7 Ways to Make $10,000+ a Month with Python
Summary
TLDRIn this video, software engineer Toas outlines seven high-demand job options for Python developers in 2024, each potentially earning over $100,000 annually. These roles include backend developer, data analyst, data scientist, quality assurance engineer, AI engineer, automation engineer, and network security engineer. He emphasizes that Python skills alone aren't enough; additional knowledge in specific areas is crucial. Toas also shares resources for learning these skills and highlights the importance of specializing in one field for greater success in the job market.
Takeaways
- 😀 Learning Python can open up various job opportunities, particularly for those interested in tech-related careers.
- 👨💻 One of the most in-demand job roles for Python developers is a backend developer, focusing on creating the server-side of websites.
- 🌐 Backend development in Python often involves learning web frameworks like Flask and Django to build and manage website features.
- 📊 Data analyst is another lucrative role where Python skills are used for data collection, analysis, and visualization to inform business decisions.
- 🔮 Data science and machine learning are advanced fields related to data analysis, requiring more rigorous statistical methods and predictive modeling.
- 🔍 Quality assurance engineers use Python for automated and manual testing to ensure software reliability and identify technical issues before release.
- 🤖 AI engineering is a high-demand field where Python skills are applied to develop intelligent systems, often overlapping with data science and machine learning.
- 🔄 Automation engineers use Python to create scripts that automate repetitive tasks, improving efficiency in both personal and company workflows.
- 🛡️ Network security engineers are responsible for protecting a company's data and networks, learning about security architecture, firewalls, and cryptography.
- 📚 To excel in any of these Python-related roles, it's essential to gain specialized knowledge beyond just Python, such as web frameworks for backend development or data analysis tools.
- 💰 Specialization in a specific area of Python development is more valuable than being a generalist, as it allows for higher earning potential and career advancement.
Q & A
What are the seven job options discussed in the video for someone with Python skills?
-The seven job options discussed are backend developer, data analyst, data scientist, machine learning engineer, quality assurance engineer, AI engineer, automation engineer, and network security engineer.
What is the primary role of a backend developer?
-A backend developer is responsible for building the server-side of web applications, which includes the logic, database interactions, and the overall structure that powers the frontend.
Which two Python web frameworks are mentioned in the video as being popular for backend development?
-The two popular Python web frameworks mentioned are Flask and Django.
What is the difference between a data analyst and a data scientist according to the video?
-A data analyst collects and analyzes data to draw insights and make reports, while a data scientist uses statistical methods to make predictions about the future based on past data.
What skills are essential for someone looking to become a quality assurance engineer?
-To become a quality assurance engineer, one should learn automated testing using libraries like Selenium, performance testing, and understanding of software bugs and development processes.
What does the video suggest about the demand and future-proof nature of AI engineering roles?
-The video suggests that AI engineering roles are in high demand and are future-proof, as they involve building AI systems that are increasingly relevant in the tech industry.
What is the primary focus of an automation engineer?
-An automation engineer focuses on creating automations to improve company workflows and automate tasks that would otherwise require manual work.
What are the key skills a network security engineer should learn according to the video?
-A network security engineer should learn about network security architecture, firewalls, virtual private networks, and cryptography.
What is the caveat mentioned in the video regarding the job options for Python developers?
-The caveat is that having Python skills alone is not enough for any of the job options; additional skills specific to each job role are required.
What advice does the video give about specializing in one area rather than being a jack of all trades?
-The video advises that it's better to specialize in one area and become really good at it, as the most money is made by those who are experts in a very specific field.
What is the recommended first step for someone who wants to learn Python and explore these job options?
-The recommended first step is to learn Python fundamentals and then explore the different job options to find what interests them the most, followed by diving deep into that specific area to acquire the necessary skills.
Outlines
💼 Python Developer Job Opportunities
This paragraph introduces the video's focus on the various job options available for Python developers in 2024, with the potential to earn over $100,000 a year. The speaker, Toas, a software engineer, shares his personal experience with Python and its impact on his life. He outlines the first job option, backend developer, explaining the role in building websites and the importance of web frameworks like Flask and Django. Toas also mentions his Python Developer Bootcamp program, offering a discount for viewers interested in learning Python web development.
