Course Outline

Introduction to NLP

  • What is Natural Language Processing?
  • Importance of NLP in modern AI applications
  • Popular libraries for NLP: NLTK, SpaCy, Hugging Face

Text Preprocessing Techniques

  • Tokenization and stop words removal
  • Stemming and lemmatization
  • Text normalization techniques

Sentiment Analysis

  • Introduction to sentiment analysis
  • Performing sentiment analysis with NLTK
  • Using SpaCy for advanced sentiment analysis

Advanced NLP Techniques

  • Named entity recognition (NER)
  • Text classification
  • Language modeling with pre-trained models

Working with Google Colab

  • Introduction to Google Colab environment
  • Setting up and managing NLP projects in Colab
  • Collaborating on NLP tasks in Colab

Real-World Applications of NLP

  • NLP in healthcare, finance, and customer support
  • Using NLP for chatbots and virtual assistants
  • Future trends in NLP research

Summary and Next Steps

Requirements

  • Basic understanding of natural language processing concepts
  • Familiarity with Python programming
  • Experience with Jupyter Notebooks or similar environments

Audience

  • Data scientists
  • Developers with experience in Python
  • AI enthusiasts
 14 Hours

Delivery Options

Private Group Training

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  • Customisation of the learning experience to achieve your goals -
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    • Practical hands-on exercises containing data / scenarios recognisable to the learners
  • Training scheduled on a date of your choice
  • Delivered online, onsite/classroom or hybrid by experts sharing real world experience

Private Group Prices RRP from £3800 online delivery, based on a group of 2 delegates, £1200 per additional delegate (excludes any certification / exam costs). We recommend a maximum group size of 12 for most learning events.

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