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

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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

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

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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.
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Part 1 prepares you for PCEP – Certified Entry-Level Python Programmer Certification.
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You'll learn Python fundamentals like variables, loops, conditionals, and functions.
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Free Resources to learn Ethical Hacking and Cyber Security
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Free Cyber Security course from Udacity

http://imp.i115008.net/7mJmZ3

Fundamentals of Computer Hacking

https://www.udemy.com/course/computer-hacking-fundamentals/

Ethical Hacking - SQL Injection Attack

https://www.udemy.com/course/sql-injection-ethical-hacking/

Cyber Security for Beginners Free Book

https://heimdalsecurity.com/pdf/cyber_security_for_beginners_ebook.pdf

Information Security Free Certified Course

https://www.freecodecamp.org/learn/information-security/

Complete Ethical Hacking Bootcamp 2021: Zero to Mastery

https://news.1rj.ru/str/ethicalhackingtoday/3

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FREE RESOURCES TO LEARN MACHINE LEARNING
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Intro to ML by MIT Free Course

https://openlearninglibrary.mit.edu/courses/course-v1:MITx+6.036+1T2019/about

Machine Learning for Everyone FREE BOOK

https://buildmedia.readthedocs.org/media/pdf/pymbook/latest/pymbook.pdf

ML Crash Course by Google

https://developers.google.com/machine-learning/crash-course

Advanced Machine Learning with Python Github

https://github.com/PacktPublishing/Advanced-Machine-Learning-with-Python

Practical Machine Learning Tools and Techniques Free Book

https://vk.com/doc10903696_437487078?hash=674d2f82c486ac525b&dl=ed6dd98cd9d60a642b

Python Machine Learning for beginners

https://news.1rj.ru/str/datasciencefun/1177

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🖥 Roadmap of free courses for learning Python and Machine learning.

▪Data Science
▪ AI/ML
▪ Web Dev

1. Start with this
https://kaggle.com/learn/python

2. Take any one of these

❯ https://openclassrooms.com/courses/6900856-learn-programming-with-python

❯ https://scaler.com/topics/course/python-for-beginners/

❯ https://simplilearn.com/learn-python-basics-free-course-skillup

3. Then take this
https://netacad.com/courses/programming/pcap-programming-essentials-python

4. Attempt for this certification
https://freecodecamp.org/learn/scientific-computing-with-python/

5. Take it to next level

❯ Data Scrapping, NumPy, Pandas
https://scaler.com/topics/course/python-for-data-science/

❯ Data Analysis
https://openclassrooms.com/courses/2304731-learn-python-basics-for-data-analysis

❯ Data Visualization
https://kaggle.com/learn/data-visualization

❯ Django
https://openclassrooms.com/courses/6967196-create-a-web-application-with-django

❯ Machine Learning
http://developers.google.com/machine-learning/crash-course

❯ Deep Learning (TensorFlow)
http://kaggle.com/learn/intro-to-deep-learning

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🔸Python https://cs50.harvard.edu/python/

🔸JavaScript https://hackerrank.com/skills-verification/javanoscript_intermediate

🔸DevOps https://mylearn.oracle.com/ou/learning-path/become-an-oci-devops-professional-2023/121756

🔸Machine Learning https://freecodecamp.org/learn/machine-learning-with-python/

🔸Java https://data-flair.training/courses/free-java-course/

🔸C++ http://learn.saylor.org/course/view.php?id=65

🔸Go https://hackerrank.com/skills-verification/golang_intermediate

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🔸Redis Certified Developer https://university.redis.com/certification/

🔸MongoDB https://learn.mongodb.com/learning-paths/mongodb-for-sql-professionals

🔸Backend Development https://freecodecamp.org/learn/back-end-development-and-apis/

🔸SQL https://hackerrank.com/skills-verification/sql_advanced

🔸C# https://freecodecamp.org/learn/foundational-c-sharp-with-microsoft/

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7⃣ Free Certification Courses from Microsoft to try in 2023:

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FREE RESOURCES TO LEARN PYTHON
👇👇

Free Udacity Course to learn Python

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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/

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5 FREE Courses by Harvard for Beginners 🔥🔥

Understanding Technology
https://pll.harvard.edu/course/cs50s-understanding-technology-0

Computer Science
https://pll.harvard.edu/course/cs50-introduction-computer-science

Programming Basics
https://pll.harvard.edu/course/cs50s-introduction-programming-scratch

Python
https://edx.org/course/cs50s-introduction-to-programming-with-python

Web Development
https://pll.harvard.edu/course/cs50s-web-programming-python-and-javanoscript

🕸 Learn Computer Science in 2023 from Harvard, Stanford, MIT, IBM, Microsoft, Google & other free resources 🕸

[Part - 2]

❯ Machine Learning
http://developers.google.com/machine-learning/crash-course

t.me/datasciencefun/1304

❯ Deep Learning
introtodeeplearning.com

t.me/machinelearning_deeplearning/4

❯ Full Stack Web (HTML/CSS)
pll.harvard.edu/course/cs50s-web-programming-python-and-javanoscript/2023-05

❯ OS, Networking
ocw.mit.edu/courses/6-033-computer-system-engineering-spring-2018/

❯ Compiler Design
online.stanford.edu/courses/soe-ycscs1-compilers

Complete Roadmap with Free Resources to become a data analyst
👇👇
https://www.linkedin.com/posts/sql-analysts_dataanalysts-sql-python-activity-7111579206714572800-Hbmw?utm_source=share&utm_medium=member_android

Free Books:

C Programming
https://books.goalkicker.com/CBook/

Linux
https://books.goalkicker.com/LinuxBook/

Algorithms Book
https://books.goalkicker.com/AlgorithmsBook/

Android Notes
https://books.goalkicker.com/AndroidBook/

C#
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Free Certificates to become a data analyst
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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

https://docs.python.org/3/faq/gui.html

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