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Course descriptions for most courses can be found in the University of Washington course catalog linked below. Please note that although summer courses are not yet listed we do offer a variety of courses. Contact the Institute of Technology for details.

You can use the Time Schedule Quick Search tool to easily find available classes.

Current Special Topics Courses

Special topics courses are not described in the catalog because their focus changes depending on the faculty member teaching the course.


TCSS 590A - Spring 2013: MW at 4:15PM with Dr. George Mobus
Computation Systems Science: Modeling Systems 


Topics Covered:

General Systems Science and Systems Thinking
  • The universality of systems theory
  • The applications of systems theory in interdisciplinary work
Complex Systems
  • Representation
  • Complexity Theory
Modeling Dynamic Systems
  • Why Are Models So Important? The Power of the Computer
  • Selecting the System of Interest – Problem Definition
  • Identifying Boundaries
  • Defining Inputs and Outputs – Black Box Analysis
  • Functional Analysis
  • Systems Analysis – Opening Up the Box
  • Constructing the Model
Implementing and Testing the Model
  • Relation Between Models and Object Oriented Languages
  • General Form of Dynamic Systems Model Program
  • Testing Object Functions
  • Data-Driven vs. Theory-Driven Models (and Hybrids)
  • Capturing Model States
  • Analyzing Model Behavior
  • Comparing the Model Results with Real-World Data
Reporting the Results
  • Structure of Reports
  • Delivery of Reports

TCSS 590B - Spring 2013: M at 6:30PM with Dr. Matthew Tolentino
Introduction to Big Data Architecture 


The course will discuss architecture issues related to processing, storing and analyzing massive amounts of data.  The emphasis will be on analyzing the impact of hardware architecture on emerging, parallel frameworks used for large-scale analytics.  This seminar class will discuss recent research papers.

Topics Covered:


  • Computer architectures for Big Data applications
  • System interconnect and storage subsystem impact of Big Data communication patterns, out-of core computations, and implications of emerging system architectures
  • Distributed databases and stores
  • Hadoop & YARN, Berkeley Data Analytics Stack (BDAS, including Shark and Spark), GraphLab, Storm, and other Big Data parallel frameworks
  • Data streams
  • Challenges in Unstructured data processing

Student Learning Goals (to be added to syllabus handed out to students)

  • Translate workload execution characteristics to hardware requirements to identify opportunities for future hardware architectures to radically accelerate application performance
  • Contrast challenges of Big Data parallel frameworks with traditional OS design
  • Compare and contrast the performance impact of architectural changes to bulk-synchronous in-memory, and stream parallel data processing frameworks
  • Analyze the running times of data manipulation, storage and retrieval algorithms that constitute database systems internals and applications.
  • Develop and compare application performance using multiple data store systems such as Hive, Hbase, Shark, InfiniDB, MemSQL, and Postgres

Previous Special Topics Courses


TCSS 590A - Winter 2013: MW at 4.15pm with Dr. Ankur Teredesai
Big Data Managemen

The course will discuss data management techniques for storing and analyzing very large amounts of data. The emphasis will be on columnar databases and on Map Reduce as a tool for creating parallel algorithms that can process very large amounts of data.
Topics include: Big Data applications, Columnar stores, distributed databases, Hadoop, Locality Sensitive Hashing (LSH), Dimensionality reduction, Data streams, unstructured data processing, NoSQL, and NewSQL.

  • Big Data Applications
  • Columnar Storage and organization
  • Distributed databases
  • Hadoop
  • Locality Sensitive Hashing (LSH)
  • Dimensionality reduction
  • Data streams
  • Challenges in Unstructured data processing
  • NoSQL
  • NewSQL
  • (time permitting) Introduction to Mining massive datasets

This is an introductory course in implementation issues of database systems being used for the big data challenges for CS majors. Columnar Databases and Hadoop are becoming increasingly important in today’s interconnected world. These database technologies drive the way we store, manage and extract information. Hence the study of big data database systems encompasses various characteristics of the study of information and computing systems. Such database systems are programs that require a fundamental understanding of data structures. We will engage in seminar style presentation and discussions, short in-class quizzes, and programming assignments.

