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https://github.com/zelalemgetahun9374/Awesome-AI-resources

Different kinds of resources useful for learning artificial intelligence including maths and statistics.
https://github.com/zelalemgetahun9374/Awesome-AI-resources

List: Awesome-AI-resources

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Different kinds of resources useful for learning artificial intelligence including maths and statistics.

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# Awesome-Free-AI-resources
Different kinds of resources for learning and practicing artificial intelligence.

## Mathematics, Statistics and Probability
* [Mathematics Stack Exchange](https://math.stackexchange.com/)
* [MathOverflow](https://mathoverflow.net/)
* [Paul's Online Math Notes](https://tutorial.math.lamar.edu/)
* [Khan Academy](https://www.khanacademy.org/)
* [TutorialsPoint - Statistics Tutorial](https://www.tutorialspoint.com/statistics/index.htm)
* [Seeing Theory - A visual introduction to probability and statistics](https://seeing-theory.brown.edu/index.html#firstPage)
* [Mathsisfun | Data, Probability and Statistics](https://www.mathsisfun.com/data/)
* [Statistics Course for Data Science | Statistics Course for Data Analytics | MarinStatsLectures](https://www.youtube.com/playlist?list=PLqzoL9-eJTNBZDG8jaNuhap1C9q6VHyVa)
* [Electronic Textbooks](https://faculty.atu.edu/mfinan/nnotes.html)
* [Wikibooks: Mahematics online bookshelf](https://en.wikibooks.org/wiki/Wikibooks:Mathematics_bookshelf)
* [Online Mathematics Textbooks](https://people.math.gatech.edu/~cain/textbooks/onlinebooks.html)
* [Probability and statistics EBook](http://wiki.stat.ucla.edu/socr/index.php/Probability_and_statistics_EBook)
* [Articles about Statistics](https://www.scribbr.com/category/statistics/)

## AI Courses and Learning Sites
* [10 Academy's Self Learning Resources](https://github.com/10-Academy-Self-Learning-Resources)
* [Jovian AI - Learn Data Science](https://jovian.ai/learn)
* [Machine Learning Mastery](https://machinelearningmastery.com/)
* [Open Machine Learning Course mlcourse.ai](https://mlcourse.ai/)
* [deeplearning.ai](https://www.deeplearning.ai/)
* [Dive Into Deep Learning: D2L by Amazon scientists](https://d2l.ai/index.html)
* [Full Stack Deep Learning](https://fullstackdeeplearning.com/)
* [Intel AI courses](https://software.intel.com/content/www/us/en/develop/topics/ai/training/courses.html)
* [Machine Learning Course - The Clever Programmer](https://thecleverprogrammer.com/2020/09/24/machine-learning-course/)
* [21-Days-Of-Machine-Learning](https://github.com/ArunSolomon/21-Days-Of-Machine-Learning)
* [Fast.ai - Practical Deep Learning For Coders](https://course18.fast.ai/)
* [Kaggle courses](https://www.kaggle.com/learn/overview)
* [W3Schools - Data Science Tutorial](https://www.w3schools.com/datascience/default.asp)
* [TutorialsPoint - Python Data Science Tutorial](https://www.tutorialspoint.com/python_data_science/index.htm)
* [TensorFlow Tutorials and Guides](https://www.tensorflow.org/overview)
* [Machine Learning Tutorial Python | Machine Learning For Beginners](https://www.youtube.com/playlist?list=PLeo1K3hjS3uvCeTYTeyfe0-rN5r8zn9rw)
* [Deep Learning With Tensorflow 2.0, Keras and Python](https://www.youtube.com/playlist?list=PLeo1K3hjS3uu7CxAacxVndI4bE_o3BDtO)
* [Korbit AI - Data Science Learning using AI tutor](https://www.korbit.ai/for-individuals)
* [CoderzColumn | Python, Data Science, Ml ,AI Tutorials](https://coderzcolumn.com/)
* [Learn Data Science Online | DPhi](https://dphi.tech/learn/)
* [Cognitiveclass.ai](https://cognitiveclass.ai/)
* [IBM Data Science Professional Certificate](https://www.coursera.org/professional-certificates/ibm-data-science)
* [IBM AI Engineering Professional Certificate](https://www.coursera.org/professional-certificates/ai-engineer)
* [MIT Introduction to Machine Learning](https://openlearninglibrary.mit.edu/courses/course-v1:MITx+6.036+1T2019/about)
* [Machine Learning by Georgia Tech](https://www.udacity.com/course/machine-learning--ud262)