🔍 Exploring Data-Centric Careers with Python
The second paragraph delves into data-related jobs such as data analyst, data scientist, and machine learning engineer. It describes the responsibilities of a data analyst, including data collection, analysis, and visualization to extract insights for business decisions. The role of a data scientist is distinguished by its focus on making future predictions using statistical methods. The paragraph also touches on the high demand and lucrative salaries for these roles, noting the higher barriers to entry due to the need for technical experience or relevant academic backgrounds.
🛡️ Diverse Python Roles in Quality Assurance and Security
This paragraph discusses the role of a quality assurance engineer, responsible for testing software to ensure it is free of bugs and functions correctly under various conditions. It also introduces the role of an AI engineer, highlighting the overlap with data science and the importance of AI in the tech industry. The paragraph concludes with the role of an automation engineer, emphasizing the value of automating tasks to improve workflows, and a network security engineer, who protects a company's data from cyber threats. The speaker emphasizes the importance of learning specific skills beyond Python for these roles.
🚀 Advancing as a Python Developer
The final paragraph serves as a conclusion, reminding viewers that Python skills alone are not sufficient to secure a job in any of the discussed fields. It stresses the importance of becoming a specialist in one area rather than being a generalist. The speaker encourages viewers to research the different job options, identify their interests, and then focus on acquiring the necessary skills. He also recommends a video that outlines the step-by-step process to become an advanced Python developer, positioning oneself for a high-paying job.
Mindmap
Keywords
💡Python
💡Backend Developer
💡Data Analyst
💡Data Science
💡Machine Learning
💡Quality Assurance Engineer
💡AI Engineering
💡Automation Engineer
💡Network Security Engineer
💡Specialization
Highlights
Learning Python opens up various high-paying job options in 2024.
Backend developer is a key role, focusing on building and maintaining website backends using frameworks like Flask and Django.
Data analysts use Python tools to gather, analyze, and visualize data, helping companies make data-driven decisions.
Data scientists take data analysis further by making predictions and using statistical methods to forecast future trends.
Machine learning engineers develop algorithms that enable systems to learn and make recommendations based on data.
Quality assurance engineers ensure software quality by developing automated tests and performing manual testing to identify and fix bugs.
AI engineers work on developing artificial intelligence technologies, a highly in-demand and future-proof skill set.
Automation engineers create scripts to automate repetitive tasks, improving efficiency within companies.
Network security engineers focus on protecting company data from cyber threats, a critical and growing field.
Python skills alone are not enough; additional specialized skills are necessary for these job roles.
Backend developers need to understand web development basics and frameworks like Flask and Django.
Data analysts must learn web scraping, data gathering methods, and visualization tools.
Data scientists require knowledge of statistical methods and data prediction techniques.
Quality assurance engineers need skills in automated testing libraries and performance testing.
AI engineers benefit from free online courses, such as Harvard's Introduction to AI.
Automation engineering skills are valuable for improving workflows and saving time in any development role.
Network security engineers need to understand security architecture, firewalls, VPNs, and cryptography.
Specializing in one specific skill set is more beneficial for career success than being a generalist.
Transcripts
so you've learned python or you're
considering learning python but you
don't know what can you actually do with
python skills specifically what job
options do you actually have with python
skills in 2024 well in this video I'm
going to give you seven of the most
popular and most in demand job options
that you can do as a python developer
all of which have the potential to earn
you more than
$100,000 a year but there is a big
caveat to all of these options that I'm
going to get back to later but first if
you're new here my name is toas I'm a
software engineer for around 2 and a
half years now from the start my main
programming language has been python
learning the code and especially
learning python completely changed my
life in more ways than one and on this
channel I want to help you learn the
code so that you can perhaps change
yours too with that said let's get
started with the first job option and
that is going to be a backend developer
so here we're essentially talking about
building websites for the web so any
website you're looking at like the
website of YouTube right now is a
website that has a front end and a back
so front end is going to be the visual
part of the website that you see on your
screen like the video player like the
suggested videos on the right the things
you can click on like the like button
for example by the way if you want to
test it out how it works you can just
click on the like button anyway but on
top of the front end every website also
has what's called a backend what the
back end will contain is for example the
YouTube algorithm that for some reason
recommended this video to you and the
back end can be written in all kinds of
different programming languages and
python is actually very popular language
to be used in the back endend of the web
specifically the way it works is that
you have these web Frameworks that
essentially contain all the building
blocks that you need to build the back
end of a website with all kinds of
features that you can apply to it like
connecting it to a database security
features things like this and for python
the two most popular Frameworks they use
for this are something called flask and
Jango so if after learning python you
want to become a backend developer your
