FREE Artificial Intelligence Resources - Penetration Testing Tools, ML and Linux Tutorials

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FREE AI Resources – Courses, Jobs, Blogs, AI Research, and many more for everyone!

WHAT IS AI?

Artificial Intelligence (AI) refers to the simulation of human intelligence in machines that are programmed to think like humans and mimic their actions. The term may also be applied to any machine that exhibits traits associated with a human mind such as learning and problem-solving.

WHY CHOOSE AI?

Artificial Intelligence is advancing by leaps and bounds. Recent research in the fields of Data Science, Machine Learning, Natural Language Processing and other sub fields of AI has already started to impact the lives of common people. AI is no more a superficial concept. It’s already used by tech giants, companies and startups to solve everyday problems. That’s why choosing AI as a career path is really rewarding in the long run.

Even if your profession is not directly related to tech, still it’s said that AI will disrupt every field in one or other ways. That’s why you need to have at least a basic understanding of how AI works.

FREE AI COURSES:

EdX’s Artificial Intelligence – https://www.edx.org/course/artificial-intelligence-ai
Udacity’s Intro to Artificial Intelligence – https://www.udacity.com/course/intro-to-artificial-intelligence–cs271
Artificial Intelligence: Principles and Techniques By Stanford – http://web.stanford.edu/class/cs221/
Udacity’s Artificial Intelligence for Robotics by Georgia Tech – https://www.udacity.com/course/artificial-intelligence-for-robotics–cs373
IBM’s Data Science and Cognitive Computing courses – https://cognitiveclass.ai/
Elements of AI – https://www.elementsofai.com/
Building AI – https://buildingai.elementsofai.com/
Intellipaat’s Artificial Intelligence – https://intellipaat.com/academy/course/artificial-intelligence-free-course/
EdX/Harvard University’s CS50: Introduction to Artificial Intelligence with Python – https://www.edx.org/course/cs50s-introduction-to-artificial-intelligence-with-python
Microsoft AI School – https://aischool.microsoft.com/en-us/home
Learn with Google AI – https://ai.google/education/
Crash Course – Artificial Intelligence https://www.youtube.com/watch?v=GvYYFloV0aA&list=PL8dPuuaLjXtO65LeD2p4_Sb5XQ51par_b

FREE MATHEMATICS RESOURCES:

Misc

academicearth.org – http://www.academicearth.org/subjects/mathematics
Encyclopedia of Mathematics – http://www.encyclopediaofmath.org/
Large List of Recommended books, online resources – http://hbpms.blogspot.com/
Online Encyclopedia of Integer Sequences – http://www.research.att.com/~njas/sequences/
MathIM – http://www.mathim.com/
Free Book on Neural Network and Deep Learning – http://neuralnetworksanddeeplearning.com/
Informational website on artificial intelligence – https://intelligencereborn.com

Other Lists of resources

Math Overflow’s List of Free Online Lectures – http://mathoverflow.net/questions/54430/video-lectures-of-mathematics-courses-available-online-for-free
Top-down Learning Path on Machine Learning for Software Engineers – https://github.com/ZuzooVn/machine-learning-for-software-engineers
Fun Learning Projects on Machine Learning for Beginners – https://elitedatascience.com/machine-learning-projects-for-beginners

FREE MACHINE LEARNING COURSES:

Machine Learning by Andrew NG – https://www.coursera.org/learn/machine-learning
Intro to ML by Udacity – https://www.udacity.com/course/intro-to-machine-learning–ud120
EdX’s Learning from Data(Introductory Machine Learning) – https://www.edx.org/course/learning-from-data-introductory-machine-learning#!
Introduction to Machine Learning for Coders – http://course18.fast.ai/ml
Statistical Machine Learning by CMU – https://www.youtube.com/watch?list=PLTB9VQq8WiaCBK2XrtYn5t9uuPdsNm7YE&v=zcMnu-3wkWo
Coursera’s Neural Networks for Machine Learning – https://www.youtube.com/watch?list=PLoRl3Ht4JOcdU872GhiYWf6jwrk_SNhz9&v=cbeTc-Urqak
Kaggle Complete Roadmap for Machine Learning – https://www.kaggle.com/learn/overview
EdX’s Principles of Machine Learning – https://www.edx.org/course/principles-of-machine-learning
Coursera’s Machine Learning Specialization – https://www.coursera.org/specializations/machine-learning
Machine Learning Crash Course by Google – https://developers.google.com/machine-learning/crash-course
Machine Learning Course at W3Schools – https://www.w3schools.com/python/python_ml_getting_started.asp
Intro to Machine Learning Course at Kaggle – https://www.kaggle.com/learn/intro-to-machine-learning
Intermediate Machine Learning Course at Kaggle – https://www.kaggle.com/learn/intermediate-machine-learning
Machine Learning with Python – https://cognitiveclass.ai/courses/machine-learning-with-python

