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CS 146
The Big Picture in
Computer Science
PROF. DANIEL ERNST
FEBRUARY 7TH, 2011
SUCCESS IN COMPUTER SCIENCE
Success in Computer Science
 As an undergraduate CS student, you want a
roadmap to success
 Issue: There are many components to success in CS:
 Curricular Activities (Courses)
 Co-Curricular Activities
 Preparation for Post-Undergraduate Life
 Overall Planning
Curricular Activities
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Curricular components
Course and Program Selection
 Studying / Course Work
 Grades
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Course Selection
 Many major courses decided for you
 There are still some choices
 CS Electives – how to choose?
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CS Comprehensive - ENGL 305 or ENGL 308 or CJ 202?
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Explore current interests, possible areas of specialization
Take courses useful for likely jobs
Take courses to help prepare for graduate school (e.g. CS 450)
ENGL 305 – Communicating Scientific Subjects to General Audiences
(communication –writing)
 Also counts toward GE 3xx-level requirement (Three 3xx-level courses)
ENGL 308 – Scientific Communication for Expert Audiences (communication –
writing)
 Also counts toward GE 3xx-level requirement (Three 3xx-level courses)
CJ 202 – Fundamentals of Speech (communication – speaking)
GE Courses – Strategies and Tactics
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Take courses that you’re interested in
Take courses that fit best with your major (and minor) program(s)
Take courses that meet multiple requirements to free up other slots
Program Selection
 Which major?
 Computer Science – Comprehensive (63 cr.)
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Computer Science – Software Engineering (39 cr.)
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Similar amount of computer science to CS-Comp.
 Only differences: not CS 462 (Networks), one less CS elective
Less mathematics, required Physics for science lab sequence
Requires minor (24 cr.)
Computer Science – Computer Engineering (68 cr.)
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Broadest array of computer science courses
More mathematics, required Physics for science lab sequence
Requires some other courses (communication, ethics) under GE
A computer science degree with an emphasis on computer hardware and
engineering issues
Useful for working in computer hardware industry, positions including
hardware verification and testing
Computer Science – GIS (68 cr.)
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Combination of computer science + study of geographic information systems
Program Selection (2)
 Which minor, if needed?
 Information systems
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Mathematics
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Additional problem solving tools for toolset, some practical
applications (e.g. probability and statistics, digital signal
processing)
Any area that you can combine with computer science
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Complementary to CS, added understanding of business
E.g. Biology, Physics, Criminal Justice (Forensics), maybe
Materials Science in future?
Any area that you’re interested in
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E.g. Music, Foreign Language, others…
Studying and Course Work
 Read assigned materials
 Several computer science instructors work primarily with PPT slides;
don’t forget how to read technical material!
 Review periodically
 Helps anchor and integrate material
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Important with comprehensive nature of CS
 Study with others (at least some of the time)
 Especially if you’re not well-disciplined at studying on your own
 Try to study with others at or above your level – this helps you to rise to
their level
 Study actively
 Try to ask “what if” questions, e.g.
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Does this algorithm really work (correctly / efficiently)?
What other approaches are there here?
Is there a better approach possible?
Studying and Course Work
 Participate in class actively
 Ask questions
 Comment where appropriate based on your own experience
 Understand what the instructor is looking for
 Read carefully, solve the problem asked, not the problem you
would like to see asked
 Be complete, thorough and organized
 Use a variety of problem solving techniques (more
later)
Grades
 GPA review
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How is GPA calculated?
How is GPA used?
Honors for semester, degree
 Internship and full-time job applications
 Perhaps the most important factor!
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 Team Exercise
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Effect of bad first year
Effect of one bad course on semester GPA
C if averaging B’s
 F if averaging B’s
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Effect of one bad semester after three good semesters
Grade Point Exercise
First Question – Difficulty of Recovering from
Bad Start
 Assume 15 credits per semester
 Ima Student figures he can “catch up later” and
doesn’t need to take school seriously the first year
 Has two semesters averaging 2.3
 What does Ima need to average in his sophomore
year to raise his GPA up to 3.0 by the end of that
sophomore year?
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Remember: many internship employers require/prefer a GPA
of 3.0
 Divide into teams of 2-3, work this out
First Question – Answer
 Freshman: 30 x 2.3 = 69.0
 Sophomore: 30 x ? = ?
// 2.3 = C+
 Total Desired (by end of sophomore year)
 60 x 3.0 = 180.0
 180.0 – 69.0 = 111.0
 111.0 / 30 = 3.70
// 3.7 = A-
 Ima has a lot of pressure for the second year
 Likelihood of accomplishing this is small
Second Question – Effect of One Bad Semester
After Good Start
 Assume 15 credits per semester
 Ima Student starts strong for three semesters, but
has a bad fourth semester due to family and health
issues
 Has three semesters averaging 3.2
 Fourth semester GPA is 2.5
 What is Ima’s GPA after four semesters?
