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Best courses/training for data science & machine learning

Best courses/training for data science & machine learning

datacamp.com
IBM — https://cognitiveclass.ai/
Microsoft — https://academy.microsoft.com/en-us/professional-program/tracks/data-science/
Harvard — https://online-learning.harvard.edu/subject/data-science

https://www.coursera.org/learn/machine-learning
Andrew Ng's Standford course
For programming knowledge there are two things I suggest — First is datacamp.com and Second is Kaggle.com
I suggest Kaggle too. Find a competition. Go to kernals. Sort by best score. Read through the top kernal.
Analyst Academy — https://www.chi2innovations.com/
and the HIIVE at Chi Squared for free and for cost books and classes

I will give you what I have collected over the years for free resources. Forgive me if the links don't work as it may have aged a bit. Also of note: Depending on your fluency with this topic you may not need some of these for a while as you work on core competency in Python for example.
Programming
Python - https://lnkd.in/gGQ7cuv
R - https://lnkd.in/giMGbph
SQL - https://lnkd.in/gM8nMNP
Command Line - https://lnkd.in/e3EQuis
Stats/Prob/Math
Coursera's Statistics w/ R - https://lnkd.in/gGT9NEf
edX's Probability - https://lnkd.in/gpUyC3P
Khan Academy Linear Algebra - https://lnkd.in/gMshbX4
Data Viz
Python Matplotlib- https://lnkd.in/gr3ifNt
R ggplot2 - https://lnkd.in/eThJXNr
Data Manipulation
Python Pandas - https://lnkd.in/g9kfpX4
R dplyr - https://lnkd.in/gAWusih
Google Crash Course - https://lnkd.in/gSgkVcT
Stanford Coursera - https://lnkd.in/g8ZG557
ISLR Book - https://lnkd.in/gk8GPZC
Experimental Design - Udacity A/B Testing - https://lnkd.in/gCerh4f
EDA Approach - https://spr.com/data-science-basics-data-exploration/
Business Sense - Metrics - https://lnkd.in/gZAG7bS
Communication - Storytelling - https://lnkd.in/gwjxVUu
Core Concepts: Introduction to Bag of Words (CountVectorizer, TFIDF, HashVectorizer) https://lnkd.in/gcymgfJ
Text Preprocessing (Stopword Removal, Tokenization, Stemming/Lemmazation) https://lnkd.in/gxDszeb
Word Vectors https://lnkd.in/gPrmD99
Regex Tutorial https://lnkd.in/gDG3HTA
Common NLP Libraries: SpaCy: https://spacy.io/usage/
TextBlob - https://lnkd.in/gZCK4QX
NLTK - https://lnkd.in/gqccVsQ
Gensim: https://lnkd.in/gee5p3Z U
LMFit - https://lnkd.in/gJMuTXy
NLP Projects: Build a Simple Chatbot from Scratch https://lnkd.in/gyS4TrJ
Web Scraping and Sentiment Analysis https://lnkd.in/g3AupnH
Textual Feature Importance with ELI5 https://lnkd.in/gYQPsiT
Topic Modeling – Latent Dirichlet Allocation (LDA) https://lnkd.in/gEQkWu7
One of the best resources for free / nearly free info on this topic is just through following this guy: https://www.linkedin.com/in/vipulppatel/

https://www.humblebundle.com/
https://pages.rstudio.net/ModelingonDatabaseswithR.html