OSU Post-Bacc

I enjoy blogging for a number of reasons. It helps me organize, solidify, and advance my thinking. It also provides a platform to put my ideas into a bottle and send it out into the ocean that is the internet. Every so often, a bottle with a message returns to me, usually in the form of an email in my inbox. Most of those emails are about people asking for guidance through (or to get into) Oregon State University’s post-baccalaureate or Georgia Tech’s Master of Science computer science programs.

While I’m still working through GT’s program (should be done spring of 2021!), my time at OSU wrapped up in August of 2019 with a Bachelor’s in Computer Science. As I owe a lot of my personal success to the resources and communities that have sprung up around the program, I wanted to use a moment to write about my path through the degree in the hopes of leaving some breadcrumbs to new and prospective students.

This summer, I’ll wrap up a computer science degree from Oregon State University. The experience has been rewarding, difficult, and incredibly eye-opening.

After the first quarter at OSU, I was not sure that the program was for me. While learning C++ was a nice wrinkle, the “Introduction to Programming” courses that served as my welcome were underwhelming. In hindsight, this perspective makes sense as someone that was coming in with years of experience managing and delivering web projects for large clients with large expectations. Learning the structure of for loops, classes, and a brief dalliance into recursion was not really what I had signed up for. However, after the fourth quarter I was trying to plot a path to continue my education far beyond the 15 courses that were required to get another bachelor’s.

It wasn’t the fact that OSU continued to underwhelm that drove me to look beyond the program – quite the opposite. OSU provided a window into a world that I didn’t know existed. It’s fair to say that two years ago I did not know what a computer science degree entailed or what it prepared you for. Two years later and I can’t imagine a world where I don’t continue to explore the field.

I rarely look at C while at the office. In many ways, it’s a language of a bygone era, especially when you’re talking about web application development. Sure, we take advantage of C every day, but write in it? Never.

However, I’ve become fairly proficient in it these past two years and have grown to appreciate the language for what it is: Blazing fast and fine-tuned for several specific use-cases. Unlike JavaScript (my language of choice while at work), C does not come with dozens of associated frameworks that come and go on a moment’s notice. It also doesn’t split its time between the hard logic of an application and managing the user interface. In many ways, C runs the world of computers around us without us even knowing.

The story behind C is the most interesting part of the language. Written in the late 60’s and launched into production around 1972/1973, C was born from necessity. In the late 60’s, Dennis Ritchie and Ken Thompson decided to write an operating system for the PDP-11, Unix (pictured above – it’s the size of a huge refrigerator and it’s processing power isn’t even close to the power of my phone).

I’m over halfway through Oregon State University’s post-bacc computer science program. It’s a (mildly) grueling gauntlet of 15 courses, made more grueling by the fact that I’ve been working full-time and taking two-courses a quarter (with an exception made for this past summer when only one course was on the docket to give me some time to get married 🙂 ). To-date, I’ve taken, or am currently taking, the following courses (in no particular order):

• Introduction to Computer Science I
• Introduction to Computer Science II
• Discrete Structures in Computer Science
• Data Structures
• Web Development
• Introduction to Databases
• Computer Architecture & Assembly Language
• Analysis of Algorithms
• Operating Systems (currently in progress)
• Software Engineering I (currently in progress)

Another week of reading, lectures, and confused Googling and skimming through videos is in the bag. This week was all about NP-complete. It has been fun to experience an “aha!” moment in each course I’ve taken so far, and this was an especially fun one. In large part, because seeking answers to these questions is seemingly beyond the reach of computers (in a reasonable time).

We’re accustomed to computers being incredibly fast. So accustomed that we forget just how fast they are. They’re really fast. I’m writing this on a 4-year old computer. It has a 2.5 GHz Intel Core i7 processor. That number equates to how many cycles the system clock of this computer runs in a second. So 2,500,000,000 cycles in one second. The version of the CPU  running on this machine is quite powerful. It should execute around 9 instructions per cycle for a single core in the processor and there are 4 total cores running.

This all adds up to a lot of numbers and those numbers represent commands that we expect the computer to execute for us so that we can….. I dunno….. watch videos of cute cats.

Having just finished my midterm in Analysis of Algorithms (yes, the class is as dry as it sounds), my brain is still sharp on a few topics; one of them being dynamic programming, which I mentioned in my last post. In that post, wherein I tried to find motivation for forcing myself to relearn calculus, I used the classic example of trying to calculate the nth term of the Fibonacci sequence.

I thought it would be helpful to see this example running with some real code. Below, we have a JavaScript function – fibRecursive – that takes an integer as a parameter. This integer represents the term that we want from the Fibonacci sequence. For example, a call to the function like so fibRecursive(6) would return 8.

This is a question that is plaguing me at the moment as I force myself to relearn calculus for Analysis of Algorithms at Oregon State University. In moments like this, where the concepts are abstract and I need to learn even more abstract concepts so I can understand the first class of abstract ideas, motivation is key.

Well, the short answer is that you don’t need this body of knowledge to develop a wide range of applications and features to applications. In my world, many of the concerns that common sorting, searching, and general optimization algorithms address are not real concerns because they’ve been abstracted to parts of the language or framework. I’m able to do my job because someone else has figured out how to do other parts of my job that normally would need to be created from scratch. So while learning merge sort and analyzing its complexity is a fun exercise, I’ll not be writing it from scratch anytime soon.

I’m about halfway through Oregon State University’s (Go Beavers!) post-bacc program for computer science, but feel like I’ve just entered the belly of the beast. On the docket for the summer is CS 271 – Computer Architecture and Assembly Language; a fine relaxing course to take in the months before and during my wedding, right? Not so much.

The material is dense as we learn to program how to move memory around on a computer and perform basic actions on the contents of said memory.  The class is focused on the IA-32 – a 32-bit version of the x86 instruction set architecture found in early IBM workstations and personal computers, and then later in embedded systems for phones, aerospace tech, and electronic musical instruments.  I’m only a few weeks in, but already it’s painfully obvious to me that assembly is not like any other language I’ve used.