Prerequisite: a minimum grade of 3.0 in TCSS 343 and TCSS445 (or equivalent course).

TCSS 590B - Winter 2013: TTh at 1020am with Dr. Senjuti Basu Roy
Data Analytics

The data analytics course teaches a variety of methods and techniques to analyze and investigate online data. Learning data analytics tools and techniques are key to success in this data enriched environment. Examples include learning how to market effectively, how to truly connect with our audiences, how to improve the customer experience on the web sites, how to invest resources, and how to improve return on investment, be it getting donations, increasing revenue, or winning elections to name a few! This course includes learning different aspects of online data analytics, interleaved with underlying theoretical concepts (statistical analysis, multidimensional data manipulation, and graph manipulations techniques) that are required to understand and apply these concepts, and hands-on experience to perform web analytics on some real world data.


TCSS 490 - Autumn 2012: TTH at 10.30am with Dr. Ling Ding
Wireless Sensor Networks

This course provides a study of issues and methods in wireless sensor networks. We will include the wireless sensor network concepts, applications, design & analysis, network protocols, security, etc. Students will study related technologies ranging from networking, algorithm, to security. We will also disscuss the issues in some variations of wireless sensor network like camera sensor network and body sensor network. The sensor network is very common in our daily life. It attracts attentions from both research community and industry. The course will be helpful for the students' further study in academia and job position in industry.


TCSS 590 - Autumn 2012: TTH at 6.30 with Dr. Mohammed Ali (Senior Software Design Engineer - Microsoft StreamInsight - Microsoft SQL Server)
GIS (Geographic Information Systems)

While traditional information systems deal with objects that are of numeric or alphanumeric data types, a wide set of applications deal with objects that have spatial extent (e.g., points, lines and polygons) or that are geographic in nature (i.e., representable on a map). "Are spatial data types special?" YES and NO! This course addresses how to represent, store, index, and process spatial objects and focuses on their application in the field of Geographic Information Systems (GIS).

With the growing interest in spatial databases (e.g., Microsoft SQL Server Spatial Library, IBM Spatial Solutions, Oracle Spatial ), with the ability to access a wealth of digitized maps (e.g., Google maps, Bing maps, Navteq), with the availability of rich Geographic Information Systems (e.g., ESRI ArcGis), and with the advances in GPS devices (e.g., Garmin, TomTom) and smart phones(e.g., iPhones, Androids, and Windows Phones), geospatial data management and location based services have been crucial to industry at all scales.

This course provides a good stretch to the students in the GIS field starting from theoretical basic concepts and ramping up quickly to provide a hands-on experience with various commercial GIS systems. The course is intended to motivate the next generation of geospatial researchers and, meanwhile, is geared up to plant the seed of an engineer who leads a career in Geographic Information Systems.

For past GIS student projects, click here or Video


TCSS 590A - Autumn 2012: TTH at 4:15 with Dr. George Mobus
Computational Cybernetics and Information Theory

This course covers the theory of information in communications and control systems such as organizational management to auto-pilots to governance. It develops the theory of information as the measure of how a system needs to change its internal operations in order to meet pre-specified goals. It draws heavily on system control theory and control engineering concepts as they apply to all kinds of systems. The course emphasizes analysis and design of computational implementations of such systems.

This subject is becoming increasingly important to all areas of the economy, education, and policy formation. The knowledge and skills taught are highly transferable to many career domains.


TCSS 590A - Autumn 2011: Advanced Database Systems

This course is an advanced-level course in database systems. The course has two main themes: First, the course covers some of the internals of a database system. Second, the course explores some of the current topics or trends in database research. The objective of the course is to give the student a first step towards a career in database systems programming and to broaden the scope of the student to appreciate the importance and the impact of newly emerging database trends. (Instructor: Mohamed Ali, Autumn 2011)