I have planned 5 steps for you to learn Python for Data Science and Machine Learning and learning Python for Data science and ML is no Rocket science. I have also Provided Resources from where you can Learn Python.

Step 1 - Start with Learning the Basics

I recommend you to refer this Python Tutorial to introduce yourself with Python and then prepare your self with the Following Topics:

Python Operators

Python Functions

Python Comprehensions

Python Lists

Python Tuples

Python Directory and Dictionary Comprehension

Decision Making in Python

Loops in Python

Step 2 - Setup your Computer

I recommend Anaconda to gear up for Data Science. Anaconda is an open source distribution for Python and R for large scale data processing, scientific computing and predictive analytics. You can also download Anaconda from Home. It has all you require to learn Python for Data Science and Machine Learning.

Step 3 - Learn Regex ( Regular Expression )

If you have to deal with textual data, regex will come in handy with data cleansing. It is a process of detecting and collecting corrupt errors from records from a record set, data base or table. It identifies inaccurate, incorrect, incomplete and irrelevant parts of data and modifies, replaces or deletes it.

Step 4 - Essential libraries for Data Science and ML

A library is actually a bundle of pre-existing functions and objects that can be imported to your script to save time and efforts.

a. Numpy

b. Pandas

c. Scipy

d. Matplotlib

e. scikit-learn

f. Seaborn

Step 5 - Start Doing Projects with Further Learning

Create something Real on Python. You will make mistakes, get stuck many times, but gradually you will find ways to come out of your problems. On the journey of finding answers to your queries you will learn new things and here the real learning will start.

See: Sakina Mirza's answer to What are some good college projects on Python?

Start with taking the Problems and Programs that are available on web and then you can design your own problem.

And just practice and you will be more perfect everyday.

Also Refer Sakina Mirza's answer to What is the scope of Python?

If this answer was helpful, Please UPVOTE and you can follow my account Sakina Mirza for more answers on Data Science.

ALL THE BEST…

I like Python because it's awesome for prototyping things or making scripts with few lines of code. If I need to read some file line-by-line, parse it with regular expression and calculate some statistics, I definitely prefer Python over combination of bash/awk/grep/sed. If I want to read some not-so-simple XML and write JSON or whatever, I use Python. Some advantages of using Python for problems that should be done once:

1. It has a very simple syntax and it doesn't force you do use something special. You can use lambdas, you can write classes, you can stick with functions, you can write straightforward boilerplate without structurization, if you wish. Everything is up to you
2. Consequence: I need no IDE. Something with syntax highlight is fine.
3. I need no package management system or build system in general. Run the interpreter on your freshly written file and it works
4. It's very and very expressive. Tuples (and ability to return them from functions), list comprehensions, no brackets, no 'public static void main'. You just write code. I rarely can find something that can be shortened without ambiguity. The only thing that is missing are references from C++ and, therefore the 'swap' function.
   
5. Even so, I find to so easy to understand. Very little extra over C or Java, in contrast with Perl or Ruby, for example. No special syntax for the sake of fast typing.
6. Good standard library: regular expressions, json, sockets, files, data structures...
7. Good packaging system that is same across different platforms (easy_install or pip). I type one command and have a package ready to go. I do not care whether it's local or global installed - it just works (remember, I typically use Python for some one-time problems).
   
8. It's strongly-typed (in a way). I don't want two hashes '1e3456' and '1e3457' to be equal just because strings look like floating point number in exponential form (true story from somewhere around PHP).
9. However, you does not need to specify types explicitly - Python has dynamic duck typization, so you don't need generics or templates to write generic code. Plus one for expressivity.

First off, let me tell you why learning Python is such a cool idea:

Benefits of Learning Python:

1. Beginner-Friendly: Python is like the "Hello World" of programming languages. It's super easy to grasp, and the syntax is so friendly that you'll feel like you're chatting with a computer, not commanding it.
2. Versatility: Python isn't a one-trick pony. You can use it for web development, data analysis, artificial intelligence, automation, and more. It's like having a Swiss Army knife in your coding toolbox.
3. Huge Job Market: Companies are hunting for Python wizards. Seriously, the demand is crazy high. So, if you're thinking about a career in tech, Python can open up some fantastic opportunities.
4. Data and AI: Python is the go-to language for data scientists and AI enthusiasts. You can analyze data, build predictive models, and even create smart chatbots. If you're into data-driven decision-making or making cool AI stuff, Python is your friend.
5. Web Development: Python isn't just about data and AI; it's also a web development powerhouse. With frameworks like Django and Flask, you can build websites and web apps in no time.
6. Supportive Community: The Python community is like a big, welcoming family. There are plenty of forums, tutorials, and passionate folks out there to help you on your Python journey.

Now, onto the exciting part - how to become a Python pro quickly!

Best Ways to Learn Python and Become Proficient:

1. Online Courses: There are tons of online platforms like Coursera, edX, and Udemy that offer Python courses for all skill levels. Check them out; they often have interactive exercises and projects to practice.
2. YouTube Tutorials: There are tons of Python tutorials on YouTube, from basic to advanced topics. It's like having a personal coding coach at your fingertips.
3. Python Documentation: Python's official website has a fantastic tutorial and documentation. It's a great place to start, and it's totally free.
4. Books: There are many excellent Python books for beginners, like "Python Crash Course" and "Automate the Boring Stuff with Python." They're a fun way to learn.
5. Coding Exercises: Websites like LeetCode, Codecademy, and HackerRank offer coding challenges that help you practice Python coding.
6. Projects: Building your projects is super effective. Start small, like creating a to-do list app, and gradually work your way up to more complex projects.
7. Join a Coding Community: Reddit has a Python subreddit, and there are Python-related forums where you can ask questions and share your progress.
8. Coding Bootcamps: If you're looking for an intensive, immersive experience, coding bootcamps offer Python-focused programs. They can be pretty effective but might be a bit more of an investment.

