Natural Language Processing (NLP) Training in Astana, Kazakhstan

This training program on Natural Language Processing (NLP) equips participants with the foundational knowledge and hands-on skills required to work with text and language data. Participants will explore the key techniques, tools, and frameworks used in modern NLP to build applications such as chatbots, sentiment analysis models, and text summarization tools. The course combines theoretical learning with practical exercises for a well-rounded experience.

Fundamentals and Preprocessing

• Session 1: Introduction to NLP

  • What is NLP? Overview and real-world applications.
  • NLP pipeline: Steps from preprocessing to deployment.
  • Tools and libraries: Overview of popular NLP frameworks.

• Session 2: Text Preprocessing Techniques

  • Tokenization, stemming, lemmatization, and stopword removal.
  • Vectorization techniques: Bag-of-Words, TF-IDF, and word embeddings.

• Session 3: Machine Learning for NLP

  • Building text classification models using scikit-learn.
  • Introduction to feature extraction for text data.

Advanced NLP Techniques and Applications

• Session 4: Modern NLP and Pre-Trained Models

  • Introduction to word embeddings (Word2Vec, GloVe, and FastText).
  • Overview of transformer-based models (BERT, GPT).

• Session 5: NLP Applications

  • Named entity recognition (NER) and part-of-speech tagging.
  • Text summarization and text generation techniques.

• Session 6: Deployment and Best Practices

  • Fine-tuning pre-trained models for specific use cases.
  • Tips for scaling NLP applications.
  • Future trends in NLP and ethical considerations.
  • Hands-on

This structured program ensures that participants gain practical, industry-relevant NLP skills, empowering them to develop cutting-edge language-processing applications.