cs 4 Computer Science Bootcamp
Winter 2018 - Credits: 4
Department of Computer Science
University of California Santa Barbara
- Instructor: Professor Çetin Kaya Koç
→ Koç is pronounced as "Coach"
- Class Schedule: Mon, Wed 3:30pm-4:45pm
- Classroom: Theater/Dance West (TD-W) 1701
- Instructor's Office Hours: Tuesdays 2:00-4:00pm
- Instructor's Office: HFH 1119
- Lab Schedule:
Friday 9:00am-9:50am, TAs: TBA
Friday 10:00am-10:50am, TAs: TBA
Friday 11:00am-11:50am, TAs: TBA
Friday 12:00pm-12:50pm, TAs: TBA
Friday 1:00pm-1:50pm, TAs: TBA
Friday 2:00pm-2:50pm, TAs: TBA
- Lab: PHELPS 3525
- Teaching Assistants:
Leonidas Eleftheriou (firstname.lastname@example.org)
Lucas Bang (email@example.com)
Michael Nekrasov (firstname.lastname@example.org)
- TA Office Hours: TBA
- TA Office:
Trailer 936 Room 104
- Please join the Piazza page for class discussions
- Check the class website and the Piazza page once a day
- Slides and course notes are in the folder
- Homework and Lab documents are in the folder
- The grades: cs4.htm
(The Code is your PERM number mod 98773
Announcements and Weekly Course Material
- We will have 7 Lab and 7 Homework Assignments
- Homework Assignments and Lab Reports are due Wednesdays 5pm
Either, upload an electronic copy to a Dropbox folder (to be provided)
Or, deliver a paper copy to the HW Box in HFH 2108
- Electronic copy of your homework or lab report can be
in Text, PDF or MS Word. You could also scan/pdf your
handwritten work, however, do not submit small and/or
low-resolution phone-camera images.
- Midterm Exam: Monday, February 26, during class
- Final Exam: Friday, March 23, 12-3pm, in class
- You need the College of Engineering accounts in order
to use the computers in the Lab
Open your browser and click on this link:
Enter your UCSBNetId and Password, then follow the steps to
request your account
- Lab Assignment 01: lab01.pdf --
This lab does not require a report submission.
Participation in the lab is necessary and sufficient.
- Homework Assignment 01: hw01.pdf --
due 5pm Wednesday Jan 24
An introduction to computational thinking, computing,
data management, and problem solving using computers,
for non-majors ONLY. Topics include coding basics,
representing code and data using a computer, and applications
of computing that are important to society.
Weekly Course Plan
- Lecture 01:
What is information?
How do we represent information?
What is data?
Analog versus digital.
- Lecture 02:
Representation, Computation, and Storing
History of number representation and calculation.
Binary, decimal, and hexadecimal number systems.
History of calculation and computers.
- Lecture 03:
Representation of Text
Representation of simple text and structured text.
Text encoding standards: 7-bit and 8-bit ASCII, Unicode, and UTF-8.
- Lecture 04:
Representation of Images
Color, intensity, and pixels.
Tradeoffs in representation.
Image formats: headers, compression algorithms, Huffman coding.
- Lecture 05:
Representation of Sound
Analog sound and digital sound.
Sampling and quantization.
Digitized music and distortion.
Sound compression and decompression.
- Lecture 06:
Overview of Programming and Operating Systems
Principles of programming.
Programming languages and platforms.
- Lecture 07:
A simple introduction to Python.
Input, Output, and Debugging.
Repetition and conditional statements.
- Lecture 08:
Iterative computations of sums and products.
Computing sums of products and or products of sums.
Computation of constants such pi or e.
- Lecture 09:
Types of recursion.
Recursive algorithmic paradigms.
Numerical examples and time/space estimates.
- Lecture 10:
The Arithmetic Model of Computer.
Time/Space and Determinism/Nondeterminism,
Difficulty of problems and hierarchies of problems.
Limits of computation and decidability.
- Lecture 11:
Basic Arithmetic Algorithms
Addition of integers.
Various adders: carry-propagate, carry-save, and carry-lookahead.
Multiplication using add-shift methods.
Simple recursive algorithms and Karatsuba.
- Lecture 12:
Advanced Arithmetic Algorithms
Cyclic and Linear Convolution.
Fourier and Fast Fourier Transformation.
Error-Detecting and Error-Correcting Codes.
- Lecture 13:
Searching and Sorting
Ordering data. Data structures.
Linear search and binary searc.
Heap and binary tree.
Sorting by searching.
Bubblesort, Heapsort, Quicksort, and Mergesort.
- Lecture 14:
Analytical versus Numerical Computation
Solving differential equations using analytical methods.
Making sense of the solutions.
Solving differential equations using numerical methods.
Euler, Runge-Kutta, and pitfalls of numerical computation.
Hilbert matrix and Wilkinson polynomial.
- Lecture 15:
Numerical and Symbolic Computation and Tools
Products, sums and solving equations symbocally.
Matrix computations. Matlab and Mathematica.
Weekly Lab Plan
- Lab 01:
The purpose of the lab is to obtain your COE account and to
locate and experiment with some applications that we will
need in the subsequent labs. The computer lab is located in
Phelps 3525. We will help you to create your account and
experiment with Linux, Python, and Mathematica.
- Lab 02:
Students get CSIL accounts or use their own laptops. Illustrate
how a simple text is a collection of bits. Similar illustrations
of text in other languages (Latin, Arabic, Chinese, and Japanese).
Illustrate structured text (such as MS Word documents) representation.
- Lab 03:
Computing Using Python
Introduction to Python programming language.
Basic data types.
- Lab 04:
Computing with Images
Illustrate how a simple image is represented using cImage (Python).
Color schemes and RGB.
Simple image processing: Grayscaling, resizing, edge detection.
Image compression and watermarking.
- Lab 05:
Recursive Computing and Fractals
Install and use Python and turtle module to illustrate recursive
algorithms and programs. Koch curves and Hilbert Curves.
- Lab 06:
Scientific Computing Tools
Illustrate Matlab and Mathematica. Infinite precision computation.
Solving equations. Plotting. Algebraic operations, symbolic
computation, factoring, simplification.
- Lab Participation and Reports: 25 %
- Homework Assignments: 25 %
- Midterm Exam: 20 %
- Final Exam: 30 %
Integrity at UCSB ←
Dr. Çetin Kaya Koç