Remember, the key is practice and consistency. Try to code a little every day, and you'll see your skills grow faster than you think.

So, my friend, are you up for the Python adventure?
Hope this is helpful
Take Care

First. Congratulations on taking first steps. Here are a few pointers.

You can’t learn programming by just watching youtube. You need to do something. Preferably something that interests you.

Picking python is a good idea. It is a good language to learn and is very popular. If you can spend a little money I would buy Raspberry Pi computer. The cheapest version with Wifi enabled runs at $10. You would need a keyboard a mouse and monitor (you probably already have one) but the whole things is likely to cost under $100.

The beauty of raspberry pi is that it allows you to build some fun projects that will teach you to program in a way that is not boring. You can build a home security system or play minecraft while changing your environment through python code, etc.

If you don’t want / can’t buy raspberry pi then just find a project that would interest you. Something that would be fun to solve through programming. May be a homework assignment in school or something related to any of your hobbies. Awhile ago Pokemon Go was popular. There was a python script that allows you to find locations easily.

Once you find a problem to solve just stick to it. When learning programming (speaking from experience) you need to get to a light bulb moment (“oh I got that now!”) and after that things become simple. But the only way to do that is to keep at it.

But again. Forget the tutorials (not completely but mostly). Start doing things and lookup particular problems you face. Handle each problem in small steps. Once you figure out each small step proceed to next. Once your program is finished look over it and try to make it better. Then do it again and again. Even experienced developers often start with messy code just to make sure that the problem is doable.

Learning Python is an excellent starting point for programming, but whether it's sufficient depends on your goals, career path, and the types of projects you want to work on. While Python is versatile, powerful, and widely used, here’s a breakdown of the benefits and limitations of learning only Python versus expanding to other languages:

Advantages of Learning Python:

1. Versatility: Python is used in a variety of fields, such as:

- Data Science and Machine Learning (with libraries like NumPy, Pandas, TensorFlow).

- Web Development(with frameworks like Django and Flask).

- Automation/Scripting (used for automating repetitive tasks).

- Software Development and Prototyping.

- Artificial Intelligence and Deep Learning.

- DevOps and Cloud services (tools like Ansible, AWS SDKs).

2. Ease of Learning: Python has a simple and readable syntax, making it a great first language for beginners. It allows new programmers to grasp the fundamentals of programming, such as loops, conditionals, and object-oriented principles, without getting bogged down by complex syntax.

3. Large Ecosystem: Python has a vast ecosystem of libraries and frameworks, making it very productive for developers. If you're in fields like machine learning, web development, or scientific computing, Python might be all you need.

4. Growing Popularity: Python is one of the most in-demand programming languages, widely adopted by companies like Google, Netflix, and Facebook. Knowing Python alone could land you a job in fields like data science or backend web development.

When Python May Not Be Enough:

1. Performance-Critical Applications:

- For high-performance computing or real-time systems, Python might not be the best choice due to its slower runtime. C, C++, or Rust would be better suited for systems programming, game development, or low-level tasks requiring high speed and memory management.

2. Mobile App Development:

- While you can create some mobile applications with Python using frameworks like Kivy, it’s not as commonly used as Swift (for iOS) or Kotlin/Java (for Android) for native app development.

3. Front-End Web Development:

- Python is strong in backend web development (via Django or Flask), but for front-end development (websites and user interfaces), you’ll need to learn JavaScript, along with its associated frameworks (React, Angular, or Vue.js).

4. Enterprise Systems and Legacy Code:

- Some industries, especially finance or large enterprises, heavily use languages like Java or C# for large-scale applications. If you're working in these environments, understanding these languages could be crucial.

5. Embedded Systems:

- For working with hardware, embedded systems, or IoT, languages like C or C++ are often more appropriate due to their ability to directly manage hardware resources.

6. Game Development:

- While Python has libraries like Pygame, serious game development typically relies on C++, C#(Unity), or other languages optimized for real-time graphics and complex simulations.

Why Learning Multiple Languages Can Be Beneficial:

1. Wider Career Opportunities: Different industries and roles require different languages. For example, learning JavaScript or TypeScript will make you more marketable as a web developer, while learning C++ might be necessary for game development or systems programming.

2. Better Problem Solving: Each language has its strengths and weaknesses. Knowing more than one language gives you the flexibility to choose the right tool for a given problem.

3. Understanding Programming Concepts More Deeply: Learning different languages exposes you to various programming paradigms (functional programming, procedural, object-oriented, etc.), which can deepen your understanding of programming principles.

4. Cross-Platform Development: Many modern projects require cross-platform expertise. For instance, if you're building a web application, you might need Python for the backend, JavaScript for the front end, and SQL for the database.

5. Interoperability: Often, projects involve multiple languages. For example, Python code might need to interface with a C library for performance reasons. Understanding other languages can help you work more effectively in multi-language environments.

