syllabus | Info |
|---|---|---|---|---|---|---|---|---|---|
| 32439D | 048 | Lecture | 3:30-6:50pm | Monday | 0 of 50 | DMC100 | | ||
| 32462D | 048 | Lecture | 3:30-6:50pm | Wednesday | 0 of 50 | DMC100 | |
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 | 8:00-11:20am | Wednesday | 0 of 120 | OHE122 | | ||
| 32411D | 034 | Lecture | 8:00-11:20am | Wednesday | 0 of 30 | DEN@Viterbi | |
Big data informatics fundamentals. Data lifecycle; the data scientist; machine learning; data mining; NoSQL databases; tools to store, process, analyze large data sets on clusters.
| Section | Session | Type | Time | Days | Registered | Instructor | Location | Syllabus | Info |
|---|---|---|---|---|---|---|---|---|---|
| 32412D | 048 | Lecture | 4:00-5:50pm | Mon, Wed | 0 of 120 | OHE122 | | ||
| 32441D | 034 | Lecture | 4:00-5:50pm | Mon, Wed | 0 of 30 | DEN@Viterbi | |
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 | 6:00-9:20pm | Monday | 0 of 120 | OHE122 | | ||
| 32414D | 048 | Lecture | 3:30-6:50pm | Tuesday | 0 of 163 | SGM101 | | ||
| 32443D | 034 | Lecture | 6:00-9:20pm | Monday | 0 of 30 | DEN@Viterbi | |
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 |
|---|---|---|---|---|---|---|---|---|---|
| 32400D | 048 | Lecture | 4:00-5:50pm | Mon, Wed | 0 of 187 | SLH200 | | ||
| 32448D | 048 | Lecture | 12:00-1:50pm | Mon, Wed | 0 of 320 | SGM123 | | ||
| 32442D | 034 | Lecture | 12:00-1:50pm | Mon, Wed | 0 of 30 | DEN@Viterbi | |
Data mining and machine learning algorithms for analyzing very large data sets. Emphasis on System Building with Spark. Case studies.
- Prerequisite: 1 from (DSCI 551 or CSCI 585) and 1 from (DSCI 552 or CSCI 567)
- Note: DSCI students must take DSCI 551 and DSCI 552 prior to taking DSCI 553.
| Section | Session | Type | Time | Days | Registered | Instructor | Location | Syllabus | Info |
|---|---|---|---|---|---|---|---|---|---|
| 32444D | 048 | Lecture | 6:00-9:20pm | Thursday | 0 of 120 | OHE122 | | ||
| 32445D | 034 | Lecture | 6:00-9:20pm | Thursday | 0 of 30 | DEN@Viterbi | |
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 | 9:00-10:50am | Tue, Thu | 0 of 82 | GFS116 | |
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 | 0 of 40 | DMC101 | | ||
| 32455D | 048 | Lecture | 5:00-8:20pm | Friday | 0 of 40 | DMC101 | |
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 | 8:00-9:50am | Mon, Wed | 0 of 72 | THH210 | |
Supervised learning. Linear regression, cross validation, ridge and lasso regression, logistic regression, k-nearest-neighbors, decision trees, random forest and gradient-boosting models, support vector machines, neural networks.
- 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 | 2:00-3:50pm | Mon, Wed | 0 of 45 | OHE122 | | ||
| 31546D | 048 | Lecture | 2:00-3:50pm | Tue, Thu | 0 of 49 | GFS101 | | ||
| 31712D | 048 | Lecture | 5:30-7:20pm | Mon, Wed | 0 of 70 | Tao Ma | SOSB46 | | |
| 31729D | 048 | Lecture | 5:30-7:20pm | Tue, Thu | 0 of 90 | GFS106 | | ||
| 31731D | 034 | Lecture | 2:00-3:50pm | Mon, Wed | 0 of 20 | DEN@Viterbi | |
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 | 12:00-1:50pm | Tue, Thu | 0 of 20 | Brent Liu | DEN@Viterbi | | |
| 29306D | 048 | Lecture | 12:00-1:50pm | Tue, Thu | 0 of 33 | 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 | |