 Again, divide into teams of 2-3, work this out
Second Question – Answer
 First 3 semesters: 45 x 3.2 = 144.0
 3.2 GPA = ~B+ (a little less)
 Fourth semester: 15 x 2.5 = 37.5
 Total (by end of sophomore year)
 60 credits, 181.5 grade points
180.1 / 60 = 3.025
// 3.025 = B
 Ima is still above the 3.0 threshold
Questions for Reflection
 When is it easier to change/have an effect on your
GPA – earlier or later in your university career?
 Which semesters matter most in establishing a good
GPA?
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Consider the mathematical reasons, but also psychology and
other factors
 How are you going to use this information in your
university career?
Grades (2)
 How to get good grades in CS courses?
 Complete all assignments
 Do your share of the work (or more) on team assignments
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Team projects will often ask for each member of the group to
anonymously evaluate all members’ participation
Make sure you learn the material; don’t leave unanswered
questions
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Computer Science is very comprehensive!
Co-Curricular Activities
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Co-Curricular Activities
Club participation / leadership
 Part-time work
 Study abroad
 Internships
 Job Search
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Club Participation and Leadership
 Computer Science clubs
 Student ACM
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ACM = Association for Computing Machinery, primary professional
organization for computer scientists
Student club – social, service, educational, networking with other students,
possible employers
Professional organization – separate student membership, access to magazine
and CS literature
WITS (Women In Technology and Science)
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Similar – social, service, educational, networking
All interested students welcome
 Benefits of membership
 Meet other CS students
 Activities
 Opportunity to run for and be a club leader, help guide club in future
year(s)
Part-Time Work
 Benefits
 Generate funds for school
But remember your primary goal – education
 Work should never be an excuse for not doing well in school
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Obtain additional CS-relevant experience (if a job that utilizes
CS skills: system administrator, web developer, help desk staff,
etc.)
 Issues
 Can interfere with course work, especially group meetings
 Overall
 Make sure part-time work is compatible with your course work
Study Abroad
 Benefits
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Learning about another culture
Experiencing the diversity of the world
 Issues
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In past, often just GE credits
Now, are some institutions that offer CS courses that may transfer
 Recommendations
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Talk to your adviser early (freshman year) if you are interested in
study abroad
Second-semester sophomore year is the best semester for study
abroad
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Required course: one elective (CS 268 or CS 278) that can be taken
another semester, doesn’t interfere with prerequisite chain
Internships
 Temporary work (often full-time during a summer, possibly including another
semester) with an employer
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Can be for pay, credits, both
Often summer after junior year, but can be after sophomore or even freshman year if you have
experience that matches employer needs
 Benefits
 One of the important accomplishments in the eyes of companies hiring for full-time positions
 A good experience (from the employer’s perspective) on an internship is often the gateway to a fulltime job offer
 Opportunities to explore internships
 CS Career Breakfast and UWEC Career Fair (late September)
 Internship Mania (February)
 Through Career Services online listings
 Prerequisites
 Have a resume prepared, reviewed by CS faculty and Career Services
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Often WITS workshops on this in fall before UWEC Career Fair
In some cases, minimum GPA requirements (e.g. 3.0)
 If want credit, must work with Dr. Jack Tan (CS Internship Coordinator) – do this in
advance
Job Search
 Necessary to be pro-active
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Can’t wait for employers to come to you
 Same opportunities as for internships:
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CS Career Breakfast and UWEC Career Fair (late September)
Internship Mania (February)
Through Career Services online listings
Also other contacts:
Employers speaking at CS 396 (Junior Seminar)
 Employers met through talks, club events, etc.
 Personal contacts
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Prerequisite
Again, having a good resume is key
 Also want strong recommendations from faculty
 May be minimum GPA requirements (e.g. 3.0) here too
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After UWEC
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Options:
Job in CS
 Graduate School in CS or other area
 Job in another area
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Job in CS
 Many different possibilities
 Consider areas previously discussed
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Application vs. systems
 Major CS employers
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Marshfield Clinic (Marshfield, WI)
Great Lakes Higher Education (Madison/Eau Claire, WI)
Liberty Mutual Insurance Company (Wausau)
Northwestern Mutual Insurance Company (Milwaukee)
3M Corporation (St. Paul, MN)
IDEXX Systems (Eau Claire)
 Other employers of CS students
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IBM (Rochester, MN)
Menards / Midwest Manufacturing (Eau Claire)
McKesson Surgical/Medical (Minneapolis)
C.H. Robinson (Minneapolis)
Silicon Logic Engineering (Eau Claire)
Many others…
Graduate School
 Approximately 5-10% of CS students go directly on
to graduate school in CS
 Worth considering if interested in teaching, research,
or advanced/focused work
 See:
http://www.cs.uwec.edu/~wagnerpj/talks/GradScho
ol.ppt for more information (Student ACM talk given
by Dr. Dan Ernst and Dr. Paul Wagner of UWEC CS)
 Will need recommendations from faculty
Job in Other Area?
