Computer Science
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Intro to Computing: Robotics |
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Professor:
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Theresa Law |
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Course
Number: |
CMSC 113 |
CRN Number: |
90156 |
Class cap: |
18 |
Credits: |
4 |
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Schedule/Location:
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Mon Fri 1:30 PM
- 2:50 PM Reem Kayden Center 107 |
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Distributional Area: |
MC Mathematics and Computing |
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Crosslists: |
Mind, Brain, Behavior |
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This course introduces students to ideas that are
fundamental to robotics and to computing in general. Teams of students will design and build
shoebox-sized robots, with guidance from the instructor. These rather minimalist robots will be
mobile and will have multiple sensors.
The student teams will use a simple programming language to program
their robots to carry out simple tasks, and will move to a more robust
programming language and more complex tasks by the end of the semester. |
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Introduction to Data Analytics and R
Programming |
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Professor:
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Jordan Ayala |
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Course
Number: |
CMSC 121 |
CRN Number: |
90157 |
Class cap: |
18 |
Credits: |
4 |
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Schedule/Location:
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Tue Thurs 1:30 PM
- 2:50 PM Reem Kayden Center 100 |
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Mon 1:30 PM
- 3:20 PM Reem Kayden Center 100 |
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Distributional Area: |
MC Mathematics and Computing |
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Crosslists: |
Environmental Studies |
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Data analytics, the process of analyzing, revealing,
interpreting and visualizing information concealed inside big data, is
revolutionizing daily life, as used by companies such as Amazon, Google and
Facebook, for the diagnosis of medical conditions or the way medical claims
are handled, for investment strategies and real estate pricing, and in
academia, with the analysis of historical texts, understanding the
deliberations of the Supreme Court or the European Commission, or processing
large amounts of genomics data. In this class, students will be introduced to
techniques, implemented via programming in R, to manipulate and pre-process
data into manageable forms, perform analyses from a descriptive and
predictive standpoint, and learn the basics of visualizing the result, all
with a focus on story telling through data, enhancing data literacy. |
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Object-Oriented Programming |
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Professor:
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Theresa Law |
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Course
Number: |
CMSC 141 A |
CRN Number: |
90158 |
Class cap: |
18 |
Credits: |
4 |
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Schedule/Location:
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Mon Wed 3:30 PM
- 4:50 PM Reem Kayden Center 107 |
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Thurs 3:30 PM
- 5:30 PM Reem Kayden Center 107 |
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Distributional Area: |
MC Mathematics and Computing |
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Crosslists: |
Experimental Humanities; Mind, Brain, Behavior |
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This course introduces students to the methodologies of
object-oriented design and programming, which are used throughout the Computer
Science curriculum. Students will learn how to move from informal problem
statement, through increasingly precise problem specifications, to design and
implementation of a solution for problems drawn from areas such as graphics,
animation, simulation. Good programming and documentation habits are
emphasized. |
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Object-Oriented Programming |
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Professor:
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Kerri-Ann Norton
and Sven Anderson |
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Course
Number: |
CMSC 141 B |
CRN Number: |
90159 |
Class cap: |
18 |
Credits: |
4 |
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Schedule/Location:
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Tue Thurs 10:10 AM
- 11:30 AM Reem Kayden Center 107 |
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Fri 10:00 AM
- 12:00 PM Reem Kayden Center 107 |
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Distributional Area: |
MC Mathematics and Computing |
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Crosslists: |
Experimental Humanities; Mind, Brain, Behavior |
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This course introduces students to the methodologies of
object-oriented design and programming, which are used throughout the Computer
Science curriculum. Students will learn how to move from informal problem
statement, through increasingly precise problem specifications, to design and
implementation of a solution for problems drawn from areas such as graphics,
animation, simulation. Good programming and documentation habits are
emphasized. |
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Discrete Math |
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Professor:
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Bob McGrail |
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Course
Number: |
CMSC 145 |
CRN Number: |
90160 |
Class cap: |
18 |
Credits: |
4 |
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Schedule/Location:
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Wed Fri 10:10 AM
- 11:30 AM Reem Kayden Center 101 |
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Distributional Area: |
MC Mathematics and Computing |
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Crosslists: |
Mathematics |
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Discrete mathematics includes those areas of mathematics
that are essential to computer science, information theory, combinatorics,
and genetics. This course emphasizes
creative problem solving, linking language to logic, and learning to read and
write proofs. The topics covered
include propositional logic, predicate logic, inductive proof, sets,
relations, functions, introductory combinatorics and discrete
probability. Applications drawn from
computation will motivate most topics.
