Natural Language Processing (NLP) Training in Aberdeen

Natural Language Processing (NLP) Training in Aberdeen

Local, instructor-led live Natural Language Processing (NLP) training courses demonstrate through interactive discussion and hands-on practice how to extract insights and meaning from this data. Utilizing different programmeming languages such as Python and R and Natural Language Processing (NLP) libraries, our trainings combine concepts and techniques from computer science, artificial intelligence, and computational linguistics to help participants understand the meaning behind text data. NLP trainings walk participants step-by-step through the process of evaluating and applying the right algorithms to analyze data and report on its significance. NLP training is available as "onsite live training" or "remote live training". Onsite live training can be carried out locally on customer premises in Aberdeen or in NobleProg corporate training centres in Aberdeen. Remote live training is carried out by way of an interactive, remote desktop. NobleProg -- Your Local Training Provider

Aberdeen - Berry Street
Learn Natural Language Processing (NLP) in our training center in Aberdeen. The Berry Street Centre occupies a three-storey 1950s building, which has recently been refurbished to a high specification. It is in a prominent and convenient location in the heart of Aberdeen's busy and thriving retail and business area and close to all amenities. The off-shore oil capital of Europe, Aberdeen is known for its outward looking, pioneering spirit. Over the last 30 years, the city has reinvented itself from a regional port dependent upon fishing, farming and tourism, to become... Read more

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Natural Language Processing (NLP) Subcategories

Natural Language Processing (NLP) Course Events - Aberdeen

CodeNameVenueDurationCourse DateCourse Price [Remote / Classroom]
tsflw2vNatural Language Processing with TensorFlowAberdeen - Berry Street35 hoursMon, 2018-10-29 09:30£6500 / £8150
chatbotpythonBuilding Chatbots in PythonAberdeen - Berry Street21 hoursMon, 2018-10-29 09:30£3300 / £4290
python_nltkNatural Language Processing with PythonAberdeen - Berry Street28 hoursMon, 2018-10-29 09:30£5200 / £6520
textsumText Summarization with PythonAberdeen - Berry Street14 hoursTue, 2018-10-30 09:30£2200 / £2860
nlgPython for Natural Language GenerationAberdeen - Berry Street21 hoursMon, 2018-11-05 09:30£3900 / £4890
dlfornlpDeep Learning for NLP (Natural Language Processing)Aberdeen - Berry Street28 hoursMon, 2018-11-12 09:30£5200 / £6520
NPL_LBGNatural Language Processing - AI/RoboticsAberdeen - Berry Street21 hoursWed, 2018-11-14 09:30£3900 / £4890
python_nlpNatural Language Processing with Deep Dive in Python and NLTKAberdeen - Berry Street35 hoursMon, 2018-11-19 09:30£6500 / £8150
nlpNatural Language ProcessingAberdeen - Berry Street21 hoursTue, 2018-11-20 09:30£3900 / £4890
aiintArtificial Intelligence OverviewAberdeen - Berry Street7 hoursFri, 2018-11-30 09:30£1300 / £1630
aitechArtificial Intelligence - the most applied stuff - Data Analysis + Distributed AI + NLPAberdeen - Berry Street21 hoursMon, 2018-12-10 09:30£3900 / £4890
nlpwithrNLP: Natural Language Processing with RAberdeen - Berry Street21 hoursMon, 2018-12-10 09:30£3900 / £4890
opennlpOpenNLP for Text Based Machine LearningAberdeen - Berry Street14 hoursWed, 2018-12-12 09:30£2600 / £3260
w2vdl4jNLP with Deeplearning4jAberdeen - Berry Street14 hoursMon, 2018-12-17 09:30£2600 / £3260
pythontextmlPython: Machine Learning with TextAberdeen - Berry Street21 hoursTue, 2018-12-18 09:30£3900 / £4890
nlgPython for Natural Language GenerationAberdeen - Berry Street21 hoursWed, 2018-12-26 09:30£3900 / £4890
chatbotpythonBuilding Chatbots in PythonAberdeen - Berry Street21 hoursWed, 2018-12-26 09:30£3300 / £4290
textsumText Summarization with PythonAberdeen - Berry Street14 hoursWed, 2018-12-26 09:30£2200 / £2860
python_nltkNatural Language Processing with PythonAberdeen - Berry Street28 hoursMon, 2018-12-31 09:30£5200 / £6520
tsflw2vNatural Language Processing with TensorFlowAberdeen - Berry Street35 hoursMon, 2018-12-31 09:30£6500 / £8150
NPL_LBGNatural Language Processing - AI/RoboticsAberdeen - Berry Street21 hoursMon, 2019-01-07 09:30£3900 / £4890
dlfornlpDeep Learning for NLP (Natural Language Processing)Aberdeen - Berry Street28 hoursTue, 2019-01-08 09:30£5200 / £6520
python_nlpNatural Language Processing with Deep Dive in Python and NLTKAberdeen - Berry Street35 hoursMon, 2019-01-14 09:30£6500 / £8150
aiintArtificial Intelligence OverviewAberdeen - Berry Street7 hoursMon, 2019-01-21 09:30£1300 / £1630
nlpNatural Language ProcessingAberdeen - Berry Street21 hoursWed, 2019-01-23 09:30£3900 / £4890
nlpwithrNLP: Natural Language Processing with RAberdeen - Berry Street21 hoursWed, 2019-01-30 09:30£3900 / £4890
aitechArtificial Intelligence - the most applied stuff - Data Analysis + Distributed AI + NLPAberdeen - Berry Street21 hoursMon, 2019-02-04 09:30£3900 / £4890
w2vdl4jNLP with Deeplearning4jAberdeen - Berry Street14 hoursTue, 2019-02-05 09:30£2600 / £3260
opennlpOpenNLP for Text Based Machine LearningAberdeen - Berry Street14 hoursWed, 2019-02-06 09:30£2600 / £3260
pythontextmlPython: Machine Learning with TextAberdeen - Berry Street21 hoursMon, 2019-02-18 09:30£3900 / £4890