 Always possible to use CS as a supplement to a job in
another field
 Students have gone on to jobs such as:
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Teaching English in foreign countries
Document translation
Web design
 Issue
 Easy to get stale technically, may limit future options
 However, CS knowledge is always helpful
Planning
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Planning includes:
Considering options
 Making choices
 Being an active participant in your undergraduate education
 Organizing your time
 Thinking ahead
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Considering Options
 Choices are made out of all available options
 Make sure you don’t limit your options
 Examples:
 Student not attending class and not doing well
 Student not attending class but doing well in class – later
issues
 Student not attending class but not officially dropping
 Goal: leave yourself more options where possible
Making Choices
 Carefully consider each option for:
 Advantages
 Disadvantages
 Other implications
 Consciously choose and act on the option you prefer
 Ownership translated to success
Being Active
 How you can you be active in your CS education?
 Many ways:
 Active participation in class
 Active consideration on choices for major, minor, CS electives,
GE courses
 Active consideration of co-curricular options
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While making sure that all choices reasonably fit within your
schedule
Talk to instructors, understand the course requirements
What accomplishments expected?
 What participation expected?
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Organizing Your Time
 Treat studying and review like a class
 Set aside standard periods of time each week to work on your
courses
 For team projects, communicate with team members
to identify common times to meet regularly
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Requires flexibility and cooperation
 Budget time for everything, including co-curricular
interests
Thinking Ahead
 Your undergraduate career is a “knapsack problem”
 Knapsack problem – famous CS optimization problem
Many objects of different weights and values (not proportionate);
all have some value...
 How to determine the optimal set of objects to put in your
knapsack/backpack that will give you the most value while staying
within a given weight limit?
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 We really need a “forward advising” system to
supplement degree audits
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Backward advising – how does what you’ve done fit into a
degree plan?
Forward advising – what should you do and when should you
do it to successfully complete a degree program?
Thinking Ahead (2)
 Putting it all together
 Consider your options regularly
 Develop a plan early, but be ready to change it if necessary
(and reconsider it regularly)
 Develop the discipline for completing course work,
participating in class, and active learning that will allow you to
succeed in CS
 Make sure you keep your options open
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Don’t back yourself into a corner with no/few options
Thinking Ahead (3)
 Key Timeline Items – Sample Schedule
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Freshman year
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Sophomore year
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Continue to do well
Develop your resume
Study abroad 2nd semester if desired
Run for office in club
Junior year
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Do well in your courses!
Consider exact major, minor, clubs, work, study abroad, act on some…
 Join SACM and/or WITS
Continue to do well
Update resume, investigate internship possibilities
Apply for internships
Do internship – summer
Senior year
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<you get it…>
Update resume, investigate full-time job possibilities
Apply for full-time job
Graduate, start that job…
Computer Scientist
of the Week
AUGUSTA ADA KING,
COUNTESS OF LOVELACE
(1815-1852)
Ada Lovelace
Analyst, Metaphysician, and
Computer Scientist(?)
 Born Augusta Ada Byron:
Only (legitimate) child of the
famous poet Lord Byron.
 Her father left when she was 1
month old, died when she was 9.
 Her mother, fearful that Ada
would also get the “poet gene”,
immersed her in mathematics
from an early age.
Training and Family
 By 17, she was an accomplished Mathematician
 Among her tutors was Augustus De Morgan
 At that time, she met Charles Babbage, who was
impressed with her intellect and they began
corresponding regularly.
 In 1835, at 19, she married William King, who
became the first Earl of Lovelace.
 They had 3 children, born between 1836 and 1839.
 All indications were that she “ran the show”.
The Analytical Engine
 In 1834, Babbage came up with the design of the
“Analytical Engine”.
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His Parliamentary sponsors wouldn’t fund its creation because
he hadn’t finished the Difference Engine yet.
 In 1842, Italian mathematician Luigi Menebrea
wrote a memoir (in French) about Babbage’s
Analytical Engine.
 Babbage asked Ada Lovelace to do the translation of
Menebrea’s work to English, with annotations.
Ada’s Notes
 Over the course of the next year, she performed the
translation, but also appended many of her own
notes.
 The Notes, when completed, were longer than the
original text, and included striking observations
about the Analytical Engine.
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Most commonly cited: An algorithm to compute Bernoulli
Numbers using the Analytical Engine – considered by many to
be the “first computer program”.
 Ada saw far more potential from the machine than
Babbage did, and she was better at articulating it.
Legacy
 Died of cancer in 1852
 Considered by many to be the
“First Computer Programmer”
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Some claim that she was also much more involved in the design
of the Babbage engines than was previously believed.
 The US Department of Defense’s official language is
called “Ada”
 Since 1998, the British Computer Society has given out
a prestigious award in her name
 Ada Lovelace Day – March 24th.
Computer Scientist
of the Week
AUGUSTA ADA KING,
COUNTESS OF LOVELACE
(1815-1852)