Natural Language Processing (NLP) Training in Sri Lanka

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.

Welcome to the official Natural Language Processing (NLP) Training certification program. This comprehensive training is designed to elevate your professional skills and provide you with practical, industry-relevant knowledge in in Sri Lanka. As a globally recognized corporate training provider operating in 55+ countries, ProgNXT ensures that our curriculum meets the highest standards of excellence.

Whether you are looking to upskill your team or advance your personal career, our expert-led sessions will guide you through the core concepts of this domain. Upon successful completion of the 14 Hrs program, participants will receive a globally accepted certification, demonstrating their proficiency and readiness to tackle complex challenges in the field.

Participants should have:

• Basic programming skills in Python.
• Familiarity with machine learning concepts and libraries like scikit-learn (preferred but not mandatory).
• Interest in working with text data and natural language.

Participants will gain skills in:

• Text preprocessing techniques: Tokenization, stemming, lemmatization, and stopword removal.
• Building and training machine learning models for text data.
• Utilizing modern NLP libraries and frameworks like spaCy, Hugging Face, and TextBlob.
• Developing applications for tasks such as sentiment analysis, NER, and text generation.
• Implementing language models like BERT for real-world applications.

By the end of this training, participants will:

• Understand the fundamental concepts of NLP and its applications.
• Gain hands-on experience with NLP tools and libraries like NLTK, spaCy, and Hugging Face Transformers.
• Learn techniques for text preprocessing, tokenization, and vectorization.
• Build NLP applications such as text classification, sentiment analysis, and named entity recognition (NER).
• Understand advanced NLP topics, including language models and transfer learning.