In different sources, normal salary of Code works ~ £ 47.5k in UK, higher ~
Therefore, codes are the most important skill that will get you more money, don't say that it is really fun.
I have been codes of work now 4 years, I work as a data scientist and the machine study engineering and this post, I will explain how to learn and if I should do it again.
My journey
I still remember the time I wrote my first code.
It was 9 every morning on the first day of physics undergrad, and we were on a computer lab.
Professor explained that combinations are an integral part of modern physics as it allows us to run the intense running of everything in the types of genocals.
Sounded amazing.
And the way we started the process was in the study books for Fortran.
Yes, you have heard that privilege.
My first language language Bracedirectly fortran 90.
I learned that I made logs before. I definitely be a burning object in this case.
At that time the first lab lab, I remember to write “Hi World” as a normal cow and thinking, “Big Woop.”
This is how you write as “Hello World” in Formran if you are interested.
program hello
print *, 'Hello World!'
end program helloIn fact, I really struggled on the Code in Formran and didn't do that well in the test we had, which put me codes.
I still have old coding projects in Fortran in my gitumbub.
When I look back, the logging curve to enter the codes is already firm, but it is really integrated, and finally, it will just click.
I never knew this at that time and I diligently avoided edition modules in my Physics facilities, which I regret viewing as my progress would be early in the early.
In my third year, I had to do research as part of my master. The company I chosen is working / through the language of the clicks called Lawview to run and treat its exams.
The Labview is based on an object called “G” and taught me to think about the different systems than script-based.
However, I never used it since again maybe I will never date, but it was nice to read at that time.
I have enjoyed a year of research, but the speed where research is going, at least in physics, slow. Nothing is like “Heyday” from the beginning of the 20th century recognized.
One day after work video was recommended to me on YouTube homepage.
For those of you who don't know, this was a book about Ai Alphago Kadeepmind hit the best player in the world. Most people thought AI would never be good in walking.
From the video, I began to understand how AI worked and learns about neural networks, the strengthening of learning, and deep reading.
I found everything interesting, like a physics study at the beginning of the 20th century.
Finally, this is where I first started to study the science and the study of the machine, where I wanted to teach me Python and Sql.
This is where you are called “falling in love” with code.
I saw its real strength by solving problems, but it was the case that I had motivated reason for learning. I was learning to join the work I wanted to have, who led me.
Then I am the data scientist for three years and now I am an engineering machine. At this time, I worked greatly with Python and Sql.
Until the past few months, those were only languages in planning programs. I have learned other tools, such as Bash / Z-Shell, AW, Docker, Data bricks, snow, etc. But not other languages ”suitable”.
In my spare time, I slowly traveled with a few ago, but I forgot about everything now. I have basic documents in my gitub if you are interested.
However, in my new role I started and started in the past few months, I would use the rust and go, looking forward to learning.
If you are interested in all my journey to become a data scientist and the machine learning engineer, you can read below:
Choose a language
I always recommend starting in one language.
According to Tesgorilla, there are more than 8,000 tongues, so how do you prefer one?
Yes, I can argue that many of these are unemployed in many activities and may be constructed as pet projects or niche charges.
You can choose your first language based on popular preferences. The abundant stack survey is full of positive detail on this. The most popular languages is JavaScript, Python, SQL, and Java.
However, the way I recommend that you choose your first language should be based on what you want to do or work as.
- Front-END Web –JavaScript, HTML, CSS
- Web-ENDS Web –Java, C #, Python, PHP or Go
- IOS / Macos Apps– Prompt
- Android Apps– Kotlin or Java
- Games Games– C ++ or C
- Embedded programs– C or C ++
- Scientific / study-study machine / no– Python and SQL
As I wanted to work in ai / ML area, I focused on my power especially in Python and others in SQL. It was probably 90% of / 10% SPLIT as a SQL is small and easy to read.
To this day, I only know the Python and SQL in the standard “professional”, but that's okay, good, all the machine learning society.
This shows that you do not need to know many languages; I was very advanced in my work, only knowing two deep down. Of course, it would be different from the Sector, but the main point was still stopped.
Therefore, select the field you want to access and select the most demanding and appropriate language in that field.
Learn the empty minimum
The biggest mistake I see the beginners do it “in hell of course.”
This is where you take the course of the course but never be released yourself.
I recommend taking a higher number of two lessons in language – honestly any course of Intro will – and start building immediately.
And I've been real, build your projects and get the struggle because this is where the reading is done.
You will not know how to write tasks until you are self-centered, and you will actually not understand the logs until you use yourself.
Therefore, read the minimum and start immediately to try; I promise to do at least one study curve.
You have probably heard this very advice, but it is actually easy.
I always say many things in life are simple but difficult to do, especially in the programs.
Avoid Styles
If I say to avoid tendency, I don't mean I don't focus on well-efficient or wanted places in the market.
What I say is that when choosing a specific language or professional, they are attached to.
Longs of organizing allergies and the same concepts, so when reading one, you promote your replacement.
But you have to focus on one language for at least a few months.
Do not improve “shiny Object syndrome” and cheeses the latest technology; It is a game to lose badly wrong.
There has been a lot of “disturbing” technology, such as Blockchain, Web3, AI, the list progresses.
Instead, focus on the placements:
- Data Types
- The design patterns
- Tested programs in things
- Data Buildings and Algorithms
- Troubleshooting skills
These articles exceed each organizational languages and are the best to enable the latest JavaScript framework!
It is best to have a solid understanding of one place than trying to read everything. It is not that this is very controlled, but it's your long-term work.
As I said earlier, I have improved well in my work with Knowledge Python and SQL, as I learned the required field technology and I am not distracted.
I cannot emphasize how much you will have to work in your work when writing you openly.
Check your reading
I don't know why many people don't do this. Sharing what I have learned online has been a large gym machine.
According to the Word to make your code in Gitub is enough, but I really recommend sending to LinkedIn or Ix, you must create a blog post to help your understanding and show information to employers.
When I communicate with candidates, if there is some type of internet that displays their readings, soon the tick is in my box and more edge than others applicants.
It shows enthusiasm and love, it can mean that increase your above Serendipity area.
I know that many people are afraid to do this, but you have a picture of the picture. Wikipedia describes this as:
The outcome of the Spotlight is a mental part of people where people believe it are more recognized than they really are.
No one cares about literally when you send online or think about you as 1% as you think.
So, start sending.
What about AI?
I can spend many hours I discuss why AI is not a quick risk for anyone who wants to work in the codes.
You must accept AI as part of your Toolkit, but only where it will go, and it will definitely take up to 5 years.
Unless AGI Breatrough suddenly appeared in the next ten years, so much.
I Doubt Your AGI Answer is the falling work of crossing, which is used for most of llms these days.
It is shown for time and time and that these types of AI are lacking strong mathematical skills, one of the most basic skills in being a good coder.
Even the one called “Software Engineer Killer” devin is incorrect as the creators initially sold.
Many companies try to improve their planting in hyping Ai, and their effects often extremely extremely extremely extremely extremely extremely extremely extremely extremely extremely extremely overreact to the interruption test.
When I make a website, Chatgpt even improved the simple HTML and CSS, which you can oppose its bread and butter!
Overall, don't worry about AI if you want to work as a code; There is a lot, big fish in the Fry before crossing the bridge!
Netcode made a good video explaining that AI current cannot replace the system editors.
One thing!
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