Conclusion:

Python is a fantastic language to start with and can take you far, especially in fields like data science, automation, web development, and AI. However, to be a well-rounded programmer or work in specific industries, you’ll likely need to expand your skillset and learn other languages.

To summarize:

- For Data Science, Automation, and Backend Development, Python is often sufficient.

- For Mobile, Game, Embedded Systems, or High-Performance Applications, other languages like Java, C++, C#, Swift, Kotlin, or Rust may be required.

- For Front-End Web Development, you’ll need to complement Python with HTML/CSS, JavaScript, and related frameworks.

Ultimately, learning other languages enhances your versatility, but Python provides a strong foundation to build upon.

I don’t know if it is the way, but it is an approach I often propose on Quora. Following this method will allow you to learn programming principles using the Python language rather than just learn Python as a programming language.

This is an important distinction because in programming it is the fundamentals that are important. Once you understand those then the language you use is really just a matter of how appropriate it is for a given project. Happily Python is a decent language for many different types of projects.

Anyway, here are the steps:

1. Learn Python the Hard Way has been the go to free resource to learn Python along with general good programming principles. This resource may still require you to develop in Python 2.x which is good because there is still a butt load of 2.x code out there. Finish this course and make sure you understand everything.
2. However, Python moved forward and so should you. https://inventwithpython.com/ is a brilliant resource for learning Python 3 (again from scratch). There are five tutorials/courses to do. Finish all of them.
3. Now that you have a great basis, register on CheckiO and solve as many problems as you can. Here you are learning to code by playing a game. Solve as many challenges as you can, then try and solve each challenge with as little code as possible.
4. Also register at https://www.hackerrank.com and start solving problems. The better you do, the better your chances of getting hired. These guys are hooked up to some serious employers, and your rank counts.
5. Remember to register on Stack Overflow where you will find willing and helpful programmers that can answer any well formulated questions you may have.
6. By now you will have enough knowledge to tackle Test-Driven Development with Python - this knowledge is critical as a skill in the workplace.

And there you have it - a full curriculum that you can do within three to six months (depending on your aptitude and the amount of time you have available).

Let’s compare some of the most popular languages with Python to do what it takes to print “Hello, World!”, the first thing any programmer is taught in any intro CS class.

C

#include<stdio.h> 
 
main() 
{ 
    printf("Hello World"); 
} 

C++

#include<stdio.h> 
 
main() 
{ 
    printf("Hello World"); 
} 

Java

public class HelloWorld { 
   public static void main(String[] args) { 
      System.out.println("Hello, World"); 
   } 
} 

C#

public class Hello1 
{ 
   public static void Main() 
   { 
      System.Console.WriteLine("Hello, World!"); 
   } 
} 

And here’s Python

print "Hello, World!" 

Just one line, that’s it.

Python’s syntax is very simple and easy to learn compared to other languages so you should be able to easily pick it up if you understand programming or have programmed before in any other language. It’s a really fun language to learn and very powerful too. I’d highly recommend it.

The most important question to answer first is why do I want to learn python? Answering this will guide what you use to learn and how you learn.

Starting with a very generic list of resources to learn python when you eventually want to make websites (for example), will not only reduce your motivation, it will also make it much harder to apply the knowledge you gain. I've tried to learn coding without context and application, and I've almost never come out of it with any meaningful skills.

When I learned python 3 years ago, I wanted to create websites. It shouldn't come as a shock to anyone that the best way to learn how to do this was to create websites.

1. Find what motivates you

Finding and keeping your motivation is key -- I slept through a lot of the one high school programming class I took because it made us memorize a bunch of syntax. On the other hand, when I needed to learn python to make an automated essay scoring algorithm, I stayed up many late nights learning and iterating.

Motivation is rarely addressed in learning -- you're often just given a list of generic tutorials to try, and told to go do them. But the great thing about python is that you can develop almost anything, from mobile apps to games to advanced machine learning algorithms. No matter what you're interested in, you can probably build it in python, and there's probably a good getting started tutorial.

Pick an area or two that you're interested in, and stick with them-- you'll be developing quite a few projects in the areas.

Here are some sample areas, but feel free to add your own:

• Websites
• Mobile apps
• Games
• Data science/Machine learning

2. Learn some basic python syntax

Unless you know the basic syntax, it's hard to implement anything. That said, don't spend too long on this. The goal is to learn the very basics, so you know enough to start working on your own projects in your areas(s) of interest.

For reference, I spent less than a week on codecademy, and went through about 30% of the material. This was enough to get started on a project.

Some resources that can help you:

• Codecademy -- does a good job of teaching basic syntax.
• Learn python the hard way -- a book that teaches a lot of python concepts.
  
• Dataquest.io -- this is my startup. It's focused on teaching python for data science, but it teaches all the basic syntax also.
• The Python Tutorial -- the tutorial on the main python site.
  

I can't emphasize enough that you should only spend the minimum amount of upfront time possible on basic syntax. The quicker you can get to working on projects, the faster you will learn. You can always refer back to the syntax when you get stuck later.

3. Make structured projects in your chosen area

Unless you actually apply your knowledge, you won't be able to retain it well. Projects are a great way to learn because they push your capabilities, show you how to apply skills, and give you a portfolio to show employers in the future.

When you start out, it can be helpful to have more structured projects with some guidance. Here are a few ideas:

Games

• Codecademy -- walks you through making a couple of simple games.
• Pygame tutorials -- pygame (the python library for making games) has a good list of tutorials
• Making games with pygame -- this book looks like a great way to learn python by making games
  

Websites

• Flask tutorial -- the official flask (simple python web framework) tutorial.
• Bottle tutorial -- Bottle (even simpler web framework for python) tutorial.
  
