⚡️ Free AWS Machine Learning Foundations Course | Udacity | Udacity Free Courses
👇👇
https://bit.ly/2WxReQE

Here we have compiled a list of 40+ cheat sheets that cover a wide range of topics essential for you. 👇

1. HTML & CSS :- htmlcheatsheet.com
2. JavaScript :- https://lnkd.in/dfSvFuhM
3. Jquery :- https://lnkd.in/dcvy6kmQ
4. Bootstrap 5 :- https://lnkd.in/dNZ6qdBh
5. Tailwind CSS :- https://lnkd.in/d_T5q5Tx
6. React :- https://news.1rj.ru/str/Programming_experts/230
7. Python :- https://news.1rj.ru/str/pythondevelopersindia/99
8. MongoDB :- https://lnkd.in/dBXxCQ43
9. SQL :- https://news.1rj.ru/str/sqlspecialist/222
10. Nodejs :- https://lnkd.in/dwry8BKH
11. Expressjs :- https://lnkd.in/d3BMMwem
12. Django :- https://lnkd.in/dYWQKZnT
13. PHP :- https://quickref.me/php
14. Google Dork :- https://lnkd.in/dKej3-42
15. Linux :- https://lnkd.in/dCgH_qUq
16. Git :- https://lnkd.in/djf9Wc98
17. VSCode :- https://quickref.me/vscode
18. PC Keyboard :- http://bit.ly/3luF73K
19. Data Structures and Algorithms :- https://lnkd.in/d75ijyr3
20. DSA Practice :- https://lnkd.in/dDc6SaR8
21. Data Science :- https://lnkd.in/dHaxPYYA
22. Flask :- https://lnkd.in/dkUyWHqR
23. CCNA :- https://lnkd.in/dE_yD6ny
24. Cloud Computing :- https://lnkd.in/d9vggegr
25. Machine Learning :- https://news.1rj.ru/str/learndataanalysis/29
26. Windows Command :- https://lnkd.in/dAMeCywP
27. Computer Basics :- https://lnkd.in/d9yaNaWN
28. MySQL :- https://lnkd.in/d7iJjSpQ
29. PostgreSQL :- https://lnkd.in/dDHQkk5f
30. MSExcel :- https://bit.ly/3Jz0dpG
31. MSWord :- https://lnkd.in/dAX4FGkR
32. Java :- https://lnkd.in/dRe98iSB
33. Cryptography :- https://lnkd.in/dYvRHAH9
34. C++ :- https://lnkd.in/d4GjE2kd
35. C :- https://lnkd.in/diuHU72d
36. Resume Creation :- https://bit.ly/3JA3KnJ
37. ChatGPT :- https://lnkd.in/dsK37bSj
38. Docker :- https://lnkd.in/dNVJxYNa
39. Gmail :- bit.ly/3JX68pR
40. AngularJS :- bit.ly/3yYY0ik
41. Atom Text Editor :- bit.ly/40oJFY9
42. R Programming :- bit.ly/3Jysq00

Hundreds of free IT certifications to add to your resume

𝟭. 𝗙𝗿𝗲𝗲𝗖𝗼𝗱𝗲𝗖𝗮𝗺𝗽
More than 40,000 people have gotten developer jobs after completing these – including at big companies like Google and Microsoft.
https://freecodecamp.org/learn

𝟮. 𝗗𝗶𝗴𝗶𝘁𝗮𝗹 𝗚𝗮𝗿𝗮𝗴𝗲
Discover a range of free learning content. You can learn by selecting individual modules, or dive right in and take an entire course end-to-end.
https://learndigital.withgoogle.com/digitalgarage/courses?certification=free

𝟯. 𝗞𝗮𝗴𝗴𝗹𝗲
You can gain usable skills in a few hours (instead of weeks or months). The courses are provided at no cost to you, and you can now earn certificates.

https://kaggle.com/learn
𝟰. 𝗖𝗼𝗴𝗻𝗶𝘁𝗶𝘃𝗲 𝗖𝗹𝗮𝘀𝘀
Free courses starting from data science and deep learning to container architectures and Kubernetes.