FREE DATA SCIENCE COURSES:

IBM Data Science Professional Certificate – https://www.coursera.org/professional-certificates/ibm-data-science
Udacity Intro to Data Science – https://www.udacity.com/course/intro-to-data-science–ud359
Introduction to Data Science in Python – https://www.coursera.org/learn/python-data-analysis
Introduction to Data Science Revised – https://alison.com/course/introduction-to-data-science-revised
A Crash Course in Data Science – https://www.coursera.org/learn/data-science-course

FREE DEEP LEARNING COURSES:

Google’s Deep Learning Course- https://www.udacity.com/course/intro-to-tensorflow-for-deep-learning–ud187
Practical Deep Learning for Coders – https://course.fast.ai/
Deep Learning from the Foundations – https://course.fast.ai/part2
Intro to Deep Learning using Tensorflow and Keras Course at Kaggle – https://www.kaggle.com/learn/intro-to-deep-learning
Free Book on Neural Network and Deep Learning – http://neuralnetworksanddeeplearning.com/

FREE NLP COURSES:

A Code-First Introduction to Natural Language Processing – https://www.fast.ai/2019/07/08/fastai-nlp/
Natural Language Processing Specialization by Deeplearning.ai – https://www.coursera.org/specializations/natural-language-processing
Natural Language Processing Course at Kaggle – https://www.kaggle.com/learn/natural-language-processing

FREE MACHINE LEARNING IN GRAPHICS AND VISION COURSES:

CVPR 2020: Neural Rendering – https://www.neuralrender.com/

DATA SCIENCE COMPETITION HOSTING PLATFORMS:

Kaggle – https://www.kaggle.com/
Analytics Vidhya – https://www.analyticsvidhya.com/
CrowdANALYTIX – https://www.crowdanalytix.com/community
Innocentive – https://www.innocentive.com/our-solvers/
CodaLab – https://competitions.codalab.org/
ZINDI – https://zindi.africa/about
AIcrowd – https://www.aicrowd.com/
Driven Data – https://www.drivendata.org/
Numerai – https://numer.ai/
Tianchi – https://tianchi.aliyun.com/competition/gameList/activeList
Omdena – https://omdena.com/
HackerEarth –https://www.hackerearth.com/hackathon/explore/field/machine-learning/

DATASET REPOSITORIES:

Data World – https://data.world/datasets/open-data
Dataset Search by Google – https://datasetsearch.research.google.com/
Kaggle Dataset – https://www.kaggle.com/datasets
UCI Machine Learning Repository – https://archive.ics.uci.edu/
Microsoft Open datasets – https://azure.microsoft.com/en-us/services/open-datasets/catalog/
UCR – http://timeseriesclassification.com/
Tensorflow Datasets – https://www.tensorflow.org/datasets/catalog/overview
Quandl – https://www.quandl.com/

AI RESEARCH AT BIG COMPANIES:

Machine Learning at Apple – https://machinelearning.apple.com/
AI at Uber – https://www.uber.com/us/en/uberai/
Machine Learning at Careem – https://blog.careem.com/en/tag/machine-learning/
Data Science at Grab – https://engineering.grab.com/categories/data-science/
Autopilot AI at Tesla – https://www.tesla.com/autopilotAI
AI at Microsoft – https://www.microsoft.com/en-us/ai
AI Research at Google – https://ai.google/research/
Self Driving Car Research at Lyft – https://medium.com/lyftlevel5
AI Research at Huawei – https://www.huawei.com/en/industry-insights/technology/ai
AI Research at Samsung – https://research.samsung.com/artificial-intelligence
AI at Alibaba – https://damo.alibaba.com/labs/ai
Data Science at Gojek – https://blog.gojekengineering.com/data-science/home
Intelligent Transportation Technology and Security at Didi Chuxing – http://www.didi-labs.com/
Amazon Science – https://www.amazon.science/
Data Science at Bolt – https://medium.com/@boltapp
Industrial AI Research at Hitachi – https://www.hitachi.com/rd/sc/aiblog/index.html