• How To Tango With Django 1.7 -- a guide to using django (more complex python web framework)

Mobile apps

• Kivy guide -- Kivy is the tool that lets you make mobile apps with python. They have a guide on how to get started.

Data science

• Dataquest.io -- Teaches you python and data science interactively. You analyze a series of interesting datasets ranging from CIA documents to NBA player stats.
• Scikit-learn documentation -- Scikit-learn (the main machine learning library for python) has some great documentation and tutorials.
• Python for Data Analysis -- written by the author of a major python data analysis library (pandas), it's a good introduction to analyzing data in python.

4. Work on projects on your own

Once you have learned the concepts in a guided manner, it's time to work on some projects on your own. You'll still need to consult references and look up concepts, but you'll be fitting what you learn into the needs of your project, not the other way around.

Finding other people to work with here can both help you learn and help keep you motivated.

Some ideas:

• Extend the projects you were working on previously, and add more functionality.
• Go to python meetups in your area, and find people who are working on interesting projects.
• Find open source packages to contribute to.
• See if any local nonprofits are looking for volunteer developers.
• Find projects other people have made, and see if you can extend or adapt them.

My first project was adapting my automated essay scoring algorithm from R into python. It didn't end up looking pretty, but it started me on the journey to learning python.

The key is to pick something and do it. If you get too hung up on picking the perfect project, there's a risk that you'll never make one.

5. Keep working on harder projects

Keep increasing the difficulty and scope of your projects. If you're completely comfortable with what you're building, it means it's time to try something harder.

Here are some ideas for when that time comes:

• Try teaching a novice how to do your current project.
• Try load testing your website -- can you scale it up?
• Can you make your program run faster?

Going forward

At the end of the day, python is evolving and changing all the time. There are probably only a few people who can legitimately claim to completely understand it.

You'll need to be constantly learning and working on projects. If you do this right, you'll find yourself looking back on your code from 6 months ago and thinking about how terrible it is. If you get to this point, you're on the right track.

Python is a really fun and rewarding language to learn, and I think anyone can get to a high level of proficiency in it if they find the right motivation.

Hi,

Trust me 100% learning Python is fairly simple from the ground up from knowing nothing to being able to do something, the most important thing for a total beginner is to find the right resources, About 1 year and a few months back I also was like you I wanted to learn how to code. What made learning Python easier for me was I had used an app called Grasshopper for about a week and I used to read the Python documentation even when I never used to understand anything, but that doesn't matter. I would advice you check out a book called Python Crash Course by Eric Matthes I can recommend that book 100% it works u will go from knowing nothing to making websites, and even learning how to make data visualization and simple 2D games. Don't worry learning Python is not HARD! All you need is time and patience I remember I would spend about 2 hours per day everyday on my computer and my mum was concerned, anyways after about 3 weeks I would say I knew how to do something with Python. Step by step you will see change each and everyday....as you progress you will run into challenges but you never quit.

I know you will learn Python.

In conclusion,

Python is fairly easy to learn than other languages.

Just take your time even if 20 to 30 minutes per day.

Last but not least have a positive attitude don't give up 😉 even if things are confusing you will get to understand after sometime.......

BUT MOST IMPORTANTLY OF ALL DONT FORGET THIS. "PERFECT PRACTICE MAKES PERFECT" Feel free to ask any question regarding Python I'll be eager to answer.

There are many good reasons for learning Python.

1. It is a very beginner-friendly language, which can teach you many concepts like OOP and how variables work.
2. It is very popular, with well-paying jobs for it.
3. It is simple to set up, and you do not need any 6.7 GB software to do this
4. It has many libraries to extend functionality, and to install them, you just need to go to PowerShell and type “pip install <package name>”
5. Python is a really good alternative to FORTRAN for data science
6. You can learn about server-side development
7. Python is very abstract, meaning stuff is hidden from you, making code easier to read.
8. Many courses are available to learn Python
9. Python follows WORA (Write Once, Run Anywhere,) meaning as long as Python 2.x or 3.x is installed on the machine, a Python app can be run.
10. Python can be used to supplement simple functions needed in other applications made in other languages (like C++,) without the heavy lifting of more complex languages.

Python Programming language is easy to learn compared to other languages like Java, C#. With the advent of ML, AI and LLM models, Python is very much in demand. To learn Python programming thoroughly, you need a combination of consistent practice, comprehensive resources, and hands-on projects. Follow the following steps to learn Python programming 100%.

1. Start with the Basics - Before diving into the complex topics of Python, learn the basic concepts like data types, variables, functions, loops, flow controls and conditional statements.
2. Practice Coding Regularly - Programming practice is the key to learn good programming and Python no different from that. Start with small exercises and gradually work on more challenging programs and projects. There are multiple example programs given for each article in this Python Tutorial. Follow this entire tutorial for good learning.
3. Start learning for Intermediate and Advanced Concepts - Once you complete learning the basic concepts of Python, you can start learning for Intermediate and Advanced concepts of Python. Topics like object-oriented programming (OOP), modules, and file handling, Iterators and decorators will deepen your understanding of Python.
4. Start working on the Projects - Working on the Python Project is important. Apply what you've learned in Python Programming. Build real-world applications like web scrapers, automation scripts, or even web apps.
5. Learn Popular Python Libraries - Learn about key libraries like NumPy, Pandas, Matplotlib for data analysis, and Flask/Django for web development.