https://cognitiveclass.ai/group/all

𝟱. 𝗧𝗲𝘀𝘁 𝗔𝘂𝘁𝗼𝗺𝗮𝘁𝗶𝗼𝗻 𝗨𝗻𝗶𝘃𝗲𝗿𝘀𝗶𝘁𝘆
Free test automation courses with videos, trannoscripts, quizzes, credits, rank badges, and certificates.

https://testautomationu.applitools.com

Complete guide to train chatgpt model

16 Websites for Coders 📍

1. HTML & CSS:- htmlcheatsheet.com

2. JavaScript :- https://lnkd.in/dfSvFuhM

3. Jquery - https://lnkd.in/dcvy6kmQ

4. Bootstrap 5:- https://lnkd.in/dNZ6qdBh

5. Tailwind CSS:- https://lnkd.in/d_T5q5Tx

6. React:- https://lnkd.in/de55QGBg 7. Python :- https://lnkd.in/dmZa39rE

8. MongoDB:- https://lnkd.in/dBXXCQ43

9. SQL:- https://lnkd.in/dEFY_jAk

10. Nodejs :- https://lnkd.in/dwry8BKH

11. Expressjs:- https://lnkd.in/d3BMMwem

12. Django :- https://lnkd.in/dYWQKZnT

13. PHP- https://quickref.me/php

14. Google Dork:- https://lnkd.in/dKej3-42

15. Linux:- https://lnkd.in/dCgH_qUq

16. Git:- https://lnkd.in/djf9Wc98

🚀 Microsoft is offering some FREE courses 🚀


1️⃣ AI for beginners
Check this out 👇
http://microsoft.github.io/AI-For-Beginners


2️⃣ IOT
Check this out 👇
https://microsoft.github.io/IoT-For-Beginners


3️⃣ Machine Learning
Check this out👇
http://microsoft.github.io/ML-For-Beginners/#/


4️⃣ Data Science
Check this out👇
http://microsoft.github.io/Data-Science-For-Beginners/#/

Free Coding Courses

https://news.1rj.ru/str/addlist/pU4nqsSMdfdiOTQx

Few more courses ✅

𝟭.𝗗𝗮𝘁𝗮 𝗙𝘂𝗻𝗱𝗮𝗺𝗲𝗻𝘁𝗮𝗹𝘀
https://learn.microsoft.com/en-us/training/paths/azure-data-fundamentals-explore-non-relational-data/

𝟮.𝗦𝗾𝗹 𝗙𝘂𝗻𝗱𝗮𝗺𝗲𝗻𝘁𝗮𝗹𝘀
https://learn.microsoft.com/en-us/training/paths/azure-sql-fundamentals/

𝟯.𝗣𝗼𝘄𝗲𝗿 𝗕𝗜
https://learn.microsoft.com/en-us/training/paths/create-use-analvtics-reports-power-bi/

𝟰.𝗔𝘇𝘂𝗿𝗲 𝗰𝗼𝘀𝗺𝗼𝘀 𝗗𝗕
https://learn.microsoft.com/en-us/training/paths/create-use-analytics-reports-power-bi/

𝟱.𝗔𝗜 𝗳𝘂𝗻𝗱𝗮𝗺𝗲𝗻𝘁𝗮𝗹𝘀
https://learn.microsoft.com/en-us/training/paths/create-no-code-predictive-models-azure-machine-learning/

FREE certification courses from Google:

1. Fundamentals of Digital Marketing
https://learndigital.withgoogle.com/digitalgarage/course/digital-marketing

2. Data Science with Python
https://learndigital.withgoogle.com/digitalunlocked/course/data-science-with-python

3. Learn programming with JavaScript
https://learndigital.withgoogle.com/digitalgarage/course/learn-programming-with-javanoscript

4. Google Cloud Computing Foundations
https://cloudskillsboost.google/course_templates/153

5. Google's Python Class
http://developers.google.com/edu/python

6. Machine Learning Crash Course
https://learndigital.withgoogle.com/digitalunlocked/course/machine-learning-crash-course