Prerequisite: Mathematics 141 or programming experience. |
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Data Structures |
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Professor:
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Sven Anderson
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Course
Number: |
CMSC 201 |
CRN Number: |
90161 |
Class cap: |
18 |
Credits: |
4 |
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Schedule/Location:
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Tue Thurs 10:10 AM
- 11:30 AM Reem Kayden Center 100 |
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Mon 10:10
AM - 12:10 PM Reem Kayden Center 100 |
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Distributional Area: |
MC Mathematics and Computing |
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Crosslists: |
Mind, Brain, Behavior |
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This course introduces students to essential principles of
program design and analysis that underlie applications of computation to
internet communication, digital media,
and artificial intelligence. Building
on basic programming skills, we will focus on the construction of more
sophisticated and reliable computer programs that employ the most important
data structures. Data structures,
common ways in which data is organized and manipulated, are an important
aspect of modern programs.
Consequently, throughout the course students will learn to create and
use the most useful data structures, including files, lists, stacks, trees,
and graphs. Students will write
several programs, ranging from short lab assignments to larger systems of
their own design. Prerequisite: CMSC
141 or 143, or permission of the instructor. |
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Data Visualization |
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Professor:
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Valerie Barr |
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Course
Number: |
CMSC 222 |
CRN Number: |
90553 |
Class cap: |
18 |
Credits: |
4 |
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Schedule/Location:
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Tue Thurs 1:30 PM
- 2:50 PM Reem Kayden Center 101 |
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Mon 1:30 PM
- 3:30 PM Reem Kayden Center 103 |
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Distributional Area: |
MC Mathematics and Computing |
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Data has a story which has to be told! Data visualization
is all around us, in print and in electronic media. Some of it is accurate
and effective, while some is extremely unclear, confusing, or misleading. In
this course we will study various approaches to information visualization and
associated data analysis techniques. How do we take a lot of data, or very
complex data, and present it in ways that allow it to communicate information
clearly and effectively? The course will explore applications from science,
medicine, social science, and humanities. Prerequisites: CMSC 121 or
per-instructor based on knowledge of the R programming language. |
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Statistics for Computing |
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Professor:
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Kerri-Ann Norton
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Course
Number: |
CMSC 275 |
CRN Number: |
90162 |
Class cap: |
18 |
Credits: |
4 |
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Schedule/Location:
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Tue Thurs 1:30 PM
- 2:50 PM Reem Kayden Center 107 |
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Fri 2:00 PM
- 4:00 PM Reem Kayden Center 100 |
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Distributional Area: |
MC Mathematics and Computing |
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Crosslists: |
Mathematics |
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This course introduces students with prior object-oriented
programming experience to the basics of probability and statistical analysis.
Students will learn theory and implementation of statistical inferences used
in computer science research starting from fundamentals in counting and
probability distributions; and go on to cover monte carlo simulation,
bayesian inference, confidence intervals, t-tests, analysis of variance, and
clustering. By the end of this course students will learn how to set up
computational experiments, classify their data, and determine the appropriate
statistical test for their experiments. This course will consist of a written
component of practice problems and a coding component where students will
organize and/or create data, develop code for statistical analysis, and use
the code to analyze the dataset. Prerequisites: CMSC 11X, 141 or 143 (OOP),
and Precalc, or permission of the instructor. |
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Design of Programming Languages |
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Professor:
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Bob McGrail |
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Course
Number: |
CMSC 305 |
CRN Number: |
90163 |
Class cap: |
18 |
Credits: |
4 |
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Schedule/Location:
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Tue Thurs 10:10 AM
- 11:30 AM Reem Kayden Center 101 |
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Fri 12:00 PM
- 2:00 PM Reem Kayden Center 100 |
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Distributional Area: |
MC Mathematics and Computing |
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Crosslists: |
Mind, Brain, Behavior |
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This course will cover a selection of issues important to
the design of programming languages including, but not limited to, type
systems, procedure activation, parameter passing, data encapsulation, dynamic
memory allocation, and concurrency. In addition, the functional, logic, and
object-oriented programming paradigms will be presented as well as a brief
history of high-level programming languages. |
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Cross-listed Courses:
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Discrete and Computational Geometry |
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Professor:
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Ethan Bloch |
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Course
Number: |
MATH 313 |
CRN Number: |
90177 |
Class cap: |
15 |
Credits: |
4 |
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Schedule/Location:
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Tue Thurs 3:30 PM
- 4:50 PM Hegeman 308 |
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Distributional Area: |
MC Mathematics and Computing |
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Crosslists: |
Computer Science |
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Algorithmic Composition and
Improvisation |
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Professor:
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Matthew Sargent
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Course Number: |
MUS 380 |
CRN Number: |
90041 |
Class cap: |
12 |
Credits: |
4 |
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Schedule/Location:
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Tue 12:30 PM
- 2:50 PM Blum Music Center N119 |
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Distributional Area: |
PA Practicing Arts |
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Crosslists: |
Computer Science |
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