Merge pull request keon#240 from ogabrielluiz/patch-1

Added Amazon's now public course

Author: keon

README.md

@@ -110,7 +110,9 @@ Blogs and Newsletters
 * [Deep Learning for Natural Language Processing (cs224-n)](https://web.stanford.edu/class/cs224n/) - Richard Socher and Christopher Manning's Stanford Course
 * [Neural Networks for NLP](http://phontron.com/class/nn4nlp2017/) - Carnegie Mellon Language Technology Institute there
 * [Deep NLP Course](https://github.com/yandexdataschool/nlp_course) by Yandex Data School, covering important ideas from text embedding to machine translation including sequence modeling, language models and so on. 
-* [fast.ai Code-First Intro to Natural Language Processing](https://www.fast.ai/2019/07/08/fastai-nlp/) - This covers a blend of traditional NLP topics (including regex, SVD, naive bayes, tokenization) and recent neural network approaches (including RNNs, seq2seq, GRUs, and the Transformer), as well as addressing urgent ethical issues, such as bias and disinformation. Find the Jupyter Notebooks [here](https://github.com/fastai/course-nlp)   
+* [fast.ai Code-First Intro to Natural Language Processing](https://www.fast.ai/2019/07/08/fastai-nlp/) - This covers a blend of traditional NLP topics (including regex, SVD, naive bayes, tokenization) and recent neural network approaches (including RNNs, seq2seq, GRUs, and the Transformer), as well as addressing urgent ethical issues, such as bias and disinformation. Find the Jupyter Notebooks [here](https://github.com/fastai/course-nlp)
+* [Machine Learning University - Accelerated Natural Language Processing](https://www.youtube.com/playlist?list=PL8P_Z6C4GcuWfAq8Pt6PBYlck4OprHXsw) - Lectures go from introduction to NLP and text processing to Recurrent Neural Networks and Transformers.
+Material can be found [here](https://github.com/aws-samples/aws-machine-learning-university-accelerated-nlp).
 
 
 ### Books