This Python Tutorial covers everything from Python basics to advanced topics, providing structured learning paths and tutorials.

Answer assumes that you are going to start with Python. If you guys are already friends, then it would be a different path, to make the bond stronger.

There's a 90–10 rule to learn something new, especially in software development.

That means, to learn 90% of something new, you need to put in 10% of efforts, and for the rest 10%, your 90% efforts and continuous practice is needed.

If we talk about python, my personal opinion is that covering the initial 10% is much easier and lesser time consuming than most other languages like C++ & Java. (Thanks to duck typing)

There's a really good series of 5 courses for python, on Coursera. They have a Python specialization. Taking the courses and accessing all the material is free, unless you want to participate in graded tests and need a certificate. The first two courses will get you up and running with Python and it's inbuilt data structure libraries. The other three will also help in getting your hands on some real life applications like database management with python or web scrapping.

If you can find 1–2 hours over weekdays, and 4–5 hours over weekends, you can easily finish a course a week. And in a month(or max 2) from the day of starting it, you will be quite confident with basics, and that would be the time to take up some project. Depending on your interest. I would suggest after few small 1–2 page scripts, look for something interesting that you can build using some existing framework. That will help you in being more comfortable with class structure, and few design paradigms of python(design pattern or not) Python has it's own way of doing things, that are sometimes considered “blasphemy” by the religious followers of other languages, but considered the “Pythonic way” by python fans.

Just an interesting fact to get you jump in the sea, Python doesn't have “switch case”. How similar situation is handled in python, is a matter of debate between Python advocates and others, while both sides of arguments being quite interesting and sensible.

Happy learning…

Recently (about 8 months ago) I asked the same question and here is what i did:

1. CodeAcademy - for syntax
2. MIT OpenCourseWare - to help me understand better
3. while doing 1 and 2 search for 'python problems for beginners' to exercise
4. Object-Oriented Programming in Python by Michael H. Goldwasser and David Letscher (this booke helped me alot to understand the paradigm)
5. The Object-Oriented Thought Process (this book uses Java, but again helps you understand better the paradigm and also there is not much coding here)
6.Python 3 Object Oriented Programming by Dusty Philips
7. Mastering Object-oriented Python by Steven F. Lott
8. Python Algorithms by Magnus Lie Hetland
9. Data Structures and Algorithms in Python by Michael T. Goodrich, Roberto Tamassia, Michael H. Goldwasser

This was going to be my path if i knew better 4 months ago :D
now i am more like 1,2,3,4,7(i am here),5,6,8,9.

The most important thing is to practice! When you're done with the first 4 you would want to make some projects that are not simple exercises, and you would probably have hard time figuring out a project to work on. Don't think that the project has to be the next 1 billion dollar thing, just pick something that would help you solve someone's problem. For example you are in the store waiting, the cashier says 'the register is not working' and baam the thought comes to mind, i will make a simple store management system (this is what happened to me..).

If at some point you feel that you haven't learned anything or you forgot something that you studied yesterday, don't worry it's normal, just reread it and move on!

Hope I helped!

Learning Python programming 100% can be an exciting and rewarding journey, especially since Python is one of the most versatile and beginner-friendly programming languages available. Whether you're looking to build web applications, automate tasks, dive into data science, or simply enhance your coding skills, mastering Python is achievable with the right approach, dedication, and resources.

Step-by-Step Guide to Learning Python:

1. Understand the Basics of Python: Every learning journey starts with building a solid foundation. Before diving into complex projects or advanced libraries, it’s essential to get comfortable with Python’s syntax and basic concepts. Start by learning:

• Variables and Data Types: Understand how Python handles different data types like strings, integers, lists, dictionaries, etc.
• Control Structures: Learn about conditionals (if-else statements) and loops (for, while) that help control the flow of a program.
• Functions: Understand how to create reusable blocks of code using functions, parameters, and return values.

These fundamentals will allow you to solve basic problems and write clean, logical code. There are plenty of beginner-friendly tutorials online that provide interactive lessons for mastering these concepts.

1. Practice Regularly with Small Projects: After grasping the basics, it’s essential to start coding daily. Python, like any other skill, improves with practice. You can start with small projects such as:

• A basic calculator.
• A simple game like Tic-Tac-Toe.
• A script to automate tasks like renaming files or scraping data from websites.

Tip: Websites like LeetCode, HackerRank, and Codewars offer challenges that test your coding skills and help you apply what you've learned in real-world scenarios.

1. Learn Object-Oriented Programming (OOP): Once you're comfortable with the basics, move on to learning object-oriented programming (OOP). This is an essential aspect of Python that allows you to write more organized, reusable, and scalable code.

• Understand Classes and Objects.
• Learn about inheritance, encapsulation, and polymorphism.
• Practice building Python projects using OOP principles, such as creating your own modules and libraries.

1. Explore Python Libraries and Frameworks: One of the reasons Python is so popular is its vast ecosystem of libraries and frameworks. These libraries can significantly boost your productivity, whether you’re working in web development, data science, or machine learning.

• For Web Development: Explore frameworks like Django or Flask.
• For Data Science: Learn libraries like Pandas, NumPy, Matplotlib, and Seaborn.
• For Machine Learning and AI: Get hands-on with TensorFlow, Scikit-Learn, and Keras.