## Data Analysis and visualization courses

* [Kaggle notebooks - search for and library, tool or topic](https://www.kaggle.com/code)
* [D3 js - Data Driven Documents](https://d3js.org/)
* [CoderzColumn | Data Science Tutorials](https://coderzcolumn.com/tutorials/data-science/)
* [Awesome machine learning - github repository for resources link](https://github.com/josephmisiti/awesome-machine-learning)
* [Python Bootcamp 2021 Build 15 working Applications and Games - contains numpy, pandas, matplotlib, seaborn, plotly, cufflinks and folium](https://www.udemy.com/course/python-complete-bootcamp-2019-learn-by-applying-knowledge/)

## Database Courses
* [khanacademy SQL course](https://www.khanacademy.org/computing/computer-programming/sql)
* [Introduction to MongoDB](https://www.coursera.org/learn/introduction-mongodb)
* [SQLBolt - Learn SQL with simple, interactive exercises](https://sqlbolt.com/)

## Jupiter Notebooks
* [Kaggle Notebooks](https://www.kaggle.com/notebooks)
* [Awesome Cheatsheets for Data Science](https://www.kaggle.com/joydeb28/awesome-data-science-cheatsheet#Big-Data)
* [IBM OpenDS4All](https://github.com/odpi/OpenDS4All/tree/master/opends4all-resources)
* [The Super Duper NLP Repo - over 300 NLP Notebooks](https://notebooks.quantumstat.com/)
* [IPython Interactive Computing and Visualization Cookbook Jupiter Notebooks](https://github.com/ipython-books/cookbook-2nd-code)

## Projects and Challenges
* [HackeRank](https://www.hackerrank.com/)
* [JetBrains Academy](https://hyperskill.org/onboarding)
* [Exercism - Code practice and mentorship for everyone](https://exercism.io/)
* [Omdena - Build real-world collaborative AI projects](https://omdena.com/projects/)
* [DeZyre - Data Science and Machine Learning code recipes](https://www.dezyre.com/)
* [8 AI/Machine Learning Projects To Make Your Portfolio Stand Out](https://www.kdnuggets.com/2020/09/8-ml-ai-projects-stand-out.html)
* [EliteDataScience's Machine Learning Masterclass course projects from 2017 class](https://github.com/jfrank94/Machine-Learning-Masterclass)
* [EliteDataScience's Machine Learning Masterclass course projects search n gthub](https://github.com/search?o=desc&q=EliteDataScience&s=updated&type=Repositories)
* [130 projects in Machine learning (with solution and explanation)](https://medium.com/the-innovation/130-machine-learning-projects-solved-and-explained-605d188fb392)
* [180 Data Science and Machine Learning Projects with Python](https://medium.com/coders-camp/180-data-science-and-machine-learning-projects-with-python-6191bc7b9db9)
* [500 + Artificial Intelligence Project List with code](https://github.com/ashishpatel26/500-AI-Machine-learning-Deep-learning-Computer-vision-NLP-Projects-with-code)
* [Google AI Experiments](https://experiments.withgoogle.com/collection/ai)
* [6 Exciting Open Source Data Science Projects you Should Start Working on Today](https://www.analyticsvidhya.com/blog/2019/11/6-open-source-data-science-projects/)
* [8 Fun Machine Learning Projects for Beginners](https://elitedatascience.com/machine-learning-projects-for-beginners)
* [Top 7 Data science projects to put on your resume-2020](https://technologynous.com/top-7-data-science-projects-to-put-on-your-resume-2020/?fbclid=IwAR3v4RVKiNsswXcvDo4K31KS8VLaXJAbemMvre8BM3cxChJc_QWz_cUcPPk)
* [Top 47 Machine Learning Projects for 2021 [Source Code Included]](https://data-flair.training/blogs/machine-learning-project-ideas/)

