Official UCSB Catalog Description

CMPSC 8: Introduction to Computer Science

Not open for credit to students who have completed Computer Science 16 or Engineering 3.

Introduction to computer program development for students with little to no programming experience. Basic programming concepts, variables and expressions, data and control structures, algorithms, debugging, program design, and documentation.

What this course is about

This course is an introduction to Computer Science, and programming.

Computer Science is the study of abstractions and algorithms.

You probably use abstractions and algorithms every day—for example:

What are Algorithms anyway?

An algorithm is a recipe for solving a problem. Algorithms have to be both designed, and "coded" so the computer can carry them out

In the case of using an index, this is probably an algorithm you may have learned in grade school, and it has been so long since you learned it, that now you don’t even think about it—you just do it. Finding a space in a parking lot—and knowing when to give up and look elsewhere—is "just common sense"; this probably isn’t something you were ever "taught", or even have to think very much about. You just do it.

Computers don’t currently have this capability—i.e. the capability to "pick up things by common sense"—and it seems unlikely that they will within our lifetime—unless there are major breakthroughs in the field of Artificial Intelligence. Such breakthroughs have been predicted for a while, but they haven’t happened yet. (Maybe you’ll be the one to figure out how to achieve this!)

So, for the time being at least, it falls to humans to design algorithms that computers can use to solve problems. In many cases, these algorithms are "just common sense"—the computer equivalent of looking for an empty parking space in a parking lot (and knowing when to give up). Algorithms like this are easy to design. Many of the algorithms we’ll see in this course are like that.

In other cases, the algorithms are very complex, or very subtle, and coming up with them is a deep intellectual challenge. Furthermore, the impact of a better algorithm on society can be very large. For example, new algorithms in the field of computational science—modeling chemical and biological reactions with computer simulations—can lead to breakthroughs such as new drugs to fight disease, or renewable sources of energy.

And often, what goes along with finding a good algorithm is finding a good abstraction of the real world concepts we are interested in: cells, molecules, oil fields, words, sentences, students, courses, GPAs, etc. Algorithms and abstractions really go hand-in-hand.

Coding, or Writing Software, or Programming

Coding is expressing algorithms in a programming language.

Human languages such as English and Spanish are not very well suited for expressing algorithms—at least not for expressing them to a computer (they have their problems for communicating with humans too!). So, special languages are used. In this course, we’ll learn the Python programming language. We choose Python rather than Java or C++ because:

This course provides you with the opportunity to become a pretty good beginning programmer, and be well prepared for an intermediate programming course such as CS16 (the first course that counts towards the CS major at UCSB, and which requires at least one quarter of prior programming experience.)

I say that the course "provides an opportunity," because you will only become a good beginning-level programmer if you put a lot of time and effort into this course—that is true no matter how much thought and attention I put in my lectures, assignments, and exams

The swimming/guitar/painting analogy

You cannot learn to swim, play guitar, or paint from a textbook or a lecture. You can only:

The same is true of programming. Programming is not a series of facts to be memorized—you cannot "cram" for a computer science exam. You must practice, practice, practice.


Python cartoon

(Image credit: Randall Munro