# Massive Online Open Courses (MOOCs)

A curated list of free/open access Massive Online Open Courses.

## Contributing

..

## Table of Contents
- [Online Platforms for Learning](#online-platforms-for-learning)
- [Courses by Topic](#courses-by-topic)

## Online platforms for learning
* [AI Campus](https://ki-campus.org/).
* [AI on Demand](https://www.ai4europe.eu/).
* [BIDAcademy. Academia Banco Interamericano de Desarrollo](https://cursos.iadb.org/en).
* [DAIR:AI. Democratizing Artificial Intelligence Research, Education and Technologies](https://github.com/dair-ai).
* [FAO elearning ACADEMY](https://elearning.fao.org/)

## Digital skills
* [Codeacademy](https://www.codecademy.com/).
* [Coursera](https://www.coursera.org/).
* [Digital Skills & Jobs Platform](https://digital-skills-jobs.europa.eu/en).
* [EDX](https://www.edx.org/).
* [Freecodecamp](https://www.freecodecamp.org/).
* [Datacamp](https://www.datacamp.com/).
* [Future Learn](https://www.futurelearn.com/).
* [NVIDIA Deep Learning Institute](https://learn.nvidia.com/en-us/training/self-paced-courses).
* [The Forage](https://www.theforage.com/).
* [The Linux foundation](https://trainingportal.linuxfoundation.org).
* [Udacity](https://www.udacity.com/).
* [Cognitive Class AI](https://cognitiveclass.ai/).
* [CertiProf free certifications][https://certiprof.com/pages/free-new-entry-level-certification]
* [SimpliLearn](https://www.simplilearn.com/).

## Open access courses offered by universities
* [MIT OpenCourseWare](https://ocw.mit.edu/).
* [MIT Open Learning](https://openlearning.mit.edu/).
* [Standford Online, free online courses](https://online.stanford.edu/free-courses).
* [Open Source Society University](https://github.com/ossu).
* [UPV EDX](https://upvx.es/).

## Earth Sciences
* [ECMWF Learning Platform](https://learning.ecmwf.int/).
* [Earth Lab. Learn to use earth science and other data in R and Python]
* [IBM SkillsBuild](https://www.earthdatascience.org/).

## Big Tech Companies
* [IBM Training](https://www.ibm.com/training/).
* (https://skills.yourlearning.ibm.com).
* [CISCO Network Academy](https://www.netacad.com/).
* [Grow with Google](https://grow.google/)
* [Microsoft. Learn Microsoft](https://learn.microsoft.com/en-us/).
* [Oracle Education](https://education.oracle.com/es/).
* [Oracle Academy](https://learn.oracle.com/).

## Courses by Topic
### Artificial Intelligence
* [Elements of AI](https://www.elementsofai.com/).

### Computer Vision
* [Computer vision image understanding](https://digital-skills-jobs.europa.eu/en/opportunities/training/computer-vision-image-understanding-efficient-business-and-industry)
  .

### Data Science
* [Curso de Data Science](https://www.santanderopenacademy.com/es/courses/introduction-to-data-science.html).
* [Data Science for Ecologist and Environmental Scientist](https://ourcodingclub.github.io/).
* [Data Science Fundamentals](https://cognitiveclass.ai/learn/data-science).
* [Data Science Foundations](https://www.codecademy.com/learn/paths/data-science-foundations).


### Deep Learning
* [Networks for Learning: Regression and Classification](https://ocw.mit.edu/courses/9-520-a-networks-for-learning-regression-and-classification-spring-2001/)
  .
* [HSG 10,860,1.00 - Introduction to Applied Deep Learning](https://github.com/pA1nD/course-deep-learning).
* [A Guide to Production Level Deep Learning](https://github.com/alirezadir/Production-Level-Deep-Learning).

### Goegraphical Information Systems (GIS)
* [Sistemas de Información Geográfica. Víctor Olaya](https://volaya.github.io/libro-sig/index.html).

### Machine Learning
* [Foundations of Machine Learning](https://bloomberg.github.io/foml/#home).
* [Google Machine Learning](https://developers.google.com/machine-learning).
* [Introduction to Machine Learning](https://developers.google.com/machine-learning/intro-to-ml).
* [Machine Learning Crash Course](https://developers.google.com/machine-learning/crash-course).
* [Machine Learning Technical Interviews](https://github.com/alirezadir/Machine-Learning-Interviews/blob/main/README.md)
  .
* [ML for Beginners](https://github.com/microsoft/ML-For-Beginners).