first step is going to be to learn the
basics of the web what the front end is
what the back end is essentially what I
just explained but in more detail and
then after that to learn one of these
Frameworks either Jango or flask I'm
going to leave resources down below to
this and to all of these other paths so
if you want to get started with learning
one of these paths right now you can do
that straight away and there's many
other things to learn as well by the way
if you're looking for one full program
that is going to teach you not only
python web development but also the
foundations of python from first
principle so you can become a python web
developer in as little as 6 months then
I have my full program python develop by
boot camp down below is my Flagship
program more than 500 students the ones
of you that have purchased it have
absolutely loved it if you are
interested you can use the code python
down below to get a discount on it as a
thank you for watching this particular
video with that let's move on to the
next part which is going to be a data
analyst so what a data analyst is is a
programmer or a professional who will
work for some company and collect a
bunch of data about the service let's
say you work for Amazon you're going to
be collecting data about the purchasing
patterns of your customers about the
watch history of your customers if you
work for something like Netflix or
YouTube You're Going to essentially look
at a bunch of data and use specific
python tools to extract and like learn
stuff from that data that is essentially
what data analysis is going to be and to
do that you're going to have to learn
certain things you're going to learn
about web scraping you're going to learn
about different ways of gathering this
data from all kinds of sources and then
you're going to learn about different
tools or different python libraries to
actually create visualizations and other
of insight from this data they can then
use and present to your superiors to
essentially say like okay based on the
watch history of our users or whatever
we learned that these things are popular
and these kinds of uses like these kinds
of movies and things like this and from
that you can improve your service this
is an extremely extremely important task
in any business which is why data
analysts are paid extremely extremely
well from that we also get into data
science and machine learning so the
difference between data analysis and
data science can be a murky because some
companies might call a role a data
scientist where that exact same role at
a different company might be called a
data analyst but broadly data science is
like data analysis except more
scientific more like rigorous in a way
so rather than just like making reports
and visualizations and drawing insights
from a data you're essentially using
data to make predictions about the
future you're using all kinds of
statistical methods to essentially look
at past data and make predictions about
the future a data analyst will look at
current data and using that explain what
happened in the past for example based
on this data these kinds of users
usually watch these kinds of movies
whereas a data scientist will look at
current data to make predictions about
the future for example a data scientist
at YouTube might look at your watch
history and based on that make
predictions about what kinds of videos
you want to watch in the future so that
they can then recommend those videos to
you on your YouTube homepage and the
next level beyond that is going to be
machine learning you're actually
creating machine learning algorithms
that take a bunch of data and then based
on that data they automatically learn
things about you or what you like what
you're interested in and then
automatically recommend that to you on
YouTube the pro of this is that for
these kinds of roles where you're going
data science machine learning the pay is
going to be extremely extremely high but
the barrier to entry to these kinds of
roles is also going to be much higher in
fact it can be quite difficult to get
into one of these roles if you don't
have relevant technical experience or a
degree in either mathematics statistics
or computer science it's not that cannot
be done but usually what will happen is
that you will start off as something
like a data analyst and then you will
essentially graduate to be a data
scientist or things like this the next
scen is going to be a quality assurance
engineer to understand what these guys
do let's just look at a real job posting
of a quality assurance engineer to
understand this here we have a job
posting on LinkedIn quality assurance
engineer quality insurance Engineers
design develop and maintain automated
testing for neon one which is the
company in this case products the over
see the software quality control
processes for web applications blah blah
blah blah blah using both automated
testing and manual testing to identify
possible technical problems in a staging
environment creating reports regarding
software bugs recommending changes to
development process prior to release so
essentially what this means to
oversimplify this in general we have bad
software and we have good software and
the difference between bad software and
good software is that good software
doesn't have bugs it's been properly
tested so it's actually going to work in
all all kinds of edge cases when a bunch
of real users useing and things like
this and usually if you're just a
software engineer whose purpose is to
develop these applications from scratch
you don't have the time to test every
possible case like if you use your
software yourself it might work
perfectly but when some other user gets
your application and uses it in a
completely different way it might
completely break because you haven't
considered all of these cases it's the
job of quality insurance Engineers to
make sure that you have quality software
that works that doesn't break that's
been properly tested to account for all
these possible use cases and things like
this so what you're going to be learning
is things like automated testing
libraries like selenium what you're also
going to be doing is what's called
performance testing so you might have
