Enroll now to join this live cohort-based course led by Doug Turnbull
Apply machine learning to ranking, query and content understanding with one of Shopify's most senior engineers.
Format: 5 x 2-hour live sessions (+ recordings of each)
Dates: 1:00 PM PT; Oct 11, 13, 20, 25 and 27
Price: $900 per seat (expense through L&D)
This course is designed for
Search Relevance Engineers and Data Scientists
who tune search engines to create more relevant results
who measure or evaluate search quality
Watch Doug's recent live chat on
What's Next in Search
Since 2010, Doug Turnbull has worked with companies such as Shopify, Careerbuilder, Wikimedia Foundation, Shipt, and LexisNexis on improving search experiences. Doug coaches and develops search teams from startups to Fortune 500 companies, setting up organizational practices to build relevant search. Doug wrote “Relevant Search” (2016) and co-authored “AI Powered Search” (2022). He also co-created the Elasticsearch Learning to Rank, bringing machine learning to the most popular search engine, which revamped Wikipedia and Yelp, driving intelligent search behind dozens of companies' search experiences.
Doug currently leads the search relevance practice at Shopify, helping democratize e-commerce discovery for millions of independent merchants.
What you get out of
Want to get to know Professor Bernstein?
You’re invited to our live course information session
Professor Berstein is hosting a live 30 minute session free to attend for all. He will be giving a breif introduction to the his upcoming course and then answering audience questions.
4:00-4:30pm PST; March 15
With limited patience — and, often, small screens — many users avoid navigation altogether. Instead, they jump to a search bar to find what they need. Yet, with limited screen real-estate, many teams know search optimization can go bad. You can show only a handful of results out of millions to click on.
How can you deliver the magic your users seek with a conversational, relevant search experience? How do you give users the results that will achieve their goals? This course helps you analyze search behaviors to target relevance treatments, solving them using modern data science and machine learning.
Learn how your business can meet modern users where and how they expect to use applications.
How do I analyze search behaviors to arrive at reliable search relevance training data?
How do I train a ranking model to optimize for relevance?
What search measures correspond to my business needs?
What does a good search experience look like?
How do I explore novel ranking features?
Session 1 - The search relevance problem
Tune a relevance solution using traditional, non-ML methods. Upon completing session 1, learners will be able to:
Differentiate relevant from irrelevant results
Develop measures for ranking quality across many searches
Experiment with manually tweaking a relevance solution
Session 2 - Now we train!
Train a simple ranking model using hand-labeled results from session 1. At the end of this session, learners will be able to:
Build models that categorize relevant from irrelevant results
Test ranking models with a test-train split
Session 3 - Better training data
Overcome core biases in search behavioral data to build a successful ranking model. After this session, learners will:
Overcome core biases in search behavioral data to build a successful ranking model.
Be able to contrast approaches to overcoming biases
Session 4 - Feature discovery
Navigate echo-chambers by experimenting with novel ranking features. Learners who complete this session will be able to:
Understand how and why echo chambers occur in search
Obliterate echo chambers underlying search experiences to make positive step-changes in search relevance
Evaluate new query, user, or document ranking features that go beyond your current search solution using Active Learning
Session 5 - Traction
The playbook on how to get unstuck from the search relevance problem. Upon completion of this session, learners will be able to:
Manage rollout of search relevance experiments in search
Balance near-term search wins, with longer-term investments needed to take search to the next level
Convince team and stakeholders that your ML-Powered search team is moving in the right direction
Still have questions?
We’re here to help!
Do I have to attend all of the sessions live in real-time?
You don’t! We record every live session in the cohort and make each recording and the session slides available on our portal for you to access anytime.
Will I receive a certificate upon completion?
Each learner receives a certificate of completion, which is sent to you upon completion of the cohort (along with access to our Alumni portal!). Additionally, Sphere is listed as a school on LinkedIn so you can display your certificate in the Education section of your profile.!
Is there homework?
Throughout the cohort, there may be take-home questions that pertain to subsequent sessions. These are optional, but allow you to engage more with the instructor and other cohort members!
Can I get the course fee reimbursed by my company?
While we cannot guarantee that your company will cover the cost of the cohort, we are accredited by the Continuing Professional Development (CPD) Standards Office, meaning many of our learners are able to expense the course via their company or team’s L&D budget. We even provide an email template you can use to request approval.
I have more questions, how can I get in touch?
Please reach out to us via our Contact Form with any questions. We’re here to help!