7 Ways to Make $10,000+ a Month with Python

Summary

In 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

00:00

💼 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.

05:01

🔍 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.

10:02

🛡️ 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.

Keywords

💡Python

Python is a high-level, interpreted programming language known for its readability and efficiency. In the context of the video, it is the primary skill discussed, with the presenter highlighting various career paths available to those proficient in Python. The video aims to show that Python skills can be applied in multiple in-demand jobs, potentially earning over $100,000 a year.

💡Backend Developer

A backend developer is a software engineer who works on the server-side of applications, creating and maintaining the infrastructure that supports the frontend. In the video, the role is associated with building websites and using Python frameworks like Flask and Django. The presenter explains that backend developers are crucial for the functionality of websites and are in high demand.

💡Data Analyst

A data analyst is a professional who collects, processes, and interprets data to help businesses make informed decisions. The video describes the data analyst's role as using Python tools to extract insights from data, such as customer purchasing patterns or viewing habits, which can then be used to improve services or products.

💡Data Science

Data science involves using scientific methods, algorithms, and systems to extract knowledge and insights from structured and unstructured data. The video distinguishes data analysis from data science by emphasizing the predictive element of the latter, where data is used to forecast future trends or behaviors, often requiring more rigorous statistical methods.

💡Machine Learning

Machine learning is a subset of artificial intelligence that enables computers to learn and improve from experience without being explicitly programmed. In the video, it is presented as the next level beyond data science, where algorithms automatically learn from data to make predictions or decisions, such as recommending videos on YouTube.

💡Quality Assurance Engineer

A quality assurance engineer is responsible for designing, developing, and maintaining tests to ensure software quality and identify potential technical problems. The video script includes a job posting example that illustrates the role's focus on both automated and manual testing to prevent software bugs and improve development processes.

💡AI Engineering

AI engineering refers to the development and implementation of artificial intelligence systems. The video discusses AI engineering as an in-demand field with a high barrier to entry, often requiring skills in data science and machine learning. It is presented as a future-proof skill set that can lead to high-paying jobs.

💡Automation Engineer

An automation engineer specializes in creating automated systems to streamline processes and reduce manual labor. The video describes how automation engineers work to improve company workflows and can be highly appreciated for their contributions, such as automating repetitive tasks to increase efficiency.

💡Network Security Engineer

A network security engineer is responsible for protecting an organization's data and network infrastructure from cyber threats. The video highlights the increasing relevance of this role due to the rise in cyber attacks and the need for companies to safeguard sensitive information. Skills in network security, cryptography, and firewalls are essential for this role.

💡Specialization

Specialization in the video refers to the idea of becoming an expert in a specific area rather than having a broad, general knowledge. The presenter advises viewers to focus on one area of interest after learning Python, as being highly skilled in a particular domain can lead to higher earning potential and job security.

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