Browse the Sinequa University course catalog for a particular subject to learn about. If you are looking for a certificate program, you can also see our Learning Paths and Certifications.
Learn about the history of cognitive search and how Sinequa is positioned to help organizations become information-driven.
Explore the Sinequa platform from a technical point of view.
Discover various demos and use cases for the Sinequa platform.
Discover all the resources Sinequa customers and partners have access to.
Learn about inverted indexes, the particularities of the Sinequa index architecture, and the various types of indexes.
Explore all there is to know about the Sinequa architecture.
Discover the security management within the Sinequa platform.
Understand how and why Natural Language Processing (NLP) and Natural Language Understanding (NLU) are implemented in Sinequa.
Set up the minimum Sinequa components needed to complete many of the other trainings found on Sinequa University.
Learn the basics of setting up the Sinequa platform on a single node or server, mostly for the purpose of training.
Learn about the range of pre-built connectors provided by Sinequa and how to set up a connector.
Explain the key concepts related to mapping when using a connector, implement the CSV connector to retrieve structured data from a CSV file, etc.
Learn how to use domain mappings to match users and/or groups from different security domains.
Discover Sinequa's Office 365 SharePoint connector, including Azure application configuration, setting up certificates for authentication, etc.
Explore collection overrides, which allow you to launch a connector while overriding the value of one or more parameters without changing the configuration of the collection.
Explore using the real-time indexing mode with the database connector.
Learn how to use a sub-query to get data from a table in a database other than the main table being indexed.
Discover how to use NLP Skills to extract information from documents with Sinequa.
Discover the two main methods used during the language identification process, the parameters that can influence the language identification process, etc.
Learn how to work with built-in entities, and modify the Entities to Extract into Columns section of NLP Analysis Parameters.
Learn how to create a whitelist for use with entities, configure entity extraction using a whitelist, and modify the Entities to Extract into Columns section of NLP Analysis Parameters.
Learn how to import entities from the Assets directory, and modify the Entities to Extract into Columns section of NLP Analysis Parameters
Work with built-in entities that are dependent on other entities, and modify the Entities to Extract into Columns section of NLP Analysis Parameters.
Explain co-occurrent entities, configure a co-occurrent entity, including modifying a whitelist, and modify the Entities to Extract into Columns section of NLP Analysis Parameters.
Explain what a selection query can be used for, and implement different selection query syntaxes.
Explain what index join queries can be used for, describe how index join queries work, and implement an index join query.
Learn how to use the JSON v2 connector, which lets you index many applications including a REST/JSON API.
Learn how NLP Resources can be used to customize linguistic analysis at indexing and search time.
Implement the file system connector and review connector and indexer logs to determine why some documents have NOT been indexed
Learn the purpose of the Access URL Root fields in the file system connector.
Explores NLP Analysis Parameters and how they can be used to customize linguistic analysis at indexing time.
Explore the indexing workflow including properties that can be used at different points in that workflow.
You have a set of film data in a CSV file that you want to make searchable. You will index this data with both mapping and full-text content configurations.
Set up entities to extract into full text and search entities in full text. Analyze the results in both the SQL console and in the SBA.
Explore the out-of-the-box configuration for Sinequa v 11.11 or later.
Explore Sinequa's Neural Search and how it works at a high level. You will also learn how to set up the out-of-the-box Sinequa Neural Search configuration.
Frequently asked questions and troubleshooting that you will encounter when working with neural search.
Learn about runnable models in Sinequa and how to package a runnable model in the Sinequa platform.
Use the entities to extract into full text and search entities in full text options, and expand on the query using a synonym search-time file so that no matter what the end user searches for, the same results will be found.
Explore document class weight with only statistical search to gain a better understanding of how it affect document result order.
Explore freshness boost with only statistical search, Set up runnable models for Neural Search, configure freshness boost to work with both Statistical Search & Neural Search.
Learn the basics of the Sinequa Assistant, including where you can download it, and find the necessary information to install it.
Learn what functions and workflows are, and how you can create new ones to customize the Sinequa Assistant.
Explore search-time files, which are used to modify the behavior of the Sinequa search platform when certain words are present. Learn how to implement synonyms and reformulations in the Sinequa platform.
Learn about search operators and how to set up the administration interface to make sure that they are all available.
Explore Search-Based Application (SBAs) including the vision and strategy, modular architecture, and the Sinequa repository at Github.
Learn about SBA sample applications such as Hello Search, Pepper, or Vanilla Search, available in the Sinequa Search-Based Application Framework.
Explore adding a cross distribution to the Multiple-Type Facet in an SBA.
Learn how to add metadata below results in the SBA using the sq-metadata-item selector, and add metadata below the results in the SBA using the sq-metadata selector.
Learn how to create a whitelist for use with entities, configure entity extraction using a whitelist, modify the Entities to Extract into Columns section of NLP Analysis Parameters, etc.
Explore highlighting extracted values in the SBA Preview and see a simple example of NLP Skills.
Explore creating a custom formatter to format metadata in an SBA without changing the data in the Sinequa Index.
Learn about the SBA tutorial challenge.
Learn how to use Vanilla Builder in order to create a personalized user interface.
Learn how to use the query intent V2 feature, which allows to detect the intent of the end user, and trigger a specific action such as modifying the query or displaying a specific view within an SBA.
Using Relevance Feedback Model (RFM), you can record clicks on the results and use those clicks to modify the result order for future searches.