7. Introduction to Google Cloud Essentials
http://cloudskillsboost.google/quests/23

8. Introduction to Baseline: Data, ML, AI
http://cloudskillsboost.google/quests/34

FREE RESOURCES TO LEARN PYTHON
👇👇

Free Udacity Course to learn Python

https://imp.i115008.net/5bK93j

Data Structure and OOPS in Python Free Courses

https://bit.ly/3t1WEBt

Free Certified Python course by Freecodecamp

https://www.freecodecamp.org/learn/scientific-computing-with-python/

Free Python Course from Google

https://developers.google.com/edu/python

Free Python Tutorials from Kaggle

https://www.kaggle.com/learn/python

Python hands-on Project

https://news.1rj.ru/str/Programming_experts/23

Free Python Books Collection

https://cfm.ehu.es/ricardo/docs/python/Learning_Python.pdf

https://static.realpython.com/python-basics-sample-chapters.pdf

👨‍💻Websites to Practice Python

1. http://codingbat.com/python
2. https://www.hackerrank.com/
3. https://www.hackerearth.com/practice/
4. https://projecteuler.net/archives
5. http://www.codeabbey.com/index/task_list
6. http://www.pythonchallenge.com/

Beginner's guide to Python Free Book

https://news.1rj.ru/str/pythondevelopersindia/144

Official Documentation

https://docs.python.org/3/

Join @free4unow_backup for more free courses

ENJOY LEARNING 👍👍

Udemy offers a wealth of free courses that can help you develop new skills in 2023. Here are 5 of the best free Udemy courses to get you started:

1. Fun & Easy Introduction to Web Development
https://bit.ly/43DOpL1

2. Foundations of Front-End Web Development
https://bit.ly/43CGqNW

3. Web Development For Freelancers
https://bit.ly/3Y5jTrW

4. Master the Basics of HTML5 & CSS3: Beginner Web Development
https://bit.ly/3Y5jTIs

5. Build a Website in less than 2 Hours! (Step by Step)
https://bit.ly/3rJ5buE

6. Learn JavaScript, Get Hired | The Essentials
https://bit.ly/3rF247c

7. Pure JavaScript Calculator Code ES6 Learn JavaScript
https://bit.ly/3KbPpz0

8. JavaScript HTML CSS Project make a Quiz Tutorial
https://bit.ly/44zg2pR

9. React JS Frontend Web Development for Beginners
https://bit.ly/3K55Tcg

10. Build Tic Tac Toe Game By React.js [Reducer Hook Tutorial]
https://bit.ly/44zg29l

Please share this with your friends who is fighting to find good and free course : )

🦚 Here are this week's five freeCodeCamp resources that are worth your time 🦚


1. TypeScript is a popular version of JavaScript that uses static types. This means that for each variable in your code, you specify whether it's a string, array, integer, or other data type. Why bother with this? Because it will dramatically reduce the number of bugs in your codebase. freeCodeCamp moved to TypeScript a few years ago, and we haven't looked back. If you know some basic JavaScript, you can quickly learn TypeScript and start reaping the benefits. This full-length handbook will teach you how to use React with TypeScript. You can code along at home and build your own type-safe To Do List app. (full-length handbook – 2 hour read): https://www.freecodecamp.org/news/typenoscript-tutorial-for-react-developers/

2. We also published a full-length book on Astro. It's a popular new User Interface framework that a lot of my friends are adopting. Astro is written in TypeScript, and built for speed. This book is structured as a series of projects. You can code along at home and build your own Component Island, then build React apps on top of it. Along the way, you'll get a feel for Server-Side Rendering. (full-length book - 8 hour read): https://www.freecodecamp.org/news/how-to-use-the-astro-ui-framework/

3. Steganography is the art of hiding things in plain sight. It translates to “the study of hidden things” in Greek. You can hide data inside of other data. Then – if you did it right – people will be none the wiser. This tutorial will show you how to use Steganography to hide information in text, images, video, and even network traffic itself. (15 minute read): https://www.freecodecamp.org/news/what-is-steganography-hide-data-inside-data/

