What to expect in a Computer Science course

About this Video

Considered getting into computer science but not sure what you’re getting into? Not sure if you know enough, or if it’s the right course for you? In this video, I answer some common concerns!

Key Learning Points

  • What does a computer science student do? (2:27)
  • Is there a lot of math in computer science? (4:05)
  • Do I need a programming / computing background? (6:13)
  • What can I do to cope better if I don’t have any background? (7:40)
  • I dislike / fear / am bad at programming. Would this be a problem? (9:01)
  • Why are topics like graphics and media part of Computer Science? (10:33)
  • Why must I implement algorithm X when it already exists out there? (11:18)
  • How do I do well in Computer Science? (12:19)

Sampling, Aliasing & Nyquist Theorem

About this Video

The world of computers is digital in nature, but the quantities around us are analog! We’ll have to perform analog-to-digital conversion to effectively store, manipulate, and transmit analog information.

Sampling – The act of taking readings of analog information at intervals, is the strategy in which this can be achieved, but sampling comes with its own set of considerations. For example, how often should we sample?

This sample rate should be well chosen to prevent aliasing – Getting poor results from sampling too infrequently. Thankfully, we can make use of the Nyquist-Shannon Sampling Theorem, which tells us what sample rate to use to prevent aliasing from happening!

Key Learning Points

  • What is Sampling and the meaning of Sampling Rate
  • What is Aliasing
  • The Nyquist-Shannon Sampling Theorem
  • Application of the Nyquist-Shannon Sampling Theorem


Use the NERDfirst Nyquist Theorem Simulator to try it for yourself! See how a sampled signal is reconstructed as you adjust the sampling rate and signal frequency.