## Competitions
* [Kaggle Competitions](https://www.kaggle.com/competitions)

## Internship, Fellowship and Jobs
* [Entry Level AI](https://www.entrylevel.ai/)
* [Internshala](https://internshala.com/)
* [Fellowship.ai](https://www.fellowship.ai/)
* [Forage Virtual Internships](https://www.theforage.com)
* [Practicum Digital Virtual Internships](https://sites.google.com/view/practicum-digital/welcome)
* [Google Internships+](https://buildyourfuture.withgoogle.com/internships/)
* [Work At A Startup Internships](https://www.workatastartup.com/internships)
* [Indeed](https://www.indeed.com/)

## Miscellaneous
* [10 Academy](https://github.com/10-Academy-Self-Learning-Resources)
* [Open Data Science](https://ods.ai/)
* [freeCodeCamp](https://www.freecodecamp.org/)
* [Google AI](https://ai.google/)
* [fast.ai](https://www.fast.ai/)
* [Workera - Personalized Data-AI Skills Transformation](https://workera.ai/)
* [KDnuggets - Machine Learning, Data Science, Big Data, Analytics](https://www.kdnuggets.com/)
* [The Ultimate guide to AI, Data Science & Machine Learning, Articles, Cheatsheets and Tutorials ALL in one place](https://www.linkedin.com/pulse/all-cheatsheets-one-place-vipul-patel/)
* [Data Science and Machine Learning Cheat Sheets and Projects 2021](https://www.theinsaneapp.com/)
* [Cheatography - Over 4,000 Free Cheat Sheets, Revision Aids and Quick References!](https://cheatography.com/)
* [Machine Learning Cheat Sheets - Stanford](https://stanford.edu/~shervine/teaching/cs-229/cheatsheet-supervised-learning)
* [Polo Club of Data Science - scalable, interactive, and interpretable tools that amplify human's ability to understand and interact with billion-scale data and machine learning models](https://poloclub.github.io/)
* [65+ Free Data Science Resources for Beginners](https://elitedatascience.com/data-science-resources#foundational-skills)
* [Library of computer science, maths, statistics, probability, artificial intelligence, ...](https://onedrive.live.com/?authkey=%21AC8oQ_EKSvCcCD4&id=82A2F2C10CA0D8F8%2130002&cid=82A2F2C10CA0D8F8)
* [Python, Data Analysis and Software Engineering courses](https://milliams.com/courses/#courses)
* [Python Programming Tutorials by Tech With Tim](https://www.techwithtim.net/)
* [Free google cloud courses](https://go.qwiklabs.com/qwiklabs-free)
* [Ace your data science interview](https://datascienceprep.com/?utm_source=share&utm_medium=link&utm_campaign=friend_referral)

## Github Repositories
* [10 Academy's Self Learning Resources](https://github.com/10-Academy-Self-Learning-Resources)
* [Learn Datascience for Free](https://github.com/therealsreehari/Learn-Datascience-for-Free)
* [Getting Started with Machine Learning](https://gettingstarted.ml/)
* [Free AI resources](https://github.com/mrsaeeddev/free-ai-resources)
* [The incredible PyTorch - Pytorch tutorials, projects, libraries, videos, papers, books](https://github.com/ritchieng/the-incredible-pytorch)
* [Hitchhiker's Guide to Data Science for Social Good](https://github.com/dssg/hitchhikers-guide)
* [Build-your-own-x](https://github.com/danistefanovic/build-your-own-x#build-your-own-programming-language)

