Level

Intermediate

Duration

16h / 2 days

Date

Individually arranged

Price

Individually arranged

SpaCy Training

The SpaCy training is an intensive two-day course focused on the practical use of the spaCy library for Natural Language Processing (NLP) in Python. The program is designed so that 80% of the time is dedicated to workshops and 20% to theory. Participants will gain skills in text analysis, building NLP models, and automating language processing using spaCy, working with real-world examples and use cases.

What You Will Learn

  • Install and configure spaCy for NLP
  • Perform basic text operations: tokenization, lemmatization, stopword removal
  • Carry out syntactic analysis, named entity recognition (NER), and sentiment analysis
  • Build and train text classification models with spaCy

Requirements

  • Basic knowledge of Python programming
  • Basic understanding of data processing
  • Ability to work with Python libraries
Who is this training for?
  • logo infoshare Programmers and data engineers wanting to expand into NLP
  • logo infoshare Data scientists and analysts interested in text processing and analysis
  • logo infoshare IT specialists looking to use spaCy for language processing automation

Training Program

  1. Day 1: Introduction to NLP and spaCy Basics

  • Fundamentals of Natural Language Processing (NLP)

    • Introduction to NLP: definitions and applications
    • Overview of NLP tools and techniques
  • Introduction to spaCy

    • Installation and configuration
    • Overview of spaCy modules and core functions
  • Basic Operations in spaCy

    • Text tokenization (words and sentences)
    • Lemmatization and stopword removal
    • Morphological analysis
  • Text Analysis with spaCy

    • Implementing basic text processing operations
    • Analyzing simple text datasets
  1. Day 2: Advanced Techniques and Practical Applications

  • Syntactic and Semantic Analysis

    • Part-of-speech (POS) tagging
    • Dependency parsing and parse trees
  • Named Entity Recognition (NER) and Sentiment Analysis

    • Techniques for recognizing named entities
    • Methods for sentiment analysis in text
  • Building NLP Models with spaCy

    • Creating and training text classification models
    • Using spaCy corpora to build custom NLP models

Contact us

we will organize training for you tailored to your needs

Przemysław Wołosz

Key Account Manager

przemyslaw.wolosz@infoShareAcademy.com

    The controller of your personal data is InfoShare Academy Sp. z o.o. with its registered office in Gdańsk, al. Grunwaldzka 427B, 80-309 Gdańsk, KRS: 0000531749, NIP: 5842742121. Personal data are processed in accordance with information clause.