These libraries simplify complex tasks, such as building machine learning models, processing large datasets, or creating web applications from scratch.

1. Work on Real-World Projects: As you progress in your Python learning, working on real-world projects is a great way to solidify your understanding and build a portfolio. This could include:

• A personal website or blog built using Flask or Django.
• A data analysis project using Pandas and visualizations with Matplotlib.
• An automation tool to simplify repetitive tasks in your daily workflow.
• Contribute to open-source Python projects on GitHub. This will expose you to best coding practices and improve your skills.

Real-world projects give you hands-on experience and also help you understand how to troubleshoot issues, work with APIs, and collaborate with others in a professional setting.

1. Stay Consistent and Keep Learning: Python, like any other language or skill, requires consistent effort and practice. Set aside time each day or week to learn and code. It's also important to stay updated with the latest trends, as Python is continuously evolving.

• Follow Python blogs, podcasts, and YouTube channels.
• Join Python communities like Stack Overflow, Reddit's r/learnpython, or local coding groups where you can seek help and share knowledge.
• Continuously challenge yourself with new projects or learning paths like data science, web development, or automation.

1. Enroll in Structured Python Courses: While self-learning is important, sometimes having a structured course can help streamline the learning process. Courses provide a clear curriculum, hands-on projects, and mentorship that can accelerate your learning.

For example, Brain Mentor Pvt Ltd offers hybrid classes that blend both online and offline teaching methods. These hybrid classes provide flexibility for learning at your own pace while giving you access to industry-expert instructors who can guide you through practical applications of Python programming. Whether you're a beginner or looking to sharpen advanced skills, a structured course with Brain Mentor ensures that you're learning in a comprehensive and hands-on environment.

By taking advantage of a hybrid learning model with Brain Mentor Pvt Ltd, you’ll be able to learn Python from anywhere, gain practical skills through real-world projects, and receive personalized guidance from experts. This makes the journey to mastering Python smoother, faster, and more efficient.

It seems that you already has the sense of programming and it should be easy for you to learn some other programming languages. As my experience you should find a specific language to solve your problems such as Python, ruby and etc. Once you have chosen a language you should care about four things:

1. How to use loops in this language: for, while loop
2. How to use logic branches: if, else, switch
3. What data types it offers
4. How to use program blocks: package, function, class

It won't take you more than 30 minutes to learn these four things above if you have any programming background before. You can implement all kinds of algorithms with the help of knowledge above.

What's Next?
Use this programming language to solve your problems. Never be shy to ask Google for any questions such as string process, file process once you have encounters a problem.

If you're already proficient at C and/or Java then consider the cost/benefit analysis for learning Python.

The costs:

• An hour or so for the syntax including all 31 keywords, seven core data types and their methods, a couple dozen commonly used functions (out of a total of 76 "built-ins" in the top-level name space and about 100 "magic" or "dunder" ("doubled underscore") methods) if:...elif:...else:, conditional structures for and while loops, try: ... except: handling, with context management (resource handling), and, of course the code organization and re-use with def, class, and import. (Yeah. Only one or two hours to cover that, because they're basically the same, conceptually, as corresponding features in C and Java but with sorta mostly pseudo-code syntax).
• Another few hours, perhaps a full day to learn more advanced syntax and semantics: list comprehensions, decorators, generators and generator expressions, iteration and context management protocols, set and dictionary generator expressions.
• A week or so learning the most useful dozen or so of the 430 modules in the 2.7 standard libraries, and 317 modules included with 3.4
• A couple of months discovering the third party modules that are most useful for your needs. There are over 10K listings on PyPI - the Python Package Index and this site: Python 3 Readiness tracks the "readiness" of the 360 most interesting packages for the transition from Python 2.x (legacy version which is still dominant in real world usage) to Python 3.x (which is the future and slowly gaining deployment ... currently at around 20%)

Those are, admittedly, rather optimistic estimates. They depend quite a bit on just how proficient you are at programming (apart from your specific skills in any given language) and, especially, on how easily you pick up a new language, and how much focus you can achieve over the time spans I've estimated.

It's really easy to pick up the very basics of Python. Mastering its idioms takes as long as any other language.

What's the value proposition? What are the benefits?

Mostly you get to work in a very high level language with about the broadest range of support for real world, practical stuff that can be found in computing.

For most APIs, file formats, and services, there are already modules available for Python, almost all free and mostly of reasonably good quality. Search PyPI for almost anything you'd conceive of programming and there's a reasonably good chance that you can fetch and use, usually with only a dozen or so lines of code. (As an example I wanted to find some numbers to intersperse in my estimates above ... and easily found: stdlib-list 0.2.1 which pulls the lists of standard libraries off the official documentation websites for any version of Python).

You get to work in a REPL (Read-Eval-Print-Loop) to explore your requirements and the behavior of code that you're writing, and especially the code that you're using ... that you're building your programs over. In particular you get to use iPython which is the pre-eminent interactive shell for Python ... and to use iPython Notebooks to document and collaborate on your computations.

Also, if you step out into the job market you'll find that many sites want practical skills in very high level scripting languages such as Python, Ruby, or Javascript. Even if you're going to work in C or Java it's handy to be able to do prototyping, testing, and backend glue work in something that's more "RAD" (suited for rapid application development).

There are plenty of benefits of learning Python but we can’t be fair if we talk only about advantages so here are pros and cons of learning Python:

Pros
1. Versatile: you will have a hard time trying to find something that cannot be done on Python. It doesn’t mean that it’s the best language for everything (see Cons) but most software can be done en it.

