Introduction

About Me

Syed Fahad Sultan سید فہد سلطان

Pronunciation: Saiyyudh Fahad Sool-tahn

Just call me “Dr. Sultan” (click on the speaker for a short audio clip: 🔈)

How to Reach Me

Office: Riley Hall 200-H

Email: fahad.sultan@furman.edu

I don’t hold fixed office hours, but I’m available for on-demand meetings in real time. If you’d like to guarantee a time, you can schedule a meeting using this link. https://calendly.com/ssultan-dpq/15-minute-meeting.

About the Course

Course website: https://fahadsultan.com/csc272

The Syllabus is available on the course website. In particular, please make sure to read the Grading, Academic Integrity and Textbook and other Resources sections carefully.

All of the course content will be posted on this website.

Important announcements will be made on both the course website homepage and in class.

You are to submit assignments and exams on the course Moodle page. I will also upload all of your grades there.

How-to knowledge > What-is knowledge

Declarative knowledge is knowledge about facts. It is knowledge that answers the “What is” questions. Most courses outside Computer Science are about declarative knowledge.

In contrast, Imperative knowledge is knowledge about how to do things. It is knowledge that answers the “How to” questions.

While we will spend a non-trivial amount of time in this course on declarative knowledge, the overwhelming majority of this course will focus on imperative knowledge. Your grade in this course will be determined by your ability to apply declarative and more importantly imperative knowledge to solve problems.

Research shows that there is only one way to acquire imperative knowledge: Practice, Practice, Practice !. Practice combined with feedback is the only way to achieve mastery.

In this course, you will be given ample opportunities to practice along with regular feedback.

Assignments

Approach assignments purely as opportunities to learn, prepare for exams and to prepare for your career.

It is not worth cheating on assignments. Just come talk to me if you are struggling with an assignment. I will literally just tell you the answer.

You can schedule a time to get your assignments graded using this link.

Written Assignments:

Written assignments are to help you build a deeper understanding of algorithms and math covered in class.

These could simply be math problems or involve tracing algorithms and dry-runs.

Both handwritten or typed submissions are acceptable. Submissions, as always, on Moodle.

Programming Assignments:

Programming assignments are going to be posted at the start of the lab session each week and will be due before next lab, unless otherwise specified. You are to submit your code on Moodle.

You should expect questions in the exams similar to assignments.

Asking Questions

Given the glut of information accessible online and otherwise in this day and age, meaningful interactions with your peers and teachers is essentially why you are paying your college tuition.

To encourage this, I have allocated 5% of your course grade to asking questions.

Class participation is somewhat subjective, but I will do my best to be as fair as possible. I will share your overall class participation points with you with each graded exam.

Exams

There will be three exams in the course, including the final. The final exam will be cumulative.

All exams will be on paper and closed-book. Exam 3 will be on the last day of class.

The finals week will be used for project presentations.

What is Data Mining?

“Data Mining” is a term from the 1990s, back when it was an exciting and popular new field. Around 2010, people instead started to speak of “big data”. Today, the popular term is “data science”. There are some who even regard data mining as synonymous with machine learning. There is no question that some data mining appropriately uses algorithms from machine learning. However, during all this time, the concept remained the same: use the most powerful hardware, the most powerful programming systems, and the most efficient algorithms to solve problems in science, commerce, healthcare, government, the humanities, and many other fields of human endeavor.

From the Venn Diagram, the course content is going to cover ✅ Hacking Skills and ✅ Math & Statistics in detail but not ☐ Substantive Expertise. For that missing piece, I strongly encourage you to bring in knowledge from your GERs and other Non-CS department courses into this class and the term project in particular. Nothing would make me happier than to see projects that combines CS with your other interests.

Expect lots of Programming and lots of Math!

“But wait, I am not a Math Person!” you say!

There is no such thing as a “Math Person”. I do recognize, however, that Math Anxiety is a real thing and is very common. It is a feeling of fear based on a belief that one is not good at math or that math is inherently difficult.

Please use this course as an opportunity to overcome your Math anxiety!

In this course, the code you write will be mostly math. Most modern “AI” is just that: math, in code.

This presents a unique opportunity for you to overcome your Math anxiety. You will be able to see the math in action, be able to visualize the results and have a conversation with it.

Trust me, there is a tremendous amount of beauty and joy to be found in mathematics. And if beauty and joy aren’t really your thing, then let me also assure you there is a lot of money to be made these days by being good at coding math. Either way, the rewards are well worth the effort!