Natural Language Processing (NLP) Course Outlines in Aberdeen

CodeNameDurationOverview
aiintArtificial Intelligence Overview7 hoursThis course has been created for managers, solutions architects, innovation officers, CTOs, software architects and anyone who is interested in an overview of applied artificial intelligence and the nearest forecast for its development.
nlpNatural Language Processing21 hoursThis course has been designed for people interested in extracting meaning from written English text, though the knowledge can be applied to other human languages as well.

The course will cover how to make use of text written by humans, such as blog posts, tweets, etc...

For example, an analyst can set up an algorithm which will reach a conclusion automatically based on extensive data source.
python_nltkNatural Language Processing with Python28 hoursThis course introduces linguists or programmers to NLP in Python. During this course we will mostly use nltk.org (Natural Language Tool Kit), but also we will use other libraries relevant and useful for NLP. At the moment we can conduct this course in Python 2.x or Python 3.x. Examples are in English or Mandarin (普通话). Other languages can be also made available if agreed before booking.
tsflw2vNatural Language Processing with TensorFlow35 hoursTensorFlow™ is an open source software library for numerical computation using data flow graphs.

SyntaxNet is a neural-network Natural Language Processing framework for TensorFlow.

Word2Vec is used for learning vector representations of words, called "word embeddings". Word2vec is a particularly computationally-efficient predictive model for learning word embeddings from raw text. It comes in two flavors, the Continuous Bag-of-Words model (CBOW) and the Skip-Gram model (Chapter 3.1 and 3.2 in Mikolov et al.).

Used in tandem, SyntaxNet and Word2Vec allows users to generate Learned Embedding models from Natural Language input.

Audience

This course is targeted at Developers and engineers who intend to work with SyntaxNet and Word2Vec models in their TensorFlow graphs.

After completing this course, delegates will:

- understand TensorFlow’s structure and deployment mechanisms
- be able to carry out installation / production environment / architecture tasks and configuration
- be able to assess code quality, perform debugging, monitoring
- be able to implement advanced production like training models, embedding terms, building graphs and logging
w2vdl4jNLP with Deeplearning4j14 hoursDeeplearning4j is an open-source, distributed deep-learning library written for Java and Scala. Integrated with Hadoop and Spark, DL4J is designed to be used in business environments on distributed GPUs and CPUs.