## Articles and Blogs
* [Bird's Eye View of The Machine Learning Workflow - Elite Data Science](https://elitedatascience.com/birds-eye-view)
* [AI Expert Roadmap](https://i.am.ai/roadmap/#introduction)
* [The Artificial Intelligence Wiki](https://wiki.pathmind.com/)
* [DATA SCIENCE PIPELINE BASICS](https://medium.com/@shubhammadke96/data-science-pipeline-basics-da4eff6bdd47)
* [The mostly complete chart of Neural Networks, explained](https://towardsdatascience.com/the-mostly-complete-chart-of-neural-networks-explained-3fb6f2367464)
* [CNN Explainer - Learn Convolutional Neural Network (CNN) in your browser!](https://poloclub.github.io/cnn-explainer/)
* [GAN Lab - Play with Generative Adversarial Networks (GANs) in your browser!](https://poloclub.github.io/ganlab/)
* [A step-by-step guide for creating an authentic data science portfolio project](https://www.kdnuggets.com/2020/10/guide-authentic-data-science-portfolio-project.html)
* [Beginners Learning Path for Machine Learning](https://www.kdnuggets.com/2020/05/beginners-learning-path-machine-learning.html)
* [10 Free Data Visualization Tools](https://www.pcmag.com/news/10-free-data-visualization-tools)
* [Easy step-by-step Tensorflow Tutorials](https://www.easy-tensorflow.com/)
* [A beginner's guide to web scraping with Python](https://opensource.com/article/20/5/web-scraping-python)
* [Visual Explanation of Backpropagation Algorithm](https://developers-dot-devsite-v2-prod.appspot.com/machine-learning/crash-course/backprop-scroll)
* [Configuring Google Colab Like A Pro](https://medium.com/@robertbracco1/configuring-google-colab-like-a-pro-d61c253f7573#a642)
* [How to Build a Stunning Interactive Dashboard within 10 Minutes using Google Data Studio](https://towardsdatascience.com/how-to-build-a-great-dashboard-ee0518c3d3f7)
* [10 Python Data Visualization Libraries for Any Field | Mode](https://mode.com/blog/python-data-visualization-libraries/#Bokeh)
* [TensorFlow Beginners Tutorial](https://datascience-enthusiast.com/DL/Tensorflow_Tutorial.html#TensorFlow-Tutorial)
* [Kavita’s Articles about text mining, text classification, NLP, neural embeddings and related issues](https://kavita-ganesan.com/kavitas-tutorials/#.X-CkSyP47IW)

## AI Applications
* [Avatarify AI Photorealistic Avatars in Realtime](https://avatarify.ai/)

## Free AI Data Science Tools
* [Google Data Studio - a data visualization tool to generate interactive dashboard](https://datastudio.google.com)
* [Tableau for Students one year free](https://www.tableau.com/academic/students)

## AI communtiy
* [Kaggle Community](https://www.kaggle.com/discussion)

## Youtube Channels
* [10Academy](https://www.youtube.com/channel/UCDwr854iwfpjDk1ESK5ofvQ/videos)
* [My CS](https://www.youtube.com/c/MyCS1/videos)
* [3Blue1Brown - Math, Probability, Neural networks explained easily](https://www.youtube.com/c/3blue1brown/playlists)
* [Data Professor](https://www.youtube.com/c/DataProfessor/playlists)
* [Krish Naik](https://www.youtube.com/user/krishnaik06/playlists)
* [Ken Jee](https://www.youtube.com/c/KenJee1/playlists)
* [Python Engineer - Python and Machine Learning Tutorials](https://www.youtube.com/c/PythonEngineer/playlists)
* [statslectures](https://www.youtube.com/user/statslectures/playlists)
* [Tech With Tim](https://www.youtube.com/c/TechWithTim/playlists)
* [codebasics - Data analysis and machine learning projects (End to End)](https://www.youtube.com/c/codebasics/playlists)
* [StatQuest with Josh Starmer](https://www.youtube.com/c/joshstarmer/playlists)