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| CSCE101 Course Information
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| Time |
2:30-3:20pm MWF |
| Location | 217 Ferguson |
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| Instructor |
Chuck Cusack |
| E-mail | cusack@cse.unl.edu |
| Office | 108 Ferguson |
| Phone | 472-2615 |
| Office Hours | MWF 10:30-11:20am,
and by appointment |
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| Graders | Xiaoyu Yao |
Dong Li |
| Items | Homework | Quizzes |
| Offices | 501 Bldg Room 5.9 | 501 Bldg Room 2.8 |
| Phones | 472-5029 | 472-0820 |
| e-mails | xyao@cse.unl.edu | li@cse.unl.edu |
| Office Hours |
T 2:00-3:30pm |
M 10:00-11:00am |
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| Textbook |
Computer Science: An Overview, 7th Edition,
J. Glenn Brookshear, Addison-Wesley, 2003
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| Coverage |
This course is a breadth-first introduction to computer science.
What that means is that you will learn a little bit about a wide range
of computer science topics.
This course is NOT a computer literacy or programming course.
You will not learn to read e-mail, use Word or other programs, or
work with spreadsheets. You will also not be writing lots of computer
programs.
The purpose of the course is not to give you some
skills that will be useful in whatever your future career is. The purpose
is simply to give you a flavor of what computer scientists do.
The main topics of the course include
- What is Computer Science
- Data Representation (binary, hexadecimal, ASCII, etc)
- Digital Logic
- Data Manipulation
- Machine Organization
- Operating Systems
- Networks and Communication
- Algorithms
- Programming Languages
- Data Structures
- Databases
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| Reading the Textbook |
Before class each day you should read the sections of the textbook listed
on the schedule for that day.
Be sure the read the entire section(s) indicated. Each class will start with
question you may have about what you read. After clearing up any confusions,
we will spend class time doing examples and solving related problems.
If you are not doing the assigned readings, you will not get nearly as much
out of the course as possible, and it is likely your grade will reflect that.
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| Suggested Exercises |
After you read each section, attempt as many of the suggested exercises
as you are able.
Some suggested exercises will ask you to solve similar problems for different
sets of data. If you are certain of how to do the problems after doing
a few, you should feel free to skip the similar problems. However, sometimes
the other problems will have subtle differences that make the solutions
slightly (and sometimes totally) different, so make sure you really understand
what you are doing if you skip problems.
Answers to the suggested exercises are in the back of the book.
Use the answers to check your work after you have already made an honest
attempt at solving each problem.
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