Natural Language Processing
Learn the core NLP building blocks powering search engines like Google or voice assistants like Siri or Amazon Alexa. We will develop an understanding of core NLP components — word vectors, intent classification, entity recognition and many more using transformer architectures like BERT and GPT — while building projects like embedding-based retrieval and smart-compose.
Course taught by expert instructors
former Engineering Manager at Neeva
Sourabh is a software engineer interested in Machine Learning and Data Infrastructure. Prior to his current role he has had several engineering roles at Google Brain working on Tensorflow, at Coursera working on data and ML infrastructure and at Neeva. He obtained a M.S. in Machine Learning from Georgia Tech and got a B. Tech in Engineering from BITS Pilani.
Software Engineer at Meta
Kaushik Rangadurai is an expert in the field of Natural Language Processing and is currently a Technical Leader in the Content Understanding team at Facebook. He holds many patents and published papers in the field of search and recommendation, and has over 10 years of experience building AI driven products for companies like LinkedIn, Google and Microsoft and was an early engineer at Passage AI. Kaushik holds a Masters in Computer Science from the Georgia Institute of Technology at Atlanta specializing in Machine Learning.
Learn and apply skills with real-world projects.
- ProjectA emotion classification system that can be used as part of chatbot systems.Learn
- PyTorch Lightning
- Intro to Deep Learning
- Word Vectors
- Multilayer perceptron (MLP)
- ProjectA system to locate and classify named entities such as organizations, names, locations (i.e. TikTok, Lebron James, London), mentioned in unstructured text.Learn
- Recurrent Neural Network (RNNs)
- Long Short-Term Memory (LSTMs)
- Named-entity Recognition (NER)
- ProjectAn embedding-based search system that can search millions of documents in a few milliseconds. We'll use this to de-duplicate any questions that are already asked on Quora.Learn
- Sentence Vectors
- Siamese Networks
- Bidirectional Encoder Representations from Transformers (BERT)
- ProjectGmail like smart-compose system that can assist with typing by suggesting the next few words in realtime. Also, we use Co:here, a short introduction on ready-made NLP models through an easy to use API.Learn
- Subword Tokenizers
- Generative Pre-trained Transformer (GPT)
Work on projects that bring your learning to life.
Made to be directly applicable in your work.
Live access to experts
Sessions and Q&As with our expert instructors, along with real-world projects.
Network & community
Core reviews a study groups. Share experiences and learn alongside a global network of professionals.
Support & accountability
We have a system in place to make sure you complete the course, and to help nudge you along the way.
Course success stories
Learn together and share experiences with other industry professionals
Absolutely stoked to share this! Over the last month I had the pleasure of learning from some of the great minds coming out of Facebook, Google, and other enterprises doing bleeding edge work in Machine Learning and Natural Language Processing. Being part of a select cohort spanning three continents I was able to hear about initiatives and research from AI/ML professionals around the globe. NLP is a fast emerging sector that is changing the landscape of software everywhere you look. I'm so honored to be part of this experience and am taking away so many great connections and insights in a field that I really love.
The co:rise NLP course has been the most efficient way I've ever learned new skills. Having access to talented instructors and peers made the learning process both quicker and richer.
You will go from zero to MLhero with this course. A lot of concepts clicked for me with this training, we went beyond the classic reading and blog post and got really into the weeds and ins-and-outs of the different topics.
This course is a great way to familiarize yourself with state-of-the-art NLP techniques. You will go from building skip-gram models to classify emotions to text-prediction with transformers in 4 weeks.
I really enjoyed the course and the community around it. I think it was a great way to not only learn about NLP, but also connect with other engineers in the field.
For learners who are looking for hands-on experience with implementing NLP methods and are interested in direct contact with instructors and other classmates, this class is a perfect fit.
An exceptional opportunity for motivated students. You will gain broad awareness and practical experience using state-of-the-art NLP techniques that can get you up to speed in this fast-moving field. The mentorship available to students is unparalleled.
I really appreciated the NLP course. I feel like every aspect of the course, from the work Judy did creating community, managing slack, and making sure we were all taken care of, to the instruction and support from Sourabh and Kaushik. I learned so much in this course, and had a great time learning from my fellow participants as well. I've finished this course feeling like I have a solid footing to move forward with NLP applications in the future. Thanks!
This course gives you a great overview of modern NLP techniques in just 4 weeks. But more importantly, you learn from people who use it in very big real life projects and have a change to get knowledge that wouldn't be available in a blog post
This course is for...
Software Engineers looking to learn more or work in machine learning fields
Data science and machine learning practitioners looking for practical learning in NLP to support their current work, including those completely new to NLP
Writing Python and an ability to find and read documentation of different libraries.
Basics of machine learning is recommended
Note: NLP experience is NOT required.