Word2Vec is a method of computing vector representations of words introduced by a team of researchers at Google led by Tomas Mikolov.

Audience

This course is directed at researchers, engineers and developers seeking to utilize Deeplearning4J to construct Word2Vec models.
aitechArtificial Intelligence - the most applied stuff - Data Analysis + Distributed AI + NLP21 hoursThis course is aimed at developers and data scientists who wish to understand and implement AI within their applications. Special focus is given to Data Analysis, Distributed AI and NLP.
nlpwithrNLP: Natural Language Processing with R21 hoursIt is estimated that unstructured data accounts for more than 90 percent of all data, much of it in the form of text. Blog posts, tweets, social media, and other digital publications continuously add to this growing body of data.

This course centers around extracting insights and meaning from this data. Utilizing the R Language and Natural Language Processing (NLP) libraries, we combine concepts and techniques from computer science, artificial intelligence, and computational linguistics to algorithmically understand the meaning behind text data. Data samples are available in various languages per customer requirements.

By the end of this training participants will be able to prepare data sets (large and small) from disparate sources, then apply the right algorithms to analyze and report on its significance.

Audience
Linguists and programmers

Format of the course
Part lecture, part discussion, heavy hands-on practice, occasional tests to gauge understanding
pythontextmlPython: Machine Learning with Text21 hoursIn this instructor-led, live training, participants will learn how to use the right machine learning and NLP (Natural Language Processing) techniques to extract value from text-based data.

By the end of this training, participants will be able to:

- Solve text-based data science problems with high-quality, reusable code
- Apply different aspects of scikit-learn (classification, clustering, regression, dimensionality reduction) to solve problems
- Build effective machine learning models using text-based data
- Create a dataset and extract features from unstructured text
- Visualize data with Matplotlib
- Build and evaluate models to gain insight
- Troubleshoot text encoding errors

Audience

- Developers
- Data Scientists

Format of the course

- Part lecture, part discussion, exercises and heavy hands-on practice
nlgPython for Natural Language Generation21 hoursNatural language generation (NLG) refers to the production of natural language text or speech by a computer.

In this instructor-led, live training, participants will learn how to use Python to produce high-quality natural language text by building their own NLG system from scratch. Case studies will also be examined and the relevant concepts will be applied to live lab projects for generating content.

By the end of this training, participants will be able to:

- Use NLG to automatically generate content for various industries, from journalism, to real estate, to weather and sports reporting
- Select and organize source content, plan sentences, and prepare a system for automatic generation of original content
- Understand the NLG pipeline and apply the right techniques at each stage
- Understand the architecture of a Natural Language Generation (NLG) system
- Implement the most suitable algorithms and models for analysis and ordering
- Pull data from publicly available data sources as well as curated databases to use as material for generated text
- Replace manual and laborious writing processes with computer-generated, automated content creation

Audience

- Developers
- Data scientists

Format of the course

- Part lecture, part discussion, exercises and heavy hands-on practice
python_nlpNatural Language Processing with Deep Dive in Python and NLTK35 hoursBy the end of the training the delegates are expected to be sufficiently equipped with the essential python concepts and should be able to sufficiently use NLTK to implement most of the NLP and ML based operations. The training is aimed at giving not just an executional knowledge but also the logical and operational knowledge of the technology therein.
opennlpOpenNLP for Text Based Machine Learning14 hoursThe Apache OpenNLP library is a machine learning based toolkit for processing natural language text. It supports the most common NLP tasks, such as language detection, tokenization, sentence segmentation, part-of-speech tagging, named entity extraction, chunking, parsing and coreference resolution.

In this instructor-led, live training, participants will learn how to create models for processing text based data using OpenNLP. Sample training data as well customized data sets will be used as the basis for the lab exercises.