4. Deploying an app to the cloud can be a daunting task. Thankfully, we have Infrastructure-as-Code tools that make this process a lot simpler. This DevOps course will teach you how to use Terraform to configure your servers and domains. If you learn how to automate app deployment, you'll save a lot of time and headache down the line. (1 hour YouTube course): https://www.freecodecamp.org/news/how-to-use-terraform-to-deploy-a-site-on-google-cloud-platform

5. Postman is a powerful tool for testing your APIs, and making sure that new feature code doesn't break your existing codebase. This in-depth course will show you how to use Postman to debug your API endpoints, and ultimately automate deployment using Continuous Integration / Continuous Delivery tools. You can code along at home, and do some CI/CD while listening to some AC/DC. (4 hour YouTube course): https://www.freecodecamp.org/news/master-api-testing-with-postman/


━━━━━━━━━━━━━

Top free Data Science resources

@datasciencefun

1. CS109 Data Science
http://cs109.github.io/2015/pages/videos.html

2. Data Science Essentials
https://www.edx.org/course/data-science-essentials

3. Learning From Data from California Institute of Technology
http://work.caltech.edu/telecourse

4. Mathematics for Machine Learning by University of California, Berkeley
https://gwthomas.github.io/docs/math4ml.pdf?fbclid=IwAR2UsBgZW9MRgS3nEo8Zh_ukUFnwtFeQS8Ek3OjGxZtDa7UxTYgIs_9pzSI

5. Foundations of Data Science by Avrim Blum, John Hopcroft, and Ravindran Kannan
https://www.cs.cornell.edu/jeh/book.pdf?fbclid=IwAR19tDrnNh8OxAU1S-tPklL1mqj-51J1EJUHmcHIu2y6yEv5ugrWmySI2WY

6. Python Data Science Handbook
https://jakevdp.github.io/PythonDataScienceHandbook/?fbclid=IwAR34IRk2_zZ0ht7-8w5rz13N6RP54PqjarQw1PTpbMqKnewcwRy0oJ-Q4aM

7. CS 221 ― Artificial Intelligence
https://stanford.edu/~shervine/teaching/cs-221/

8. Ten Lectures and Forty-Two Open Problems in the Mathematics of Data Science
https://ocw.mit.edu/courses/mathematics/18-s096-topics-in-mathematics-of-data-science-fall-2015/lecture-notes/MIT18_S096F15_TenLec.pdf

9. Python for Data Analysis by Boston University
https://www.bu.edu/tech/files/2017/09/Python-for-Data-Analysis.pptx

10. Data Mining bu University of Buffalo
https://cedar.buffalo.edu/~srihari/CSE626/index.html?fbclid=IwAR3XZ50uSZAb3u5BP1Qz68x13_xNEH8EdEBQC9tmGEp1BoxLNpZuBCtfMSE

Share the channel link with friends
http://t.me/datasciencefun

Some useful PYTHON libraries for data science

NumPy stands for Numerical Python. The most powerful feature of NumPy is n-dimensional array. This library also contains basic linear algebra functions, Fourier transforms,  advanced random number capabilities and tools for integration with other low level languages like Fortran, C and C++

SciPy stands for Scientific Python. SciPy is built on NumPy. It is one of the most useful library for variety of high level science and engineering modules like discrete Fourier transform, Linear Algebra, Optimization and Sparse matrices.

Matplotlib for plotting vast variety of graphs, starting from histograms to line plots to heat plots.. You can use Pylab feature in ipython notebook (ipython notebook –pylab = inline) to use these plotting features inline. If you ignore the inline option, then pylab converts ipython environment to an environment, very similar to Matlab. You can also use Latex commands to add math to your plot.

Pandas for structured data operations and manipulations. It is extensively used for data munging and preparation. Pandas were added relatively recently to Python and have been instrumental in boosting Python’s usage in data scientist community.