2. Ease and speed: this is for the one developing the code. You can build your software way faster than you would do with other programming languages.

3. Readability and maintainability: reading Python is like reading English. It will be easy for coworkers to understand your code and also develop the product on top of the code you already have.

Cons

1. Speed: I’m not going to tell you that speed is the only con of Python but IMHO is tho only one you should really pay attention to. Even Python is the most used language in AI but although it can handle every problem it can take quiet a long time to run (clarification at the end between creating speed and running speed)
2. Memory: Python is expensive not only in terms of speed but also in terms of memory so that’s other thing you could pay attention to.

I have talked from a business perspective because at the end the goal of a programmer is to help the companies or humanity to come with a solution to real problems so we should look for how much value we can create. I mentioned speed as a pro and a con and it’s because Python is very good for creating a solution really fast but your program will run slow. So Python is great when you want to be in a field where a fast solution is more important than the running speed or power consumption of your solution.

Happy coding!

Is as hard as learning just about any other programming language

At first it gives you a feeling that is easy…pretty much like some old Basic style languages…how hard can it be…you start typing like writing in Word and surprise surprise the code works…no special variable declarations..no strict methods handling…and it even gets better with duck typing for classes…

Somewhat you have read the initial tutorials…you have typed a few lines and you have created a masterpiece..great…you feel like a semi god… a programmer on pretty much every other language would spend days/weeks/months to accomplish the same…

And then you start to create your own applications…nobody is holding your hand…the tutorial got you to a point and now its up to you…and now the issues start…should i use the X library or the Y library…or both…and what is the syntax to accomplish “this”…and now something is not working because the indentation was wrong..and you missed it…and wait…duck typing on the classes is great but i want to do more robust coding … in the end you probably end as every other programmer…you have to work for years to get to a level that you are considered good Python programmer.

Think it like this

You have 2 Ladders…each with 100 steps

1 Ladder is for Python ..call it LadderA

1 Ladder is for another language …call it LadderB

In LadderA the first steps are way too easy…you are just hoping 2–3 even 4 at a time…you quickly reach step 20 (in no time)…but the next steps are hard…way too hard…and you will need much more time to climb them

In LadderB the steps are hard no matter what…you go one step at the time…each step takes some considerable amount of time..but each step is almost the same as the previous or the next…

So in the end the time you took to climb LadderA and LadderB is equal…simple.

Is learning Python sufficient for programming, or is it necessary to learn other languages as well?

Programming is a tool used to solve problems. The problem might be “I need a website (web app) for my business”, in such a case, you are able to make web apps using Python web frameworks. So I guess the question can be posed as “Can I solve a lot of technical problems with python programming?” And the answer to that is Yes.

With Python programming, you are able to:

1. Create web applications using Django web framework. Web apps are everywhere! Quora is just an example of a web app and the backend services for quora can be built using web frameworks in python. There are other frameworks such as Flask, Bottle, Cherrypy etc that can be an alternative to Django.

1. Create mobile apps using Kivy framework . Kivy is a python library which allows you to create cross platform apps using python programming language alone. The apps you create can be used for mobile apps, desktop apps etc. So if you need a simple mobile app, kivy framework may just be the framework you need.

1. Build machine learning models using python. ML & AI is all the rage nowadays! The most advanced libraries and tools for performing AI & ML tasks are all written in python, making it easy for you to do any ML work completely using python programming.

1. Build desktop apps using Python Libraries like Tkinter. Tkinter is a standard library which ships with python. It is similar to Kivy framework and allows you to create desktop apps on windows, ios etc.

1. Create beautiful data visualizations using python libraries like Plotly.

1. You can even perform engineering simulation such as CFD (Computational Fluid Dynamics) using python libraries.

All the above shows how versatile Python programming is! So I can say that learning python is sufficient for most tasks. If you can learn javascript as well, it will open up all the opportunities for what you can do.

Disclaimer: Some of the links shared are to my personal youtube channel.

Python itself? Easy. It’s designed to be extremely simple, just like every other programming language. By definition, it’s small word count, consistent ruleset, non exceptions, etc. Make it waaaayyyy easier than human languages. That’s a prerequisite for programming languages - they have to be simple enough for a dumb computer to interpret, making it extremely simple for a human to write.

But, that’s not programming. Same as learning a dictionary, doesn’t turn you into a novelist.

Learning to program, no matter what language you pick, is hard. You could select a no-code language, some graphical puzzle piece placer, and the programming itself is still a hard thing to grasp.

Think back to maths questions. Particularly those “story-mode” questions. Those that don’t just ask you a formula, and the answer. But some description of what happened, and then asks you to solve some measure from that story. That is equivalent to an extremely simplistic program.

Programming starts with what is called a “problem definition”. Basically, the “story” to describe what you want the program to do. Even this, in itself, can be brain damagingly difficult. It’s like coming up with your own question to ask yourself.

And that’s just the start. Following from there, you now have to solve the “problem” by breaking it down into simple steps. Yet again, so that “dumb” computer can actually accomplish those steps.

And once you can do this regularly, no matter what problem is thrown at you. You’re an entry level programmer. Now comes the really difficult part. how to ensure it works correctly every time, no matter what occurs. Do you have to add extra steps to ensure nothing untoward happens? Something unexpected - which, by definition, you couldn’t think of before?

