Course Review: Udacity Data Structures and algorithms

Tracyrenee
10 min readDec 14, 2021

Udacity’s course, Data Structures and Algorithms, is intended for those individuals who are intending to go on interviews in the field of data science. While I don’t think I am going to be on any interviews, namely because of my age and health, I decided it would be a good idea to take the course nevertheless to see if the content will help me in the projects I am currently involved in.

Below is a review of the course and my thoughts about the content:-

Lesson 1: Introduction and Efficiency

The purpose of data structures and algorithms is to invent efficient solutions to unsolved problems using algorithms and data structures.

An algorithm is a program that solves a problem. It is a series of steps to solve a problem. It is a high level description of a trick for solving a problem.

Data types:-

  1. String = “ “
  2. List = [ ]
  3. Tuple = ( )
  4. Dictionary = {}
  5. Boolean = True or False
  6. Number = 1 or 1.0
  7. Variable with zero data = None

Types of loops

  1. For
  2. While

Efficiency, or complexity, shows how well the programmer is using his computer’s resources to get things done.

Writing efficient code can come with a tradeoff between time efficiency and space efficiency.

Big O notation is one of the most fundamental tools for computer scientists to analyze the cost of an algorithm.

Lesson 2: List based collections

Collections don’t have a specific order. They do not have to be a specific type of object.There are many data structures that are extensions of collections.

Lists have all the properties of a collection.

Arrays are perhaps the most common implementation of lists. An array is a list with a few added rules. Each array has an index, which starts at zero.

A linked list is an extension of a list, but is not an array. A linked list is characterised by its links. Each element has some notion of what the…

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Tracyrenee

I have close to five decades experience in the world of work, being in fast food, the military, business, non-profits, and the healthcare sector.