Python

And provide GitHub link

Try secure mail With encryption (use symmetric key and assymetric key encryption) Authentication/ digital signatures and digital certificates using asymmetric key encryption and hashing algorithms You will have lot to do Front end Back end Security Secure mail features implementations General mail features like ( Send, reply , page views , favourites marking, address book ) It will be a gigantic project

I want to learn python for data science. I've downloaded several videos tutorials but I'm still lagging behind. Is there specific methods I need to apply please. I need someone guide 😔.

Check data science syllabus topics Find the best possible set of videos you can find and watch those Data science with python is a huge topic and you will need several months to learn ( may be even years) It is not something you can learn in few days You need a long-term plan you can find take time and find a plan Or you can develop a plan from the syllabus

Thank you. Can you recommend some for me.

There Is the doc online

I have the mindset understanding that python take times to learn. I have been on this journey since last two years. Although not consistency

I personally worked o database engineering like data modelling and SQL and procedural programming in few languages in depth , but have not had experience in data science specifically and not with python My intention was only to help with a plan and help you be consistent By the way I have 10 + years of experience in RDBMS with fortune 500 companies But have been working on non profit projects only for the last several years I intended to help only from my general experience I don't have specific experience in data science with python It's best you find someone with specific data science experience

No amount of tutorials can help one to learn python - coding in general, they are good to kick-start the learning but cap at somepoint. Ask yourself, how long have you spent struggling to write a line of code by yourself ? writing code is skill, the more you practice , the more better you'll become doing that. Data science is theory-heavy with lot of math, most of the time you will be using few set of the tools for your experiments, for this I would suggest the learn the foundation of the language and then learn the set of the tools (libraries). All the best.

i can't find the shitty place, so... it's a really shitty ad

append .com

Sorry, this was a bit elaborate xd

Full disclosure, I didn't find it the first time I looked for it neither.

Always work on code yourself. Even if you found it on SO, or got it from Claude, or from some legacy project - remaster it for your own understanding.

thanks

If you can understand python syntax and if you can modify it to suit your requirements you are pretty ahead, have you programmed in other languages where you have built applications from scratch, If yes then your journey may not be so difficult Keep learning, you need to know syntax and you need to write lines of code, you need to write blocks of code you should be able to divide and conquer, split your requirements into functions ( or may be objects) and be able to integrate, focus on all of the above starting with small less complex problems, then larger less complex problems where divide and conquer is easy and then move into more complex problems This was just something I thought up and wrote now so it may not be perfect but if it helps, I will be happy