Rishabh Mehrotra currently works as a Director of Machine Learning at ShareChat based in London. His current research focuses on machine learning for marketplaces, multi-objective modeling of recommenders, and the creator ecosystem. Prior to ShareChat, he was an Area Tech Lead and Staff Scientist/Engineer at Spotify where he led multiple ML projects from basic research to production across 400+ million users. Rishabh has a PhD in Machine Learning from UCL, and 50+ research papers and patents. Some of his recent work has been published at conferences including KDD, WWW, SIGIR, RecSys, and WSDM. He has co-taught a number of tutorials and summer school courses on the topics of learning from user interactions, marketplaces, and personalization.
Hien Luu is Head of Machine Learning Platform at DoorDash, author of Beginning Apache, and has been teaching at UCSC Extension School for more than 10 years. Previously, Hien was an Engineering Manager at LinkedIn where he helped build big data applications and infrastructure. And before that, Hien was at Uber, where he led the engineering team responsible for building a streaming processing platform to extract actionable business insights.
Grant is a CTO, independent consultant and advisor. He is the former CTO of the Wikimedia Foundation and the co-founder and ex-CTO of Lucidworks, co-author of Taming Text, co-founder of Apache Mahout and a long-standing committer on the Apache Lucene and Solr open source projects. Grant’s experience includes managing a large team of engineers, researchers and data scientists at a top ten website as well as engineering a variety of search, question answering, and natural language processing applications for a variety of domains and languages. He earned his B.S. from Amherst College in Math and Computer Science and his M.S. in Computer Science from Syracuse University.
Pamela Fox loves to learn, teach, and create. She’s currently a UC Berkeley lecturer, teaching a Python class to 1000+ students each semester. Previously, at Khan Academy, she created all of the programming courses and also helped develop the interactive platform for teaching programming in Python/JS. In her role before that as one of Coursera’s first frontend developers, she coded much of the original student-facing experience (also in Python/JS!). Her first job was at Google, as one of the first developer advocates, showing developers how to use their APIs in JS, Python, and many other languages.
Andrew Maas is currently at Apple working on data-centric deep learning. He completed a PhD in Computer Science at Stanford in 2015 advised by Andrew Ng and Dan Jurafsky. His dissertation focused on large scale deep learning methods for spoken and written language. Andrew has worked as an engineer and scientific advisor to several startups including Wit.ai, Coursera, and Semantic Machines. Prior to Apple, he built an NLP platform for precise healthcare language as cofounder of Roam Analytics. Additionally he also teaches CS224S: Spoken Language Processing as a visiting lecturer at Stanford University.
Daniel is an independent consultant specializing in search, machine learning / AI, and data science. He was a founding employee of Endeca, a search pioneer that Oracle acquired in 2011. He then led engineering and data science teams at Google and LinkedIn. He’s worked with a wide range of consulting clients, including Apple, eBay, Pinterest, Salesforce, Yelp, and Zoom. He wrote a book on Faceted Search, published by Morgan & Claypool, and he blogs on Medium about search-related topics — particularly query understanding. Daniel has degrees in Computer Science and Math from MIT and a PhD in computer science from CMU.
Emily Hawkins is a rising analytics star and expert in the field of dbt. She leads the analytics data platform at Drizly (acquired by Uber for $1.1B) where she designed and works on a modern data stack using tools like Fivetran, Snowflake, dbt, Dagster, Looker, and Census.
She also holds a Master of Science in Business Analytics from Bentley University, used to be the analytics lead for Wayfair, and gives powerful presentations on data modeling, the modern data stack, and analytics engineering at leading industry conferences.
Or take the complete Search track
Two courses for a combined price of $1140
Or take the complete ML Foundations track
Three courses for a combined price of $960
your ML & Data Skills
Or just wish to go through the basics again?
Shoutout to the course team for helping me (and others) keep pushing along to make sure we get through the finish line, even when things are hard. I can't tell you how much I appreciate the accountability and extra help!
I love it - just enough content and guidance that can be covered between work, kids, and life but still learn and be challenged
Completing this course has given me the foundation and confidence needed to make the full jump from Finance to Analytics Engineering. I've always felt like I needed a "credential" to make the full leap. Having gone through the course and learning with this community has made me feel like less of an "imposter" and like I have the skills/knowledge to do this as my profession (or at least know where to go to find the answers!). Really appreciative of the entire staff, TAs, cohort, pod, etc.
This course has been an amazing learning experience - no only because of the content of the course but also the way in which is taught! It has the perfect mix of online - individual work - community time and resources. The teaching materials are very high quality and the whole team are super attentive and responsive.
It's a great way to learn hands-on experience with dbt, get exposed to real life problems, industry experts and also networking! I highly recommend it!
I would recommend this to anyone looking to get their feet wet in dbt that needs a structured course and accountability to learn a new tool/skill
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.
I got to learn and directly interact with world class practitioners of NLP which no other course in the market offers.