singhsuryansh12/free-ai-resources

🚀 FREE AI Resources - 🎓 Courses, 👷 Jobs, 📝 Blogs, 🔬 AI Research, and many more - for everyone!

A curated list of FREE AI RESOURCES for aspiring AI Engineers

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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/
• 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

⚙️ 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

📈 FREE DATA SCIENCE COURSES:

• IBM Data Science Professional Certificate - https://www.coursera.org/professional-certificates/ibm-data-science

🧠 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

🗣️ 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

👁️ 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/

📦 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/
• 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

💼 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

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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