Learning to think of future changes, future possible fixes as those unknowns sneak up. Allowing others to easily understand what you created, so they can also work on it. That is the sign of a professional.

And yet, none of the above, is relevant to “a” particular programming language. No matter what language, those things are always just as difficult as any other.

Where programming languages differ between one another. Is in those steps to solve the problem. Some make you define each and every step the computer has to take. Others have pre-created some generic sets of steps you can select from, abstracting them, so you can move on and only think up the steps relevant to your own program. All programming languages fit somewhere in between just a way to tell the computer how to handle electrical signals, through to using pre-designed concepts (loops, data structures, etc.)

Python is one language where a lot of those pre-built stuff are available. It’s probably one of the most abstracted languages. But, that also makes it less useful, since a general purpose piece of a program may not perfectly fit your particular problem. It may not function exactly as you want, it may be too slow (following unneeded steps), etc.

some things are incredibly easy in python ..like printing hello world…wupee !

but once you get down to some serious problems, python is just as difficult as any other language….

im just a novice programmer, but had to write some multithreading code with python ..using threads and events, and lots of dictionary entries holding objects…

now when i was seeking help, as i was totally confused, i found a lot of the community hadnt even done such things..

they run around saying python is easy…and really dont get that involved with classes and inheritance and superclasses and threading…

these are useful things to learn when using an object oriented programming language..

i also found the libraries quite confusing, and again not a lot of help there, eg asyncio… then as a beginner i found l ot of people have different approaches on how to do something…they tell you that it is ridiculous that you are trying to do something a certain way…and hten advise to do it another way.

then someone else says how ridiculous it is to do something that way …and how you should have done it this way.

i found it best to listen to them and try and just get the job done. .. and working.

but maybe i am not cut out for programming, but i most certainly found things difficult, and for a useful module i wrote…i had to learn about

classes, methods, __init__ , threading, loops, accesing external API, json, slicing text pygame, and general coding and objects, event handling, dictionaries, and ,much more.…

i would say the small project i did that involved getting stuck into all that, was a novice project….but as you can see …it was no

print(‘hello world’)

so to reiterate, python is difficult and if you are doing anything worthwhile will take a lot of frustration, a lot of effort, and a long time.

in general the syntax is less cluttered than other languages…but this can also cause issues….i dont know if i am dealing with a float a decimal a text string or an object reference…as you dont have to declare your types etc.

im starting to think the world is full of absolute jokers that call themselves coders……

python is hard, but the hardest part is actually learning to solve problems to a problem you need to automate..sometimes if you are doing many tasks and setting many events and things…it is overwhelming and easy to get confused twisted and lost.

people make out python is easy … becasue they are only doing superficial things with it ..which are easier than doing superficial things with another language..eg java or c++.. but at the end of the day…you can do anything with python , just as you can with java or c++ and you can go super easy…to super complex.

but beginning the basics with python is generally quite straight forwards.

I do not have personal opinions or emotions, but here are some objective facts: "Learn Python the Hard Way" is a popular beginner's guide to learning the Python programming language, written by Zed Shaw. It has a unique teaching style that emphasizes practice and repetition, which can be helpful for some people in solidifying their understanding of the language. However, the book has received criticism for its outdated teaching methods and for promoting poor coding practices. Ultimately, the effectiveness of the book will depend on the individual reader's learning style and needs.

I hope you understand this.

Pick a project small that you want to solve that will touch someone else's life. Projects that don't have the possibility of affecting someone else quickly become stale.

There are three fundamental drives that you can always rely on: health, wealth and relationships.

Build something that will affect one of those three things.

Health

• Script that takes a jogging route and plots it on a map via Google Maps API
• Cron job that reminds you to take a break every 90 minutes
• Calorie counter. Takes in a recipe, figures out the ingredients and then does calorie/nutrition calculations.

Wealth

• Stock Investment Analysis tool - just pull data from google/yahoo
• Homepage that displays "Days until you can purchase X" -> where X is something you really want.
• Tool for remembering who owes who what.

Relationships

• Script that automatically wishes all your facebook friends Happy Birthday
• Auto-schedule calendar invites with friends for different activities. Rotate accordingly.
• Photo gallery app that is a scrapbook of shared moments.

The realm of ideas is infinite. Staying motivated is the hard part.

A lot of people now-a-days hate this answer… but

Reading and Practice

Are the #1 ways to learn any kind of programming.

Start with a book that teaches you the basics.

If you can’t afford a book, search the web for the basics of programming in python. There are tons of websites out there.

If you want a general outline of what you’ll learn as you go:

• Data types
• Operators
• Type casting
• If/else statements
• Nested if/else statements
• Switch statements
• Loops
• Nested loops
• Files and data storage
• Functions
• Overloading functions
• Arrays
• N-dimensional arrays
• Classes
• Inheritance
• OOP (object oriented programming)
• Exceptions
• Libraries
• Recursion
• Binary trees
• … etc

On to the next point.

If you don’t practice what you read, then there’s no point in reading.

Follow the text. Be creative. Try changing the code and see what it does.

Coding isn’t all science.

Like Rick Sanchez once said:

Don’t be afraid to mess up… A LOT

But if you want to get started

You can google Python IDE (Download Python)

BeginnersGuide/Download - Python Wiki

Download it.

Search for Python basics.

(BeginnersGuide/NonProgrammers - Python Wiki)

And enjoy the journey.

Good luck!