Explore the basics of working with the security column model feature.
Explore how to set up column security, a feature used to exclude specific index columns from the search so that users only see results from the columns they are allowed to access.
Learn how to set up field-level security, which provides you with the ability to restrict access to specific indexed data using a specific field within a partition.
Learn how to migrate from using a file share for the Sinequa data folder and document cache to using primary nodes with a queue cluster and store servers for the document cache.
Learn about proper sizing and design of a GRID architecture.
Explore environment variables, which can be used within the configuration forms of the administration interface.
Learn how to install Sinequa with Primary Nodes, modify the sinequa.xml file to make a regular node into a primary node, and add components to a primary node distributed architecture.
Learn how to add a highly available queue cluster to your configuration, create store servers for use with the document cache, configure a document cache store to use replicated store servers.
You will configure a queue cluster in your primary node distributed architecture. Then you will create a replicated index that will use the queue cluster for index replication.
Configure two servers: one with Sinequa components and another with a Neural Search API. Enable cross-grid authentication and inference, then use the remote Neural Search for Sinequa searches.
Create a .NET class plug-in in the admin interface, set up Visual Studio, and link your file. Write and attach the connector plug-in in Visual Studio to the appropriate connector, then debug it in Visual Studio.
This exercise will walk you step-by-step through the process of developing a simple connector plug-in using recommended pages from the Sinequa technical documentation.
Learn how to create a custom function using a Function plug-in to convert mobile phone prices from US dollars to Euros during CSV file indexing.
Commands are used to automate various types of actions. If a built-in command is not available, a plug-in can be used to create a new command.
Learn to set up a plug-in in the administration interface and link it to a Visual Studio project. Create a query plug-in to filter file extensions from query text and add them to the SQL WHERE clause for metadata filtering.
Boost the relevance of recently published articles using Freshness Boost, which adjusts relevance based on the document's publication date.
Add metadata, such as document titles, to passages in Neural Search to improve relevance and avoid retrieving passages from incorrect documents.
A very simple introduction to Sinequa's stable, well-defined REST API.
Learn the steps to upgrade Sinequa.
Learn about the Usage Analytics application, which will let us track and monitor activity on the search-based application such as the number of users, search queries, top sources, most used filters, etc.
Explore the purpose of the different technical environments - development, staging and production - as well as the activities that would likely occur in each environment.
Discover delegated administration in the Sinequa platform, which makes it possible to show or hide specific areas of the administration interface based on the role of users or groups of users.
Discover aliases, which can be created for various components in the Sinequa platform including engines, indexers, indexes, nodes, and identities entities.
Learn about the foundations of working with the Git Console in the Sinequa platform. Explore different markers and menu options that are available when the Git Console is enabled.
Explore working with jobs and job lists to schedule the execution of different tasks including: indexing a collection or partition, running a command, or running a series of jobs either sequentially or in parallel.
Explain why commands are used, and learn how to create and use various commands.
Configure administration alerts for a collection error. You will then configure a collection that will fail and run it so an administration alert email is sent for the collection error.
Implement Expert Finder to help users find other users or help them find subject matter experts (SMEs) by searching for a specific topic.
Learn how to index data from across multiple databases and then to consolidate that data into a single point of access in your Sinequa platform.
Explore Sinequa's rich text mining capabilities including several techniques to tag and tokenize words during the indexing process.
This course introduces foundational principles and functionalities related to issue troubleshooting and the day-to-day operations of a Sinequa implementation.
This course covers many of the plug-ins available in Sinequa as well as their use within the indexing and search workflows.
Discover the power of the Sinequa search platform, optimized for Azure.
Explore how to install the Sinequa platform on Azure by building your own Sinequa image. This option will let you add monitoring tools, policies, etc. that are specific to your company.
Access all necessary guidelines: reusable documents, spreadsheets, templates or how-to guides used to help Sinequa partners and customers speed up various tasks during the Sinequa project lifecycle.
Learn about the different roles and responsibilities among Sinequa, the system integrator and/or the customer during the sales and deployment cycle.
Discover the various extranet portals and resources that Sinequa customers and partners have access to, which can provide knowledge and support when working with the Sinequa platform.
This ExperTalk addresses the question of Relevance Management within the Sinequa platform.
This ExperTalk is dedicated to Search-Based Applications developed in Angular and released in our public Github repository.
In this talk by Eric Leibenguth, Director of Application Design at Sinequa, learn about new features and apps in Sinequa's SBA Framework.
This ExperTalk introduces new architecture components like Primary Nodes, Queue Clusters and Store Servers.
This ExperTalk introduces the NLP Skills, a newly released framework to deal with all the NLP extractions.
This ExperTalk demonstrates how the Usage Analytics application based on the SBA framework can be used and customized.
This ExperTalk introduces a whole universe of available content and tools to Sinequa partners that will simplify and improve their work with Sinequa.
In this session, Eric Leibenguth, Director of Applications Design at Sinequa, introduces the newly released UI Builder.
This session describes and explains Sinequa4Azure, the Sinequa platform optimized for Microsoft Azure cloud thanks to a tight integration with Azure services.
Learn how to use the Usage Analytics application. Discover how Alstom Transport has implemented the Sinequa Usage Analytics application, to track their user adoption, feedback and performances.
The latest version of the Sinequa Assistant combines the power of the Sinequa Search platform with GenAI latest models, to deliver an high-end Retrieval Augmented Generation experience.