DEVELOPER RESOURCES:

Apple – https://developer.apple.com/machine-learning/
Facebook – https://ai.facebook.com/tools/
Google – https://cloud.google.com/products/ai
Microsoft – https://docs.microsoft.com/en-us/ai/

YOUTUBE CHANNELS:

The Massachusetts Institute of Technology’s Computer Science and Artificial Intelligence Laboratory – https://www.youtube.com/user/MITCSAIL/videos
The Allen Institute for Artificial Intelligence – https://www.youtube.com/channel/UCEqgmyWChwvt6MFGGlmUQCQ/videos
DeepMind – https://www.youtube.com/channel/UCP7jMXSY2xbc3KCAE0MHQ-A/videos
Applied AI Course – https://www.youtube.com/channel/UCJINtWke3-FMz2WuEltWDVQ/videos
StarCraft Artificial Intelligence Tournament – https://www.youtube.com/user/certicky/videos
Sentdex – Data Analysis Tutorials – https://www.youtube.com/c/sentdex/videos
Amazon – Machine Learning University – https://www.youtube.com/channel/UC12LqyqTQYbXatYS9AA7Nuw
Microsoft Research – https://www.youtube.com/user/MicrosoftResearch
Krish Nayak for ML/DL/Data Science – https://www.youtube.com/user/krishnaik06
TechWithTim – Python and ML Tutorials – https://www.youtube.com/channel/UC4JX40jDee_tINbkjycV4Sg
Jabrils https://www.youtube.com/channel/UCQALLeQPoZdZC4JNUboVEUg

AI JOB SITES:

DataYoshi – https://www.datayoshi.com/
AI Jobs – https://aijobs.com/
AI-Jobs – https://ai-jobs.net/
Indeed – https://www.indeed.com/q-Artificial-Intelligence-jobs.html
Kaggle Jobs – https://www.kaggle.com/jobs
Remote AI/ML Jobs: https://www.remoteaijobs.com/
AI Jobs Board: https://aijobsboard.com/

AI BLOGS:

Towards Data Science: https://towardsdatascience.com/
Towards Machine Learning: https://towardsml.com/
Towards AI: https://medium.com/towards-artificial-intelligence
Fritz AI: https://heartbeat.fritz.ai/
The Batch: https://www.deeplearning.ai/thebatch/
AI Trends: https://www.aitrends.com/
DeepMind: https://deepmind.com/blog
Becoming HumanAI: https://becominghuman.ai
Berkeley Artificial Intelligence Research: https://bair.berkeley.edu/blog/
IBM Developer: https://developer.ibm.com/patterns/category/artificial-intelligence/
OpenAI: https://openai.com/
MIT News: https://news.mit.edu/topic/artificial-intelligence2
Baidu Research: http://research.baidu.com/
Algorithmia: https://algorithmia.com/blog
Machine Learning Mastery: https://machinelearningmastery.com/blog/
Learn OpenCV: https://www.learnopencv.com/

AI CHEAT-SHEETS:

Best of AI Cheat-Sheets: https://becominghuman.ai/cheat-sheets-for-ai-neural-networks-machine-learning-deep-learning-big-data-science-pdf-f22dc900d2d7
Stanford CS229 Machine Learning: https://github.com/afshinea/stanford-cs-229-machine-learning
Stanford CS230 Deep Learning: https://github.com/afshinea/stanford-cs-230-deep-learning
Stanford CS221 Artificial Intelligence: https://github.com/afshinea/stanford-cs-221-artificial-intelligence
Collection of AI Cheat-Sheets: http://www.aicheatsheets.com/

CONTRIBUTION GUIDELINES:

Feel free to open a PR if you feel like something needs to be added or may be you want to suggest something. If you want to add something then your commit message should be like: added <resource_name> to <section_name>

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