Scikit Learn for machine learning. Built on NumPy, SciPy and matplotlib, this library contains a lot of efficient tools for machine learning and statistical modeling including classification, regression, clustering and dimensionality reduction.

Statsmodels for statistical modeling. Statsmodels is a Python module that allows users to explore data, estimate statistical models, and perform statistical tests. An extensive list of denoscriptive statistics, statistical tests, plotting functions, and result statistics are available for different types of data and each estimator.

Seaborn for statistical data visualization. Seaborn is a library for making attractive and informative statistical graphics in Python. It is based on matplotlib. Seaborn aims to make visualization a central part of exploring and understanding data.

Bokeh for creating interactive plots, dashboards and data applications on modern web-browsers. It empowers the user to generate elegant and concise graphics in the style of D3.js. Moreover, it has the capability of high-performance interactivity over very large or streaming datasets.

Blaze for extending the capability of Numpy and Pandas to distributed and streaming datasets. It can be used to access data from a multitude of sources including Bcolz, MongoDB, SQLAlchemy, Apache Spark, PyTables, etc. Together with Bokeh, Blaze can act as a very powerful tool for creating effective visualizations and dashboards on huge chunks of data.

Scrapy for web crawling. It is a very useful framework for getting specific patterns of data. It has the capability to start at a website home url and then dig through web-pages within the website to gather information.

SymPy for symbolic computation. It has wide-ranging capabilities from basic symbolic arithmetic to calculus, algebra, discrete mathematics and quantum physics. Another useful feature is the capability of formatting the result of the computations as LaTeX code.

Requests for accessing the web. It works similar to the the standard python library urllib2 but is much easier to code. You will find subtle differences with urllib2 but for beginners, Requests might be more convenient.

Additional libraries, you might need:

os for Operating system and file operations

networkx and igraph for graph based data manipulations

regular expressions for finding patterns in text data

BeautifulSoup for scrapping web. It is inferior to Scrapy as it will extract information from just a single webpage in a run.

Frontend web development:

https://www.w3schools.com/html

https://www.w3schools.com/css

https://www.jschallenger.com

https://javanoscript30.com

https://news.1rj.ru/str/webdevcoursefree/110

https://news.1rj.ru/str/Programming_experts/107

Backend development:

https://learnpython.org/

https://news.1rj.ru/str/pythondevelopersindia/314

https://www.geeksforgeeks.org/java/

https://introcs.cs.princeton.edu/java/11cheatsheet/

https://docs.microsoft.com/en-us/shows/beginners-series-to-nodejs/?languages=nodejs

Database:

https://mode.com/sql-tutorial/introduction-to-sql

https://www.sqltutorial.org/wp-content/uploads/2016/04/SQL-cheat-sheet.pdf

https://books.goalkicker.com/MySQLBook/MySQLNotesForProfessionals.pdf

https://docs.oracle.com/cd/B19306_01/server.102/b14200.pdf

https://leetcode.com/problemset/database/

Cloud Computing:

https://bit.ly/3aoxt1N

https://news.1rj.ru/str/free4unow_backup/366

UI/UX:

https://www.freecodecamp.org/learn/responsive-web-design/

https://bit.ly/3r6F9xE

ENJOY LEARNING 👍👍

🚨 6 free online courses by Harvard University, in ML, AI, and Data Science.

