We may have a plan to learn. We may have a plan to create a new product. We may have a plan to achieve a well-paying remote job.

But the important thing is how far we have come in terms of our professional abilities and the discipline we have to move from being wanted to being wanted.

Work until you no longer have to chase opportunities—until opportunities chase you.

Have a good working day.

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Books and tutorials are great, but nothing teaches you faster than getting your hands dirty. Even the tiniest project, a to-do app, a note saver or a random quote generator, forces you to:

Think through problems step by step

Debug real issues (not textbook ones)

See how code fits together in the real world

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Learning Python for data science can be a rewarding experience. Here are some steps you can follow to get started:

1. Learn the Basics of Python: Start by learning the basics of Python programming language such as syntax, data types, functions, loops, and conditional statements. There are many online resources available for free to learn Python.

2. Understand Data Structures and Libraries: Familiarize yourself with data structures like lists, dictionaries, tuples, and sets. Also, learn about popular Python libraries used in data science such as NumPy, Pandas, Matplotlib, and Scikit-learn.

3. Practice with Projects: Start working on small data science projects to apply your knowledge. You can find datasets online to practice your skills and build your portfolio.

4. Take Online Courses: Enroll in online courses specifically tailored for learning Python for data science. Websites like Coursera, Udemy, and DataCamp offer courses on Python programming for data science.

5. Join Data Science Communities: Join online communities and forums like Stack Overflow, Reddit, or Kaggle to connect with other data science enthusiasts and get help with any questions you may have.

6. Read Books: There are many great books available on Python for data science that can help you deepen your understanding of the subject. Some popular books include "Python for Data Analysis" by Wes McKinney and "Data Science from Scratch" by Joel Grus.

7. Practice Regularly: Practice is key to mastering any skill. Make sure to practice regularly and work on real-world data science problems to improve your skills.

Remember that learning Python for data science is a continuous process, so be patient and persistent in your efforts. Good luck!

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Official Python Docs
https://docs.python.org/3/

Tools:
http://docs.python-guide.org/en/latest/dev/virtualenvs/
http://www.pythonforbeginners.com/basics/python-pip-usage

Practice:
http://www.practicepython.org/
https://www.hackerrank.com
https://wiki.python.org/moin/PythonDecorators

Python GUI FAQ
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Python Projects
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There is something rewarding about grappling with yourself to attain what you are striving for.

Make the walk your “mental commit”

Move, relax, and regenerate your energy.
Let the screen fade and your thoughts settle.
Each step helps you close the code loops in your head.
You’re not just walking, you’re syncing body and mind for tomorrow’s push.

🔆 t.me/techpsyche

Convert Images to PDF using Python

How to get job as python fresher?

1. Get Your Python Fundamentals Strong
You should have a clear understanding of Python syntax, statements, variables & operators, control structures, functions & modules, OOP concepts, exception handling, and various other concepts before going out for a Python interview.

2. Learn Python Frameworks
As a beginner, you’re recommended to start with Django as it is considered the standard framework for Python by many developers. An adequate amount of experience with frameworks will not only help you to dive deeper into the Python world but will also help you to stand out among other Python freshers.

3. Build Some Relevant Projects
You can start it by building several minor projects such as Number guessing game, Hangman Game, Website Blocker, and many others. Also, you can opt to build few advanced-level projects once you’ll learn several Python web frameworks and other trending technologies.

4. Get Exposure to Trending Technologies Using Python.
Python is being used with almost every latest tech trend whether it be Artificial Intelligence, Internet of Things (IOT), Cloud Computing, or any other. And getting exposure to these upcoming technologies using Python will not only make you industry-ready but will also give you an edge over others during a career opportunity.

5. Do an Internship & Grow Your Network.
You need to connect with those professionals who are already working in the same industry in which you are aspiring to get into such as Data Science, Machine learning, Web Development, etc.

Python for Data Science: t.me/pythonresourcestp/178

Official Python Docs: t.me/pythonresourcestp/186

Convert Images to PDF using Python: t.me/pythonresourcestp/189

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