Difference between revisions of "CMSC420 - Data Structures"
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| − | + | <div id="TOC" style="float:right;">__TOC__</div> | |
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| + | This year, this course has three different instructors, all of whom teach this course differently. At present, we have information for only Michelle Hugue and Larry Davis. We are currently working on getting information from Venkatramanan Subrahmanian. If you have any questions about their section of the course and how they will be presenting the material, please ask them directly.<br> | ||
| + | == Michelle Hugue | 0101 & 0201 == | ||
{| style="text-align:left; width: 550PX;" | {| style="text-align:left; width: 550PX;" | ||
| − | |||
! Section | ! Section | ||
! Day & Time | ! Day & Time | ||
! Location | ! Location | ||
|- style="vertical-align:top;" | | |- style="vertical-align:top;" | | ||
| − | + | | 0101 || TuTh 2:00pm - 3:15pm|| style="vertical-align:top;" | [http://maps.umd.edu/map/index.html?Welcome=False&MapView=Detailed&LocationType=Building&LocationName=406 CSI 3117]<br> | |
|- style="vertical-align:top;" | | |- style="vertical-align:top;" | | ||
| − | | | + | | 0201 || TuTh 3:30pm - 4:45pm || style="vertical-align:top;" | [http://maps.umd.edu/map/index.html?Welcome=False&MapView=Detailed&LocationType=Building&LocationName=406 CSI 1122] |
| − | | | + | |} |
| − | + | ||
| − | + | '''Course Description'''<br> | |
| + | Description, properties, and storage allocation of data structures including lists and trees. Algorithms for manipulating structures. Applications from areas such as data processing, information retrieval, symbol manipulation, and operating systems. | ||
''' Course Prerequisite(s) ''' <br> | ''' Course Prerequisite(s) ''' <br> | ||
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''' Class Webpage ''' <br> | ''' Class Webpage ''' <br> | ||
| + | [http://www.cs.umd.edu/class/fall2016/cmsc420/ CMSC420 Fall 2016 - Meesh] | ||
''' Hours Per Week ''' <br> | ''' Hours Per Week ''' <br> | ||
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''' Recommended Prior Experience ''' <br> | ''' Recommended Prior Experience ''' <br> | ||
| − | + | ||
''' Projects, Exams, or other Assessments ''' <br> | ''' Projects, Exams, or other Assessments ''' <br> | ||
| − | + | ||
''' Misc Info ''' <br> | ''' Misc Info ''' <br> | ||
We often refer to this course as "data structures in context." | We often refer to this course as "data structures in context." | ||
The class presents a practical approach to data structures for computer intensive products that can be proven to satisfy correctness and performance requirements. One can obtain almost any data structure from a book or online. However, it takes experience to identify data structures known to provide the desired behavior; to extend them to satisfy the specific application; and to evaluate the deliverables to show that they satisfy the composite standard and custom requirements. The lectures, the project (three linked parts) and the exams are designed to provide students with such experience. This includes having projects which require sustained effort rather than last minute code-a-thons, exams written to elicit knowledge, not empty verbiage, and course policies which reward hard work and learning from mistakes. To put it bluntly, I'll do my best to help you to make mistakes and then support your efforts to learn from them. This is a thinking class, not an echo information class. | The class presents a practical approach to data structures for computer intensive products that can be proven to satisfy correctness and performance requirements. One can obtain almost any data structure from a book or online. However, it takes experience to identify data structures known to provide the desired behavior; to extend them to satisfy the specific application; and to evaluate the deliverables to show that they satisfy the composite standard and custom requirements. The lectures, the project (three linked parts) and the exams are designed to provide students with such experience. This includes having projects which require sustained effort rather than last minute code-a-thons, exams written to elicit knowledge, not empty verbiage, and course policies which reward hard work and learning from mistakes. To put it bluntly, I'll do my best to help you to make mistakes and then support your efforts to learn from them. This is a thinking class, not an echo information class. | ||
