Where to start with Data Science

There is now way to be taught to be data scientist, but you can learn how to become one yourself. There is no right way, but there is a way, which was adopted by a number of data scientists and it goes through online courses (MOOC). Following suggested order is not required, but might be helpful.

Best resources to study Data Science /Machine Learning

1. Andrew Ng’s Machine Learning (https://www.coursera.org/learn/machine-learning).
2. Geoffrey Hinton’s Neural Networks for Machine Learning (https://www.coursera.org/learn/neural-networks).
3. Probabilistic Graphical Models specialisation on Coursera from Stanford (https://www.coursera.org/specializations/probabilistic-graphical-models).
4. Learning from data by Caltech (https://work.caltech.edu/telecourse.html).
5. CS229 from Stanford by Andrew Ng (http://cs229.stanford.edu/materials.html)
6. CS224d: Deep Learning for Natural Language Processing from Stanford (http://cs224d.stanford.edu/syllabus.html).
7. CS231n: Convolutional Neural Networks for Visual Recognition from Stanford (http://cs231n.stanford.edu/syllabus.html).
8. Deep Learning Book by Ian Goodfellow and Yoshua Bengio and Aaron Courville (http://www.deeplearningbook.org/).
9. Machine Learning Yearning by Andrew Ng (http://www.mlyearning.org/).

#books #wheretostart #mooc

Google has released a new open and free machine learning course. The course is built around Google's TensorFlow API, which is now one step closer to becoming an industry standard.

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

Microsoft’s AI course is now open and free

Microsoft Professional Program for Artificial Intelligence — previously being available only to employees is now available at edx.org for free. Program includes 10 courses from basic python programming to deep learning and reinforcement learning disciplines.

https://academy.microsoft.com/en-us/professional-program/tracks/artificial-intelligence/

#mooc #microsoft #course

Udacity has published a github repo for the Deep Reinforcement Learning Nanodegree program

Repo: https://github.com/udacity/deep-reinforcement-learning
Nanodegree: https://www.udacity.com/course/deep-reinforcement-learning-nanodegree--nd893

#dl #udacity #mooc #course #github #rl

🎓Amazon have released its Free Machine Learning #course.

Course consits of 30+ digital ML classes totaling 45+ hours, aiming for improving skills of different roles: from Data Platform Engineer to Business Decision Maker.

Link: https://aws.amazon.com/ru/training/learning-paths/machine-learning/

#Amazon #ML #MOOC

New free Deep Learning course from #FastAI

This course shows how to build a state of the art deep learning model from scratch.
FastAI’s mission is to make neural nets uncool again by teaching as many people from as many backgrounds as possible.

Link: https://www.fast.ai/2019/06/28/course-p2v3/

#MOOC #DL #freecourse

🔥🎓New FastAI's free online course on NLP

It is called «A Code-First Introduction to Natural Language Processing». All code & videos are available for free online, make sure you save this link into bookmarks and at least review the content, because it provides opportunity not only to learn new skills, but to actually understand how NLP works.

Link: https://www.fast.ai/2019/07/08/fastai-nlp/

#NLP #NLU #DL #MOOC #FastAI #course

Overview of 10 Stanford's Data Science courses

A survivor’s guide to Artificial Intelligence courses at Stanford

Link: https://huyenchip.com/2018/03/30/guide-to-Artificial-Intelligence-Stanford.html

#Staford #MOOC #course #free #rating #learning

Great collection and reviews for top online machine and deep learning courses

Post covers short reviews and suggested order in which course could be taken, along with the links at great prerequisites.

Link: http://thegrandjanitor.com/2016/08/15/learning-deep-learning-my-top-five-resource/

#DL #ML #MOOC #novice #entrylevel

Great collections of Data Science learning materials

The list includes free books and online courses on range of DS-related disciplines:

Machine learning (#ML)
Deep Learning (#DL)
Reinforcement learning (#RL)
#NLP

Tutorials on #Keras, #Tensorflow, #Torch, #PyTorch, #Theano

Notable researchers, papers and even #datasets. It is a great place to start reviewing your knowledge or learning something new.

Link: https://hackmd.io/@chanderA/aiguide

#wheretostart #entrylevel #novice #studycontent #studymaterials #books #MOOC #meta

🎓CS224W: Machine Learning with Graphs

Great course from #Stanford. You still on time to jump at studying from one of the best schools.

Students are introduced to machine learning techniques and data mining tools apt to reveal insights on the social, technological, and natural worlds, by means of studying their underlying network structure and interconnections.

Topics include: robustness and fragility of food webs and financial markets; algorithms for the World Wide Web; graph neural networks and representation learning; identification of functional modules in biological networks; disease outbreak detection.

Link: http://cs224w.stanford.edu
Videos link: http://snap.stanford.edu/class/cs224w-videos-2019/

#MOOC #entrylevel #wheretostart

Big scandal on popular YouTuber ML course

Siraj Raval, who raised his audience on devliering various YouTube videos, explaning #ML and #DL concepts as long with interviews with leading persons, launched his own course, but failed to provide much value.

His course was built on open and free tutorials, created by passionate enthusiasts, but he failed to attribute them properly and charged money for ununique content without any proper support for students.

He also oversold his course and tried to hide that from students, claiming to provide personal feedbacks, but failing to do so due to being too greedy.


Most of the best online courses and study programms are available online and for free, including those, we gathered here on our channel and attributed with hastags #wheretostart #entrylevel #MOOC #tutorial. Feel free to click these hashtags and browse for best available resources to start learning data science.

Link: https://www.theregister.co.uk/AMP/2019/09/27/youtube_ai_star

🎓 Reinforcement Learning Course from OpenAI

Reinforcement Learning becoming significant part of the data scientist toolbox.
OpenAI created and published one of the best courses in #RL. Algorithms implementation written in #Tensorflow.
But if you are more comfortable with #PyTorch, we have found #PyTorch implementation of this algs

OpenAI Course: https://spinningup.openai.com/en/latest/
Tensorflow Code: https://github.com/openai/spinningup
PyTorch Code: https://github.com/kashif/firedup

#MOOC #edu #course #OpenAI

Matus Telgarsky’s Deep Learning Theory course

Course syllabus, lecture handout materials from Illinois university.

Link: http://mjt.cs.illinois.edu/courses/dlt-f19/

#MOOC #DL #Theory #Course

Free eBook from Stanford: Introduction to Applied Linear Algebra – Vectors, Matrices, and Least Squares

Base material you need to understand how neural networks and other #ML algorithms work.

Link: https://web.stanford.edu/~boyd/vmls/

#Stanford #MOOC #WhereToStart #free #ebook #algebra #linalg #NN

​​Ultimate post on where to start learning DS

Most common request we received through the years was to share insights and advices on how to start career in data science and to recommend decent cources. Apparently, using hashtag #wheretostart wasn't enough so we were sharing some general advices.

So we assembled a through guide on how to start learning machine learning and created another #ultimatepost (in a form of a github repo, so it will be keep updated and anyone can submit worthy piece of advice to it).

We welcome you to share your stories and advices on how to start rolling into data science, as well as to spread the link to the repo to those your friends who might benefit from it.

Link: Ultimate post

#entrylevel #beginner #junior #MOOC #learndatascience #courses #mlcourse #opensource

🎓Online Berkeley Deep Learning Lectures 2021

University of Berkeley released its fresh course lectures online for everyone to watch. Welcome Berkeley CS182/282 Deep Learnings - 2021!

YouTube: https://www.youtube.com/playlist?list=PLuv1FSpHurUevSXe_k0S7Onh6ruL-_NNh

#MOOC #wheretostart #Berkeley #dl