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Search for Product Managers

Building effective search applications requires addressing a number of technical challenges. But fundamentally search is a product challenge, and the best search applications have strong product managers who deeply understand search. This course is designed to teach product managers the most important things they need to know about search: Metrics and Evaluation, Relevance and Ranking, Content and Query Understanding, and Vectors and Neural Search.

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Daniel Tunkelang
Machine Learning Consultant

We taught over 5000 learners from these companies:

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Real-world projects that teach you industry skills.
Learn alongside a small group of your professional peers
Part-time program with 2 live events per week.
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Course taught by expert instructors

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Daniel Tunkelang

Machine Learning Consultant

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.

A course you'll actually complete. AI-powered learning that drives results.

AI-powered learning

Transform your learning programs with personalized learning. Real-time feedback, hints at just the right moment, and the support for learners when they need it, driving 15x engagement.

Live courses by leading experts

Our instructors are renowned experts in AI, data, engineering, product, and business. Deep dive through always-current live sessions and round-the-clock support.

Practice on the cutting edge

Accelerate your learning with projects that mirror the work done at industry-leading tech companies. Put your skills to the test and start applying them today.

Flexible schedule for busy professionals

We know you’re busy, so we made it flexible. Attend live events or review the materials at your own pace. Our course team and global community will support you every step of the way.


Completion certificates

Each course comes with a certificate for learners to add to their resume.

Best-in-class outcomes

15-20x engagement compared to async courses

Support & accountability

You are never alone, we provide support throughout the course.

The course

Learn and apply skills with real-world projects.

Who is it for?
  • This course is for product managers who work with or want to work with search applications.

  • The class assumes no previous knowledge of search.

  • Defining Relevance: Precision, Recall, Position, Discounted Cumulative Gain (DCG)
  • Collecting Judgements: Explicit Human Judgements vs. Implicit Behavioral Judgements
  • Metrics: Query vs. Session vs. User, Components vs. End-to-End, User vs. Business
  • Experimentation: Offline Analysis, A/B Testing, Interleaving, Explore-Exploit
  • Quantitative vs. Qualitative Evaluation: Analyzing Data vs. Conducting User Studies
  • Relevance vs. Ranking: Separating Objective and Subjective Concerns
  • Ranking Factors: Query-Dependent vs. Query-Independent vs. Contextual
  • Hand-Tuned and Machine Learning Ranking: Theory and Practice
  • Multiple-Phase Ranking: Computational Tradeoffs and Multiple Objectives
  • Limitations: When Ranking is Not the Solution to Your Search Problem
  • Matching vs. Ranking: Simplifying the Problem by Factoring It
  • Content Understanding: Indexing Content to make it Findable
  • Query Understanding: Representing Queries as Search Intents
  • Hand-Tuned and Machine Learning Content and Query Understanding
  • Limitations: When to Trust Algorithms vs. When to Ask Humans
  • AI-Powered Search: Representing Content and Queries as Vectors
  • Semantic Retrieval: Nearest Neighbors and Approximate Methods
  • Ranking: Combining Vector Similarity with Other Factors
  • Filtering and Sorting: Challenges of Similarity-Based Retrieval
  • Limitations: When to Stick with Traditional Indexing Representations

Still not sure?

Get in touch and we'll help you decide.

Course success stories

Learn together and share experiences with other industry professionals

If you’re a Product Manager in a Search or a Search adjacent space then you don’t want to miss Daniel’s course on Search for Product Managers. I’ve worked with Daniel at LinkedIn and have continued to rely on him for advice on building Search products in my subsequent roles. He has unmatched expertise in both the product thinking and technology that goes into building a world-class Search experience. If you’re building either a domain specific or general search product you’ll get a ton of value from this course.

Daniel FranciscoGoogle

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