Natural Language Processing Specialization

Due to the COVID-19 outbreak our training courses will be taught via an online classroom.

With this training you will receive in-depth knowledge from industry professionals, test your skills with hands-on assignments & demos, and get access to valuable resources and tools.

Natural Language Processing (NLP) has grown into a large subfield of Machine Learning encompassing a rich set of useful techniques. This training aims to give a good introduction of this field, its techniques and common language models.

The NLP training is perfect for companies of all sizes that want to close the data gap and train their employees. You can follow the schedule below in our offices or contact us for a tailor-made program that meets your needs.

Are you interested? Contact us and we will get in touch with you.

Close the Gap with this NLP Specialization

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Who should take this course?

Participants in this training typically have a background in a quantitative subject, analytics or are junior/medior data scientists. Additionally, they should have the ambition to dive deeper into specific machine learning algorithms and language-based techniques. 

In order to get most value out of the training, you have basic experience with machine learning in Python. You should have knowledge about the machine learning workflow and familiarity with concepts such as overfitting/underfitting, scoring metrics and parameter tuning. If you previously followed the Basic Machine Learning training these prerequisites are satisfied.

After the training you receive a Certificate of Completion. 

Training Dates

This NLP specialization consists of 1 full day of theory and training. This training is given in our offices on specific dates. We can also tailor the training and dates if you have specific needs. 

Description of the training

We start off by giving a broad introduction on NLP and its potential applications, before describing the most important preprocessing and feature extraction techniques, such as tokenization, stemming, N-grams, tf-idf and Part Of Speech tagging. This gives us a good foundation before discussing several common models for NLP that incorporate relationships between words, such as Bayesian Models and Word Embeddings.

The training includes theory, demos, and hands-on exercises. After this training you will have gained knowledge about:

  • NLP and potential applications, such as sentiment analysis, machine translation and author profiling
  • Feature extraction
  • Several Models for NLP
  • Hands-on experience with NLP basic feature extraction techniques and building an Author Profiling model

After the training you receive a Certificate of Completion.