some software that works well when it's
being used by a small number of users
but it might break when it's being used
by 5,000 or 5 million users so there are
all kinds of libraries in Python that
allow you to test these kinds of
scenarios automatically without actually
having to give your software to millions
of users next we have ai engineering so
obviously unless you've been living
under a complete rock you will know that
AI is a really big thing nowadays in the
tech industry and why being an AI
engineer is particularly interesting to
you is that obviously a lot of people
are afraid that AI is going to take our
jobs and things like this but if you're
an AI engineer you can actually be one
of the people taking the jobs rather
than one of the people whose job is
being taken if that makes sense now this
is going to overlap quite a lot with
data science and machine learning one of
the categories that we talked about
before you could even say that this is
part of the same category because a lot
of the time an AI job will involve a lot
of data science and vice versa but I
decided to include it as a separate job
here anyway now if you have the skills
of building AI then you're going to have
probably the most in demand and like
most future proof skill set you can
possibly have in this day and age if you
want to get started with the AI this a
great course it's a completely free
course by Harvard University that you
can do online it's called like
introduction to AI or something like
that absolutely fascinating and
interesting course I haven't done much
AI in my life but I recommend everyone
does this you'll sort of get an idea of
how AI like different types of AI
actually work behind the scenes so I
highly recommend you do that with that
let's move on to the next one and that
is going to be an automation engineer so
on this channel we talk a lot about
automation projects I have a ton of
videos about python automation projects
that you can do obviously to automate
real things like boring things in your
own workflow and in your own life if you
were to work as an automation engineer
it's essentially the same idea except
you're creating automations for
companies to improve company workflows
to automate things that people would
have to do manual work for otherwise for
example I remember at my software
engineer job that I was working at even
though I was not an automation engineer
or anything like that I was able to
create a python script that actually
automated some tasks that we were having
to do like hundreds of times manually in
the team and when I did that then
obviously the team was extremely
extremely appreciative of that so I
think automation is the kind of skill
that even if you're not particularly
working as an automation engineer it's
going to be an extremely extremely
useful just a skill to have as a
developer because he can help you in
your own life and in your company and
can really buy a lot of Goodwill from
your team if you're able to use
automation to help your team last but
not least we have a network security
engineer this is another thing that
these days is becoming more and more and
more relevant and it's a really great
option specifically because I don't
think there's as many people who are
doing this as for example web
development or data analysis or some of
the other things we talk about because
it's not as like sexy it's not as cool
to be taking care of the security of
your computer's Network or something
like that but again it's something that
almost every company is going to need
because every company is going to have
some sort of classified data in their
private Network or things like this and
there's a lot of cyber attacks and
things like this that can happen in this
day and age so protecting the data of
your company is extremely extremely
crucial for example right now I'm
staying at a hotel and I'm sure that
they have a lot of data in their
internal servers and things like this
that they don't want to leak like
sensitive data about their guests like
their systems their revenue things like
this now here again you're going to be
learning a lot of specific skills around
network security around the security
architecture of all kinds of computer
networks about firewalls about virtual
private networks you might learn about
cryptography now this brings us to the
one big caveat about all of these seven
jobs that we've gone through here and
you might have noticed here is that a
common thing here is is that to get into
any of these jobs is not enough to just
have python skills for all of these
you're going to need some skills on top
of learning python for web development
you're going to need to learn web
Frameworks for data analysis you're
going to need to learn data analysis
tools for network security Engineers
you're going to need to learn a bunch of
things about Network Concepts about
cryptography all these kinds of things
and this is a really great lesson for
anyone wanting to become a developer
It's never enough just to learn a
programming language and think like oh
now I'm going to become a developer it's
good to just Learn Python first and then
explore all these different options so
I'm going to leave bunch of resources
down below for all of these different
jobs and what I want you to do to go and
research all of them to think about what
actually interests you and then Deep
dive into that one area it's not useful
to be a jack of all trade where you know
a bit about everything it's much better
to be a specialist in one thing because
in this economy the most money is made
by those people who are really really
good at one very very specific thing so
keep that in mind with that said if
you're looking to Learn Python and you
hav haven't even started yet and you're
wondering what is the actual
step-by-step process to go from beginner
to intermediate to advance I recommend
you watch this video right here because
that video is going to help you to
become an advanced python developer so
that after that you can go and learn the
specific skills for any of these
specific parts and become a real python
developer and get a 100K job so go watch
that video next and I'll see you in the
next one
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