Telegram Group & Telegram Channel
How to master Python from scratch๐Ÿš€

1. Setup and Basics ๐Ÿ
   - Install Python ๐Ÿ–ฅ๏ธ: Download Python and set it up.
   - Hello, World! ๐ŸŒ: Write your first Hello World program.

2. Basic Syntax ๐Ÿ“œ
   - Variables and Data Types ๐Ÿ“Š: Learn about strings, integers, floats, and booleans.
   - Control Structures ๐Ÿ”„: Understand if-else statements, for loops, and while loops.
   - Functions ๐Ÿ› ๏ธ: Write reusable blocks of code.

3. Data Structures ๐Ÿ“‚
   - Lists ๐Ÿ“‹: Manage collections of items.
   - Dictionaries ๐Ÿ“–: Store key-value pairs.
   - Tuples ๐Ÿ“ฆ: Work with immutable sequences.
   - Sets ๐Ÿ”ข: Handle collections of unique items.

4. Modules and Packages ๐Ÿ“ฆ
   - Standard Library ๐Ÿ“š: Explore built-in modules.
   - Third-Party Packages ๐ŸŒ: Install and use packages with pip.

5. File Handling ๐Ÿ“
   - Read and Write Files ๐Ÿ“
   - CSV and JSON ๐Ÿ“‘

6. Object-Oriented Programming ๐Ÿงฉ
   - Classes and Objects ๐Ÿ›๏ธ
   - Inheritance and Polymorphism ๐Ÿ‘จโ€๐Ÿ‘ฉโ€๐Ÿ‘ง

7. Web Development ๐ŸŒ
   - Flask ๐Ÿผ: Start with a micro web framework.
   - Django ๐Ÿฆ„: Dive into a full-fledged web framework.

8. Data Science and Machine Learning ๐Ÿง 
   - NumPy ๐Ÿ“Š: Numerical operations.
   - Pandas ๐Ÿผ: Data manipulation and analysis.
   - Matplotlib ๐Ÿ“ˆ and Seaborn ๐Ÿ“Š: Data visualization.
   - Scikit-learn ๐Ÿค–: Machine learning.

9. Automation and Scripting ๐Ÿค–
   - Automate Tasks ๐Ÿ› ๏ธ: Use Python to automate repetitive tasks.
   - APIs ๐ŸŒ: Interact with web services.

10. Testing and Debugging ๐Ÿž
    - Unit Testing ๐Ÿงช: Write tests for your code.
    - Debugging ๐Ÿ”: Learn to debug efficiently.

11. Advanced Topics ๐Ÿš€
    - Concurrency and Parallelism ๐Ÿ•’
    - Decorators ๐ŸŒ€ and Generators โš™๏ธ
    - Web Scraping ๐Ÿ•ธ๏ธ: Extract data from websites using BeautifulSoup and Scrapy.

12. Practice Projects ๐Ÿ’ก
    - Calculator ๐Ÿงฎ
    - To-Do List App ๐Ÿ“‹
    - Weather App โ˜€๏ธ
    - Personal Blog ๐Ÿ“

13. Community and Collaboration ๐Ÿค
    - Contribute to Open Source ๐ŸŒ
    - Join Coding Communities ๐Ÿ’ฌ
    - Participate in Hackathons ๐Ÿ†

14. Keep Learning and Improving ๐Ÿ“ˆ
    - Read Books ๐Ÿ“–: Like "Automate the Boring Stuff with Python".
    - Watch Tutorials ๐ŸŽฅ: Follow video courses and tutorials.
    - Solve Challenges ๐Ÿงฉ: On platforms like LeetCode, HackerRank, and CodeWars.

15. Teach and Share Knowledge ๐Ÿ“ข
    - Write Blogs โœ๏ธ
    - Create Video Tutorials ๐Ÿ“น
    - Mentor Others ๐Ÿ‘จโ€๐Ÿซ

I have curated the best interview resources to crack Python Interviews ๐Ÿ‘‡๐Ÿ‘‡
https://topmate.io/coding/898340

Hope you'll like it

Like this post if you need more resources like this ๐Ÿ‘โค๏ธ



tg-me.com/pythonanalyst/985
Create:
Last Update:

How to master Python from scratch๐Ÿš€

1. Setup and Basics ๐Ÿ
   - Install Python ๐Ÿ–ฅ๏ธ: Download Python and set it up.
   - Hello, World! ๐ŸŒ: Write your first Hello World program.

2. Basic Syntax ๐Ÿ“œ
   - Variables and Data Types ๐Ÿ“Š: Learn about strings, integers, floats, and booleans.
   - Control Structures ๐Ÿ”„: Understand if-else statements, for loops, and while loops.
   - Functions ๐Ÿ› ๏ธ: Write reusable blocks of code.

3. Data Structures ๐Ÿ“‚
   - Lists ๐Ÿ“‹: Manage collections of items.
   - Dictionaries ๐Ÿ“–: Store key-value pairs.
   - Tuples ๐Ÿ“ฆ: Work with immutable sequences.
   - Sets ๐Ÿ”ข: Handle collections of unique items.

