Technology Training · Artificial Intelligence
Natural Language Processing Training
Teach computers to understand text — text processing, sentiment analysis, named entities, embeddings and transformer models.
- Python
- NLTK
- spaCy
- scikit-learn
Course overview
Natural Language Processing Training Overview
Natural Language Processing (NLP) training covers how computers read, understand and generate human language.
You move from text cleaning and classic NLP techniques to word embeddings and transformer models, and build applications such as sentiment analysis, text classification, entity extraction, summarisation and question answering.
Course syllabus
What You'll Learn in Natural Language Processing Training
- Text preprocessing, tokenisation and normalisation
- Bag of words, TF-IDF and n-grams
- Part-of-speech tagging and parsing
- Named entity recognition
- Sentiment analysis and text classification
- Word embeddings — Word2Vec and GloVe
- Sequence models for language
- Transformers, BERT and GPT models
- Summarisation and question answering
- Evaluating NLP models
Tools & technologies
Tools & Technologies Covered
- Python
- NLTK
- spaCy
- scikit-learn
- Hugging Face Transformers
- PyTorch
Who should join?
Who Should Join Natural Language Processing Training?
Developers
Add search, chat and text analytics to applications.
Data scientists
Work with text and document data.
Linguistics & research students
Apply computational methods to language.
Analysts
Analyse customer feedback, reviews and documents at scale.
Prerequisites: Python programming and basic machine learning knowledge are recommended.
Career paths
Career Opportunities After Natural Language Processing Training
Common roles for professionals with Natural Language Processing skills:
- 01NLP Engineer
- 02Machine Learning Engineer
- 03Conversational AI Developer
- 04Data Scientist
- 05Text Analytics Specialist
Career outcomes depend on your background, practice and the job market. We focus on practical skills and do not promise guaranteed placement.
FAQ
Natural Language Processing: Frequently Asked Questions
What will I learn in the Natural Language Processing course?
The Natural Language Processing training covers text preprocessing, tokenisation and normalisation, bag of words, TF-IDF and n-grams, part-of-speech tagging and parsing, named entity recognition, sentiment analysis and text classification, word embeddings — Word2Vec and GloVe, sequence models for language, Transformers, BERT and GPT models, summarisation and question answering and evaluating NLP models.
Which tools are covered in Natural Language Processing training?
You will work with Python, NLTK, spaCy, scikit-learn, Hugging Face Transformers and PyTorch.
Who can join the Natural Language Processing course?
The course suits developers, data scientists, linguistics & research students and analysts. Python programming and basic machine learning knowledge are recommended.
What jobs can I apply for after learning Natural Language Processing?
Common roles include NLP Engineer, Machine Learning Engineer, Conversational AI Developer, Data Scientist and Text Analytics Specialist. Career outcomes depend on your background, practice and the job market.
How do I get the Natural Language Processing syllabus, duration, fees and batch details?
Contact us on WhatsApp or through the enquiry form and our team will share the current Natural Language Processing syllabus, course duration, fees and upcoming batch details.
Keep Exploring
Related Artificial Intelligence courses
Ready to Start Natural Language Processing Training?
Talk to our team about the Natural Language Processing syllabus, course duration, fees and upcoming batch details.
NLP course | Natural Language Processing course | NLP with Python | text analytics training