### Maths
* [Cómo aprender matemáticas – Para Estudiantes](https://online.stanford.edu/courses/gse-yeduc115-sp-como-aprender-matematicas-para-estudiantes)
  .
* [Linear Algebra Gilber Strang](https://ocw.mit.edu/courses/18-06sc-linear-algebra-fall-2011/pages/ax-b-and-the-four-subspaces/)
  .
* [Matrix Methods In Data Analysis, Signal Processing, And Machine Learning](https://ocw.mit.edu/courses/18-065-matrix-methods-in-data-analysis-signal-processing-and-machine-learning-spring-2018/)
  .
* [Single Variable Calculus](https://ocw.mit.edu/courses/18-01-single-variable-calculus-fall-2006/).
* 

### Statistics and Probability
* [Introduction to Probability and Statistics - Spring 2022](https://ocw.mit.edu/courses/18-05-introduction-to-probability-and-statistics-spring-2022/)
  .
* [Introduction to Probability and Statistics](https://openlearninglibrary.mit.edu/courses/course-v1:MITx+18.05r_10+2022_Summer/course/)
  .
* [Técnicas Estadísticas para el Análisis Científico de Datos](https://www2.uned.es/experto-estadistica-multivariante/).
* [MITx: Probability - The Science of Uncertainty and Data](https://www.edx.org/learn/probability/massachusetts-institute-of-technology-probability-the-science-of-uncertainty-and-data)
  .
* [Statistics and Probability contents. Tech yourself statistics](https://stattrek.com/).

[HARVARD UNIVERSITY - Data Science Courses](https://pll.harvard.edu/catalog?topics%5B714%5D=714&price%5B1%5D=1&max_price=&keywords=&page=1)

### Scrum methodology
* [Scrum Foundations](https://www.agile-academy.com/en/agile-insights/scrum-foundations-online-course/).
* [Scrum Guides](https://scrumguides.org/).
* 

### Remote Sensing
* [Remote sensing](https://es.coursera.org/learn/remote-sensing).
* [Tutorial Open Nighttime Lights](https://worldbank.github.io/OpenNightLights/welcome.html).

### CUDA programming / GRPU programming/ Paralell Programming
* [Fundamentals of Accelerated Computing with CUDA Python](https://courses.nvidia.com/courses/course-v1:DLI+C-AC-02+V1/)
  .
* [Fundamentals of Accelerated Computing with CUDA C/CMITx: Probability - The Science of Uncertainty and Data ++](https://courses.nvidia.com/courses/course-v1:DLI+C-AC-01+V1/)
  .
* [CUDA Tutorial](https://cuda-tutorial.readthedocs.io/en/latest/).
* [NVIDIA CUDA](https://github.com/federico-busato/Modern-CPP-Programming).
* [NVIDIA DLI Online Training Catalogue](https://digital-skills-jobs.europa.eu/en/opportunities/training/nvidia-dli-online-training-catalogue)
  .
* [Fundamentals of Heterogeneous Parallel Programming with CUDA C/C++](https://education.molssi.org/gpu_programming_beginner/)
  . | https://github.com/MolSSI-Education/gpu_programming_beginner
  

### Robotics
* [Modern Robotics](https://github.com/madibabaiasl/modern-robotics-course).
* [Robotics courses](https://github.com/mithi/robotics-coursework).
* [Robotics courses online platform. Cursos de robótica](https://www.theconstructsim.com/).
* [ROS Industrial, Industrial Training](https://industrial-training-dev.readthedocs.io/).

### Teledetection, satellital images
* [Applied NASA Training](https://appliedsciences.nasa.gov/get-involved/training/). The ROS-Industrial training page!

## Plants
*[Cultivo sin suelo - Tercera edición](https://www.plataformatierra.es/formacion/cultivo-sin-suelo-tercera-edicion)

## Licenses

License

[![CC0](http://i.creativecommons.org/p/zero/1.0/88x31.png)](http://creativecommons.org/publicdomain/zero/1.0/)