4. Modules and Packages ๐Ÿ“ฆ
   - Standard Library ๐Ÿ“š: Explore built-in modules.
   - Third-Party Packages ๐ŸŒ: Install and use packages with pip.

5. File Handling ๐Ÿ“
   - Read and Write Files ๐Ÿ“
   - CSV and JSON ๐Ÿ“‘

6. Object-Oriented Programming ๐Ÿงฉ
   - Classes and Objects ๐Ÿ›๏ธ
   - Inheritance and Polymorphism ๐Ÿ‘จโ€๐Ÿ‘ฉโ€๐Ÿ‘ง

7. Web Development ๐ŸŒ
   - Flask ๐Ÿผ: Start with a micro web framework.
   - Django ๐Ÿฆ„: Dive into a full-fledged web framework.

8. Data Science and Machine Learning ๐Ÿง 
   - NumPy ๐Ÿ“Š: Numerical operations.
   - Pandas ๐Ÿผ: Data manipulation and analysis.
   - Matplotlib ๐Ÿ“ˆ and Seaborn ๐Ÿ“Š: Data visualization.
   - Scikit-learn ๐Ÿค–: Machine learning.

9. Automation and Scripting ๐Ÿค–
   - Automate Tasks ๐Ÿ› ๏ธ: Use Python to automate repetitive tasks.
   - APIs ๐ŸŒ: Interact with web services.

10. Testing and Debugging ๐Ÿž
    - Unit Testing ๐Ÿงช: Write tests for your code.
    - Debugging ๐Ÿ”: Learn to debug efficiently.

11. Advanced Topics ๐Ÿš€
    - Concurrency and Parallelism ๐Ÿ•’
    - Decorators ๐ŸŒ€ and Generators โš™๏ธ
    - Web Scraping ๐Ÿ•ธ๏ธ: Extract data from websites using BeautifulSoup and Scrapy.

12. Practice Projects ๐Ÿ’ก
    - Calculator ๐Ÿงฎ
    - To-Do List App ๐Ÿ“‹
    - Weather App โ˜€๏ธ
    - Personal Blog ๐Ÿ“

13. Community and Collaboration ๐Ÿค
    - Contribute to Open Source ๐ŸŒ
    - Join Coding Communities ๐Ÿ’ฌ
    - Participate in Hackathons ๐Ÿ†

14. Keep Learning and Improving ๐Ÿ“ˆ
    - Read Books ๐Ÿ“–: Like "Automate the Boring Stuff with Python".
    - Watch Tutorials ๐ŸŽฅ: Follow video courses and tutorials.
    - Solve Challenges ๐Ÿงฉ: On platforms like LeetCode, HackerRank, and CodeWars.

15. Teach and Share Knowledge ๐Ÿ“ข
    - Write Blogs โœ๏ธ
    - Create Video Tutorials ๐Ÿ“น
    - Mentor Others ๐Ÿ‘จโ€๐Ÿซ

I have curated the best interview resources to crack Python Interviews ๐Ÿ‘‡๐Ÿ‘‡
https://topmate.io/coding/898340

Hope you'll like it

Like this post if you need more resources like this ๐Ÿ‘โค๏ธ

BY Python for Data Analysts


Warning: Undefined variable $i in /var/www/tg-me/post.php on line 283

Share with your friend now:
tg-me.com/pythonanalyst/985

View MORE
Open in Telegram


Python for Data Analysts Telegram | DID YOU KNOW?

Date: |

That growth environment will include rising inflation and interest rates. Those upward shifts naturally accompany healthy growth periods as the demand for resources, products and services rise. Importantly, the Federal Reserve has laid out the rationale for not interfering with that natural growth transition.It's not exactly a fad, but there is a widespread willingness to pay up for a growth story. Classic fundamental analysis takes a back seat. Even negative earnings are ignored. In fact, positive earnings seem to be a limiting measure, producing the question, "Is that all you've got?" The preference is a vision of untold riches when the exciting story plays out as expected.

Spiking bond yields driving sharp losses in tech stocks

A spike in interest rates since the start of the year has accelerated a rotation out of high-growth technology stocks and into value stocks poised to benefit from a reopening of the economy. The Nasdaq has fallen more than 10% over the past month as the Dow has soared to record highs, with a spike in the 10-year US Treasury yield acting as the main catalyst. It recently surged to a cycle high of more than 1.60% after starting the year below 1%. But according to Jim Paulsen, the Leuthold Group's chief investment strategist, rising interest rates do not represent a long-term threat to the stock market. Paulsen expects the 10-year yield to cross 2% by the end of the year. A spike in interest rates and its impact on the stock market depends on the economic backdrop, according to Paulsen. Rising interest rates amid a strengthening economy "may prove no challenge at all for stocks," Paulsen said.

Python for Data Analysts from fr


Telegram Python for Data Analysts
FROM USA