Building a successful PoC requires a good understanding of the technology basics, as well as its practical implementation. This training covers both aspects in a concise, yet comprehensive way. We will help:
to agree on their PoC functional design.
We had undergone an excellent training on introduction to semantic technology, and this gave a deep insight to RDF, ontologies and GraphDB’s behaviour and semantic technology.
Sreejith K, Team Lead, Impelsys
The training can be followed by an individual 1-hour consultation (included in the price) to turn the acquired knowledge into a practical solution to a specific business case. We will be able to offer only 15 spots for individual consultations for each training.
As part of the consultation, we will:
Get a chance to address your project’s specific requirement with our experts in the domains of Life Science, Healthcare, Publishing & Media, Natural Language Processing, Text Analysis, Ontology and Vocabulary Management and others.
Georgi is a leading expert in technical programming, technical architecture, linked data, cognitive technology, and text analytics. He is the author of more than 60 research and industry publications on today’s hot topics of machine learning, algorithms, linguistics, big data, analytics and Semantic Technology.
Vladimir’s experience includes ontology engineering, metadata standards, vocabularies and thesauri, RDF, RDFS, OWL2, SHACL, SKOS, SPARQL, LOD, mapping, R2RML, ETL, semantic web applications, project management, business analysis and requirements specifications. He has worked in various business domains, from Customs and Excise,to Personal Finance workflows, to Legal Procedures and Statistics, to Cultural Heritage and Digital Humanities.
Ivelina has over 10 years of experience in natural language processing. Recently she has been focusing on the application of NLP techniques for enhancing semantic technologies, which is also the topic of her Ph.D. thesis. Her expertise in semantic annotation and information extraction is the result of numerous research and commercial projects in domains like news & media, financial, biomedical and cultural heritage. In these areas, she sets to solve problems related to named entity recognition, relation extraction, and event modeling.
Alex has an MSc in Computing from Imperial College London and is currently a Ph.D. candidate, with a focus in Computational Linguistics and, more specifically, Word Sense Disambiguation with neural networks. He has worked on information extraction and machine translation projects, as well as on building lexical semantic language resources (such as a Bulgarian version of WordNet). He also has a strong background in Theoretical and Applied Linguistics.
Todor has multiple successful projects behind his back in data integration for life sciences, including highly scalable sequence repositories, semantic meta data integration of biomedical entities, interactive visualization of data. He participated in the specification, implementation, deployment and the support of the first National Health Portal and Integrated Personal Health Record in Bulgaria.
Dimitar has more than 25 years of IT experience, of which 14 years with Ontotext. He is a semantic software architect at the Innovation & Consulting group. Previously he was the product manager of Ontotext GraphDB, and CTO of Ontotext’s Bulgarian search engine Namerimi. He is an expert in Semantic Technologies, Artificial Intelligence, Web Mining, Information Extraction, Linked Open Data, Natural Language Processing, Machine Learning, Semantic Enrichment, and Semantic Search.
Yes, this is a paid training. The price includes a week-long self-paced course, a 5-hour live session with demonstrations, hands-on assignments, and Q&A, and an individual consultation with a Semantic Technology expert. The consultation is optional, i.e. you can either choose to have one or not.
There are three price options on offer:
For detailed pricing, please refer to the price list.
There are a couple of advantages to the training when compared to the freely available Ontotext documentation and webinars.
In addition to the lecturing materials, which teach the basics such as Semantic Technology, RDF Triplestores, SPARQL, cleaning/ingesting/querying and analyzing data, we have introduced a live online session. You can think of it as a virtual classroom. During the live session, we focus on practical implementation scenarios via hands-on demonstration of building a small Proof-of-Concept project with high-level applications on top of a graph database. The demonstration includes building a Lucene connector, implementing a full-text search functionality and some basic data visualization tools.
The presence of a trainer throughout the entire training is important not only for guidance and Q&A but also to ensure that everybody keeps with more or less the same pace.
Another plus is the personal contact and feedback as part of the individual consultation. This session is a chance discuss a specific use case with an expert in the fields of Semantic Technology, Ontology & Vocabulary Management, NLP Engineer, Machine Learning, and Automation. In comparison, the freely available materials on the Ontotext website explain what Semantic Technology is but they don’t necessarily demonstrate the practical implementation.
You can purchase this training with PayPal or via bank transfer. In either case, you need to fill out the registration form. Once this is done, you will be forwarded to a payment page where you will be asked to pay with PayPal or a bank transfer. In order to proceed with the latter, you will be provided with Ontotext’s company details on the payment page.
Yes. All training registrations receive a formal invoice.
If you submit your payment through PayPal, you will be asked to provide billing information. A formal invoice (issued under your name or your organization’s name accordingly) will be emailed within five business days of your registration with an order number, bank payment information and any VAT taxes outlined if applicable.
If you submit your payment information via a bank transfer, please provide bank receipt and billing information to firstname.lastname@example.org to be issued a formal invoice. The formal invoice will be emailed within five business days of submitting your billing information.
If your company or procurement department requires a vendor form or bank information prior to registering for the training, please submit your request to email@example.com.
All payments are non-refundable. It is expected that participants review the course descriptions and schedules in advance of purchase or registration.
Rescheduling and postponement are not an option as this is not a recurring training, and we cannot guarantee if and when such training will be organized again. However, if for some reason you cannot take part in the live session, do let us know. We will keep you in mind when planning the next such training and will inform you in advance if dates are set.
This training is meant to provide data scientists, researchers, product managers and developers with the theoretical and practical knowledge necessary to design a small Proof-of-Concept project that demonstrates the utility of Semantic Technology and a graph database.
Although you will need to have some basic understanding of Semantic Technology, and programming and query languages, no detailed knowledge is required. All advanced concepts exposed in the training will be explained in sufficient detail.
The training consists of three parts that equal to a total of 9.5+1 teaching hours.
Part I is a self-paced course and starts one week prior to Part II. Part II is a live session, and is scheduled on a specific date and time. Part III of the training, the individual consultation takes place after the live session. The participant has two weeks to schedule the consultation on a preferred date and time.
The first part covers a broad range of advantages that Semantic Technology offers such as the integration of dynamic data from virtually unlimited sources, flexible data modeling, automated knowledge discovery, and data integration with Linked Open Data resources. Participants have one week to cover the video materials and assignments that are required for the live session.
In the live session, the focus is put on practical implementation scenarios via a hands-on demonstration of loading/transforming/querying and linking data, and a showcase of the end product, which is a small Proof-of-Concept project with high-level applications built on top of a graph database. In addition, there is a 30-minute Q&A session at the end. The live session lasts 5 hours in total and is interrupted by short breaks – two 10-minute breaks, and one 20-minute break in the middle.
Finally, the individual consultation (if you have selected to have one upon registration) provides a great opportunity to address questions and challenges that are specific to your project, as well as receive guidance for further implementation and development. The session lasts about 1 hour.
In case you decide to take advantage of the individual consultation, we will ask you to share detailed information about the project you’re working on in order to provide relevant feedback and guidance for further implementation. To address any concerns you might have regarding confidentiality, we are ready to sign a mutual non-disclosure agreement (NDA).
We can provide a template, work with a document provided by your Legal Department or work out a mutual one. In case of the last two, the timeframe necessary to have the document reviewed by our Legal Department is five working days.
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