| + | |||
| + | == Larry Davis | 0301 == | ||
| + | {| style="text-align:left; width: 550PX;" | ||
| + | ! Day & Time | ||
| + | ! Location | ||
| + | |- style="vertical-align:top;" | | ||
| + | | TuTh 11:00am - 12:15pm || style="vertical-align:top;" | [http://maps.umd.edu/map/index.html?Welcome=False&MapView=Detailed&LocationType=Building&LocationName=406 CSI 1122] | ||
| + | |} | ||
| + | |||
| + | '''Course Description'''<br> | ||
| + | Sorting and searching (trees, tries, hashing), representations for higher dimensional data (kd trees, quadtrees and others), big data applications.<br> | ||
| + | |||
| + | '''Hours per week'''<br> | ||
| + | 2 - 4 Hours per week<br> | ||
| + | |||
| + | ''' Languages Used ''' <br> | ||
| + | Fairly open. Java mostly | ||
| + | |||
| + | ''' Recommended Prior Experience ''' <br> | ||
| + | Just the standard sequence through the 300 level. | ||
| + | |||
| + | ''' Projects, Exams, or other Assessments ''' <br> | ||
| + | Usually 2-3 exams, 3 projects | ||
| + | |||
| + | '''Misc Info'''<br> | ||
| + | Emphasis is on algorithms and data structures, not proofs. Projects designed to exercise methods covered in class. | ||
Latest revision as of 19:54, 4 April 2017
This year, this course has three different instructors, all of whom teach this course differently. At present, we have information for only Michelle Hugue and Larry Davis. We are currently working on getting information from Venkatramanan Subrahmanian. If you have any questions about their section of the course and how they will be presenting the material, please ask them directly.
Michelle Hugue | 0101 & 0201[edit]
| Section | Day & Time | Location |
|---|---|---|
| 0101 | TuTh 2:00pm - 3:15pm | CSI 3117 |
| 0201 | TuTh 3:30pm - 4:45pm | CSI 1122 |
Course Description
Description, properties, and storage allocation of data structures including lists and trees. Algorithms for manipulating structures. Applications from areas such as data processing, information retrieval, symbol manipulation, and operating systems.
Course Prerequisite(s)
Prerequisite: Minimum grade of C- in CMSC351 and CMSC330; and permission of CMNS-Computer Science department. Or must be in the (Computer Science (Doctoral), Computer Science (Master's)) program.
Class Webpage
CMSC420 Fall 2016 - Meesh
Hours Per Week
The workload for this course is at least the 10 hours associated with a 3 credit class. Programming and debugging skills, or a lack thereof, make it hard to give a decent estimate here.
Languages Used
JAVA
Recommended Prior Experience
Projects, Exams, or other Assessments
Misc Info
We often refer to this course as "data structures in context."
The class presents a practical approach to data structures for computer intensive products that can be proven to satisfy correctness and performance requirements. One can obtain almost any data structure from a book or online. However, it takes experience to identify data structures known to provide the desired behavior; to extend them to satisfy the specific application; and to evaluate the deliverables to show that they satisfy the composite standard and custom requirements. The lectures, the project (three linked parts) and the exams are designed to provide students with such experience. This includes having projects which require sustained effort rather than last minute code-a-thons, exams written to elicit knowledge, not empty verbiage, and course policies which reward hard work and learning from mistakes. To put it bluntly, I'll do my best to help you to make mistakes and then support your efforts to learn from them. This is a thinking class, not an echo information class.
Larry Davis | 0301[edit]
| Day & Time | Location |
|---|---|
| TuTh 11:00am - 12:15pm | CSI 1122 |
Course Description
Sorting and searching (trees, tries, hashing), representations for higher dimensional data (kd trees, quadtrees and others), big data applications.
Hours per week
2 - 4 Hours per week
Languages Used
Fairly open. Java mostly
Recommended Prior Experience
Just the standard sequence through the 300 level.
Projects, Exams, or other Assessments
Usually 2-3 exams, 3 projects
Misc Info
Emphasis is on algorithms and data structures, not proofs. Projects designed to exercise methods covered in class.
