Course Information and Introductions

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Course Information and Introductions

• Intro to Computer Science
• CS1510
• Dr. Sarah Diesburg

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Instructor

• Sarah Diesburg (diesburg_at_cs.uni.edu)
• Office 311 ITTC
• Office hours MW 2-3pm, TTh 3-5pm, by appt.
• Class website
• http//www.cs.uni.edu/diesburg/courses/cs1510_sp1
  5/index.htm
• UNI eLearning

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Teaching Assistants

• Jordan Baker bakerjal_at_uni.edu
• Lab Assistant (1000am), Grader
• Huy Nguyen nguyehad_at_uni.edu
• Lab Assistant (800am)

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Class Schedule

• Lecture M W F 900-950am in 328 ITTC
• Mandatory
• Three lectures per week
• Lab
• Section 1 Thurs 800-950am in 112 Wright
• Section 2 Thurs 1000am-1150am in 339 Wright
• Also mandatory
• Hands-on work on projects for points
• TA and I are available

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Today

• Passing along attendance sheet
• For rest of lectures, please sign by your name
• Class objectives
• What is computer science?
• Logistics

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What is computer science??

• Computer science is a discipline that involves
  the understanding and design of computers and
  computational processes
• And its a REALLY diverse discipline

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VirtualEnvironments
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What do these things have in common?

• They all treat the computer as only part of a
  bigger picture
• They all treat the computer as a tool!

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Which tool would you rather use?
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Just like other tools, we have to be careful they
arent misused
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But how do we turn a computer from that thing on
our desk

• To that powerful tool
  that helps us solve problems?

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Programming!

• Programming is the process of writing, testing,
  and maintaining the source code of computer
  programs
• Collection of instructions that describe a task,
  or set of tasks, to be carried out by a computer
• While this course is an introduction to computer
  science, it focuses on how we can program the
  computer to be the tool we need!

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A Well-Educated Computer Scientist Should be Able
to...

• Apply the fundamental concepts and techniques of
• computation,
• algorithms, and
• computer design
• to a specific problem

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Our Goals This Semester

• Increase our problem solving skills
• Design good solutions to problems
• Test how well they are indeed solutions to the
  problem
• Provide the solution as a readable document

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A brief look at course logistics

• Take the time outside of class to thoroughly read
  the course syllabus.
• Some highlights

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Why two websites?

• eLearning is for interaction
• Submit assignments and labs, view your grades
• Traditional website is for notes, labs, and other
  downloads
• Demo

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Prerequisites

• None
• Some of you may have programming experience,
  others may not
• Either way is fine

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Required Skills

• Time and patience

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Course Material

• Lecture notes (posted at the class website)
• Textbook
• The Practice of Computing Using
  Python (2nd edition), by William
  Punch and Richard Enbody

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Class Grading
Activity Number Points
Class Participation/Attendance 14_at_5 pts each 45
In-lab Work (Thursday) 13_at_10 pts each 130
Programming Assignments 11_at_25 pts each 275
Midterm Exams 1 and 2 2_at_150 pts each 300
Final Exam 1_at_250 pts each 250
Total 1000
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Grading Scale

• 100 92 A
• 91.9 90 A-
• 89.9 88 B
• 87.9 82 B
• 81.9 80 B-
• 79.9 78 C
• 77.9 72 C
• 71.9 70 C-

• 69.9 68 D
• 67.9 62 D
• 61.9 60 D-
• 59.9 0 F

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Your Responsibilities

• Understand lecture and reading materials
• Attend office hours for extra help, as needed
• Uphold academic honesty
• Turn in your assignments on time
• Check class web page and your UNI email account
  and regularly

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Dos and Donts

• Do share debugging experiences
• Do share knowledge of tools
• Do acknowledge help from others
• Do acknowledge sources of information from books
  and web pages

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Dos and Donts

• Dont cheat
• Dont copy code from other people or websites
• Dont paraphrase code from others either
• E.g., changing variable names indentations
• Will be using sophisticated plagiarism checker
• http//www.uni.edu/policies/301
• Dont post code to the discussion board

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Course Policies

• Attendance mandatory
• There are no make-up exams for missed exams
• Honor code read your student handbook
• Students with disabilities
• Report to Student Disability Resource Center
• Bring me a letter within the first week of class

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To see or not to see me TAs

• We are not psychics
• Please let us know if
• Class is too hard
• You dont have the background
• Class can be improved in certain ways
• When in doubt, email us

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Survival Tips

• Do post messages and read the discussion board
  frequently
• Sign up to receive emails
• Do not post code on the discussion board
• If you absolutely need someone to look at your
  code, contact me or the TA
• Web search engines are your good friends

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Programming Environment

• Python freely available online (www.python.org)
• But get version 3.4.1
• Do NOT get version 2

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Guidelines for Success in this Course

• Prepare for lecture! Read the text selections
  before the start of lecture and complete any
  class prep assignment
• On previous course evaluations, the NUMBER ONE
  answer to the question I could have improved my
  learning in this course by was some variation
  of read the textbook

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Guidelines for Success in this Course

• Be on time. Class sessions will start promptly. 
  I will collect assignments at that time and will
  often start with important announcements.
• Write code on your own! Think of simple problems
  on your and solve them.  If you wonder "what if,"
  TRY IT!

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Guidelines for Success in this Course

• Start assignments early so you have time to ask
  questions.
• Face to face questions are better than email
  questions.
• If you email me the night before something is due
  you shouldnt get mad if I dont respond.
• If you spend more than 15 minutes staring at the
  computer stuck on something, ask for help! 
• Make use of the office hours early! Don't wait
  until late in the term to seek help.

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Guidelines for Success in this Course

• You can (and should) program from home
• Remember, programming takes practice
• Make sure that your code runs in the lab
• Verify that code that runs on another machine
  actually runs in the lab so there are no
  surprises at grading time

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Guidelines for Success in this Course

• Finally, remember, programming takes practice.
  You may not get it the first time, but keep
  trying, asking for help, and caring. Eventually,
  you might find out that you are pretty good at
  this whole process!

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Rooms you should know!

• ITTC 328 Lectures
• ITTC 305 The departmental office
• ITTC 311 My office
• ITTC 335 Student Lounge
• Wright 112 Section 1 lab. Can also work in
  here outside of lab times.
• Wright 339 Section 2 lab. Can also work in here
  outside of lab times.

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To Do

• Buy a class thumb drive for your labs and
  assignments.