By the end of this training, participants will be able to:

- Install and configure OpenNLP
- Download existing models as well as create their own
- Train the models on various sets of sample data
- Integrate OpenNLP with existing Java applications

Audience

- Developers
- Data scientists

Format of the course

- Part lecture, part discussion, exercises and heavy hands-on practice
textsumText Summarization with Python14 hoursIn Python Machine Learning, the Text Summarization feature is able to read the input text and produce a text summary. This capability is available from the command-line or as a Python API/Library. One exciting application is the rapid creation of executive summaries; this is particularly useful for organizations that need to review large bodies of text data before generating reports and presentations.

In this instructor-led, live training, participants will learn to use Python to create a simple application that auto-generates a summary of input text.

By the end of this training, participants will be able to:

- Use a command-line tool that summarizes text.
- Design and create Text Summarization code using Python libraries.
- Evaluate three Python summarization libraries: sumy 0.7.0, pysummarization 1.0.4, readless 1.0.17

Audience

- Developers
- Data Scientists

Format of the course

- Part lecture, part discussion, exercises and heavy hands-on practice
dlfornlpDeep Learning for NLP (Natural Language Processing)28 hoursDeep Learning for NLP allows a machine to learn simple to complex language processing. Among the tasks currently possible are language translation and caption generation for photos. DL (Deep Learning) is a subset of ML (Machine Learning). Python is a popular programming language that contains libraries for Deep Learning for NLP.

In this instructor-led, live training, participants will learn to use Python libraries for NLP (Natural Language Processing) as they create an application that processes a set of pictures and generates captions.

By the end of this training, participants will be able to:

- Design and code DL for NLP using Python libraries
- Create Python code that reads a substantially huge collection of pictures and generates keywords
- Create Python Code that generates captions from the detected keywords

Audience

- Programmers with interest in linguistics
- Programmers who seek an understanding of NLP (Natural Language Processing)

Format of the course

- Part lecture, part discussion, exercises and heavy hands-on practice
NPL_LBGNatural Language Processing - AI/Robotics21 hoursThis classroom based training session will explore NLP techniques in conjunction with the application of AI and Robotics in business. Delegates will undertake computer based examples and case study solving exercises using Python
chatbotpythonBuilding Chatbots in Python21 hoursChatBots are computer programs that automatically simulate human responses via chat interfaces. ChatBots help organizations maximize their operations efficiency by providing easier and faster options for their user interactions.

In this instructor-led, live training, participants will learn how to build chatbots in Python.

By the end of this training, participants will be able to:

- Understand the fundamentals of building chatbots
- Build, test, deploy, and troubleshoot various chatbots using Python

Audience

- Developers

Format of the course

- Part lecture, part discussion, exercises and heavy hands-on practice

Note

- To request a customized training for this course, please contact us to arrange.
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Course Discounts

Course Venue Course Date Course Price [Remote / Classroom]
Jenkins: Continuous Integration for Agile Development Manchester, King Street Thu, 2018-10-18 09:30 £2574 / £3224
Introduction to Recommendation Systems Swansea- Princess House Thu, 2018-10-18 09:30 £990 / £1140
Advanced Statistics using SPSS Predictive Analytics Software Birmingham Mon, 2018-10-22 09:30 £5148 / £6448
Building Augmented Reality Applications with Vuforia and Unity Glasgow Wed, 2018-10-24 09:30 £2178 / £2878
Impact Evaluation – Quantitative Analysis London, Hatton Garden Wed, 2018-10-24 09:30 £2574 / £3324
Statistics with SPSS Predictive Analytics Software Cambridge Thu, 2018-11-01 09:30 £2574 / £3024
Programming in Scala Cambridge Thu, 2018-11-01 09:30 £2178 / £2628
CakePHP: Rapid Web Application Development Birmingham Tue, 2018-11-06 09:30 £4356 / £5656
AWS: A Hands-on Introduction to Cloud Computing Brighton Wed, 2018-11-07 09:30 £1287 / £1487
JMeter Fundamentals and JMeter Advanced Edinburgh Training and Conference Venue Mon, 2018-12-03 09:30 £2178 / £2578
HAProxy Administration London, Hatton Garden Mon, 2018-12-03 09:30 £2178 / £2928
Social Media Marketing Oxford Wed, 2018-12-12 09:30 N/A / £1364
Test Automation with Selenium Manchester, King Street Wed, 2018-12-12 09:30 £3267 / £4242

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