𝐈𝐧𝐭𝐫𝐨𝐝𝐮𝐜𝐭𝐢𝐨𝐧 𝐭𝐨 𝐀𝐫𝐭𝐢𝐟𝐢𝐜𝐢𝐚𝐥 𝐈𝐧𝐭𝐞𝐥𝐥𝐢𝐠𝐞𝐧𝐜𝐞 𝐰𝐢𝐭𝐡 𝐏𝐲𝐭𝐡𝐨𝐧
🔗 Link

𝐃𝐚𝐭𝐚 𝐒𝐜𝐢𝐞𝐧𝐜𝐞: 𝐌𝐚𝐜𝐡𝐢𝐧𝐞 𝐋𝐞𝐚𝐫𝐧𝐢𝐧𝐠
🔗 Link

𝐇𝐢𝐠𝐡-𝐝𝐢𝐦𝐞𝐧𝐬𝐢𝐨𝐧𝐚𝐥 𝐝𝐚𝐭𝐚 𝐚𝐧𝐚𝐥𝐲𝐬𝐢𝐬
🔗 Link

𝐒𝐭𝐚𝐭𝐢𝐬𝐭𝐢𝐜𝐬 𝐚𝐧𝐝 𝐑
🔗 Link

𝐂𝐨𝐦𝐩𝐮𝐭𝐞𝐫 𝐒𝐜𝐢𝐞𝐧𝐜𝐞 𝐟𝐨𝐫 𝐁𝐮𝐬𝐢𝐧𝐞𝐬𝐬 𝐏𝐫𝐨𝐟𝐞𝐬𝐬𝐢𝐨𝐧𝐚𝐥𝐬
🔗 Link

𝐈𝐧𝐭𝐫𝐨𝐝𝐮𝐜𝐭𝐢𝐨𝐧 𝐭𝐨 𝐏𝐫𝐨𝐠𝐫𝐚𝐦𝐦𝐢𝐧𝐠 𝐰𝐢𝐭𝐡 𝐏𝐲𝐭𝐡𝐨𝐧
🔗 Link

AI is transforming the way we work and live.

📍6 AI tools that will 10X your Productivity:

Check out the list now:

01) Create Resume – Kickresume - https://bit.ly/44rqSOA

02) Solves anything -Chat GPT - https://lnkd.in/drxqDJmF

03) Writes anything- Writesonic (writesonic.com)

04) Generates Art – Midjourney - www.midjourney.com

05) Generates Code – Replit - https://replit.com/ai

06) Generates Video-Synthesia - https://lnkd.in/dPmA6-ee

More here - https://news.1rj.ru/str/free4unow_backup/596

Thank you so much for reading!!

Free AI Course from Google: https://ai.google/education/

Free Python IBM course with Certificate: https://cognitiveclass.ai/courses/python-for-data-science

🍓 Python Certifications to boost your resume in 2023 🍓

𝟭. 𝗜𝗻𝘁𝗿𝗼 𝘁𝗼 𝗣𝘆𝘁𝗵𝗼𝗻
This a great course to get started with learning Python, if you have no coding experience.
👉 https://kaggle.com/learn/intro-to-programming

𝟮. 𝗣𝘆𝘁𝗵𝗼𝗻 𝗣𝗿𝗼𝗴𝗿𝗮𝗺𝗺𝗶𝗻𝗴 𝗰𝗼𝘂𝗿𝘀𝗲
Learn the fundamentals like functions, loops, conditional statements, etc of the most important language for data science.
👉 https://kaggle.com/learn/python

𝟯. 𝗣𝗿𝗼𝗴𝗿𝗮𝗺𝗺𝗶𝗻𝗴 𝗘𝘀𝘀𝗲𝗻𝘁𝗶𝗮𝗹𝘀 𝗶𝗻 𝗣𝘆𝘁𝗵𝗼𝗻
Part 1 prepares you for PCEP – Certified Entry-Level Python Programmer Certification.
Part 2 prepares you for PCAP – Certified Associate in Python Programming Certification.
👉 https://netacad.com/courses/programming/pcap-programming-essentials-python

𝟰. Python Data Structure and Algorithms
👉 https://news.1rj.ru/str/programming_guide/76

𝟱. 𝗦𝗰𝗶𝗲𝗻𝘁𝗶𝗳𝗶𝗰 𝗖𝗼𝗺𝗽𝘂𝘁𝗶𝗻𝗴 𝘄𝗶𝘁𝗵 𝗣𝘆𝘁𝗵𝗼𝗻
You'll learn Python fundamentals like variables, loops, conditionals, and functions.
Then you'll quickly ramp up to complex data structures, networking, relational databases, and data visualization.
👉 https://freecodecamp.org/learn/scientific-computing-with-python/