Algorithms and Data Structures Tutorial - Full Course for
Beginners
freeCodeCamp.org
Introduction to Algorithms
This is a full-length course from Treehouse. We, at Free Code
Camp, are longtime fans of their learning platform. They were
kind enough to let our nonprofit make this course freely
available on our YouTube channel. If you like this course,
Treehouse has a lot more courses like this one. The link is in
the description along with time codes to the different sections
in this course.
Hi, my name is Passan. I'm an instructor here at Treehouse,
and welcome to Introduction to Algorithms. Whether you are a
high school or college student, a developer in the industry, or
someone who is learning to code, you have undoubtedly run
into the term algorithm. For many people, this word is kind of
scary. It represents this body of knowledge that seems just out
of reach. Only people with computer science degrees know
about algorithms. Now, to others, this brings up feelings of
imposter syndrome. You might already know how to code, but
you're not a real developer because you don't know anything
about algorithms.
In this course, our goal is to dispel all those feelings and get
you comfortable with the basics of algorithms. Like any other
subject, I like to start my courses with what the course is and is
not. In this course, we're going to cover the very basic set of
knowledge that you need as a foundation for learning about
algorithms. This course is less about specific algorithms and
more about the tools you will need to evaluate algorithms,
understand how they perform, compare them to each other,
and make a statement about the utility of an algorithm in a
given context. Now, don't worry, none of this will be
theoretical, and we will learn these concepts by using well-
known algorithms. In this course, we will also be writing code,
so I do expect you to have some programming experience if
you intend to continue with this topic. If you're a JavaScript
developer or a student who's learning JavaScript, for example,
chances are good that you'll still be able to understand the
code we write later. I'll be sure to provide links along the way if
you need anything to follow up on.
, Let's start with something simple. What is an algorithm? An
algorithm is a set of steps or instructions for completing a task.
In computer science, the term algorithm more specifically
means the set of steps a program takes to finish a task. If
you've written code before, any code really, generally
speaking, you have written an algorithm.
Given that much of the code we write can be considered an
algorithm, what do people mean when they say you should
know about algorithms? Now consider this. Let's say I'm a
teacher in a classroom, and I tell everyone I have an
assignment for them. On their desks, they have a picture of a
maze, and their task is to come up with a way to find the
quickest way out of the maze. Everyone does their thing and
comes up with a solution. Every single one of these solutions is
a viable solution and is a valid example of an algorithm, the
steps one needs to take to get out of the maze. But from being
in classrooms or any group of any sort, you know that some
people will have better ideas than others. We all have a diverse
array of skill sets. Over time, our class picks the best of these
solutions, and any time we want to solve a maze, we go with
one of these solutions. This is what the field of algorithms is
about.
There are many problems in computer science, but some of
them are pretty common regardless of what project you're
working on. Different people have come up with different
solutions to these common problems, and over time, the field
of computer science has identified several that do the job well
for a given task. When we talk of algorithms, we're referring to
two points. We're primarily saying there's an established body
of knowledge on how to solve particular problems well, and it's
important to know what the solutions are. If you're unaware
that a solution exists, you might try to come up with one
yourself, and there's a likelihood that your solution won't be as
good or efficient (whatever that means) compared to those
that have been thoroughly reviewed. But there's a second
component to it as well. Part of understanding algorithms is not
just knowing that an algorithm exists, but understanding when
to apply it. Understanding when to apply an algorithm requires
properly understanding the problem at hand, and this arguably
is the most important part of learning about algorithms and
data structures. As you progress through this content, you
should be able to look at a problem and break it down into
Beginners
freeCodeCamp.org
Introduction to Algorithms
This is a full-length course from Treehouse. We, at Free Code
Camp, are longtime fans of their learning platform. They were
kind enough to let our nonprofit make this course freely
available on our YouTube channel. If you like this course,
Treehouse has a lot more courses like this one. The link is in
the description along with time codes to the different sections
in this course.
Hi, my name is Passan. I'm an instructor here at Treehouse,
and welcome to Introduction to Algorithms. Whether you are a
high school or college student, a developer in the industry, or
someone who is learning to code, you have undoubtedly run
into the term algorithm. For many people, this word is kind of
scary. It represents this body of knowledge that seems just out
of reach. Only people with computer science degrees know
about algorithms. Now, to others, this brings up feelings of
imposter syndrome. You might already know how to code, but
you're not a real developer because you don't know anything
about algorithms.
In this course, our goal is to dispel all those feelings and get
you comfortable with the basics of algorithms. Like any other
subject, I like to start my courses with what the course is and is
not. In this course, we're going to cover the very basic set of
knowledge that you need as a foundation for learning about
algorithms. This course is less about specific algorithms and
more about the tools you will need to evaluate algorithms,
understand how they perform, compare them to each other,
and make a statement about the utility of an algorithm in a
given context. Now, don't worry, none of this will be
theoretical, and we will learn these concepts by using well-
known algorithms. In this course, we will also be writing code,
so I do expect you to have some programming experience if
you intend to continue with this topic. If you're a JavaScript
developer or a student who's learning JavaScript, for example,
chances are good that you'll still be able to understand the
code we write later. I'll be sure to provide links along the way if
you need anything to follow up on.
, Let's start with something simple. What is an algorithm? An
algorithm is a set of steps or instructions for completing a task.
In computer science, the term algorithm more specifically
means the set of steps a program takes to finish a task. If
you've written code before, any code really, generally
speaking, you have written an algorithm.
Given that much of the code we write can be considered an
algorithm, what do people mean when they say you should
know about algorithms? Now consider this. Let's say I'm a
teacher in a classroom, and I tell everyone I have an
assignment for them. On their desks, they have a picture of a
maze, and their task is to come up with a way to find the
quickest way out of the maze. Everyone does their thing and
comes up with a solution. Every single one of these solutions is
a viable solution and is a valid example of an algorithm, the
steps one needs to take to get out of the maze. But from being
in classrooms or any group of any sort, you know that some
people will have better ideas than others. We all have a diverse
array of skill sets. Over time, our class picks the best of these
solutions, and any time we want to solve a maze, we go with
one of these solutions. This is what the field of algorithms is
about.
There are many problems in computer science, but some of
them are pretty common regardless of what project you're
working on. Different people have come up with different
solutions to these common problems, and over time, the field
of computer science has identified several that do the job well
for a given task. When we talk of algorithms, we're referring to
two points. We're primarily saying there's an established body
of knowledge on how to solve particular problems well, and it's
important to know what the solutions are. If you're unaware
that a solution exists, you might try to come up with one
yourself, and there's a likelihood that your solution won't be as
good or efficient (whatever that means) compared to those
that have been thoroughly reviewed. But there's a second
component to it as well. Part of understanding algorithms is not
just knowing that an algorithm exists, but understanding when
to apply it. Understanding when to apply an algorithm requires
properly understanding the problem at hand, and this arguably
is the most important part of learning about algorithms and
data structures. As you progress through this content, you
should be able to look at a problem and break it down into
