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CODE: NAI06
DURATION: 3 Days | 5 Days | 10 Days
CERTIFICATIONS: CPD
This course focuses on practical methods for analyzing unstructured text using Natural Language Processing (NLP). Participants will learn tasks like text cleaning, sentiment analysis, topic modeling, entity recognition, and classification. The course uses tools like NLTK, spaCy, and scikit-learn. The course is designed for participants to build NLP models and apply them to real-world problems in business and research.
This course is available in the following formats:
Virtual
Classroom
Request this course in a different delivery format.
Course Outcomes
Delegates will gain the knowledge and skills to:
Engage the fundamentals of text mining and NLP.
Preprocess and clean raw text data for analysis.
Perform sentiment analysis, topic modeling, and text classification.
Apply named entity recognition and part-of-speech tagging.
Use popular NLP libraries such as NLTK, spaCy, and scikit-learn.
Build and evaluate machine learning models for text data.
Extract meaningful insights from unstructured text.
Apply NLP techniques to solve real-world business and research problems.
At the end of this course, you’ll understand:
This course is ideal for data analysts, data scientists, machine learning engineers, researchers, business intelligence professionals, and anyone working with large volumes of text data. It is also suitable for professionals in marketing, customer service, healthcare, finance, and academia who want to apply NLP techniques for insights and automation. Basic knowledge of Python and data analysis is recommended.
✓ Modern facilities
✓ Course materials and certificate
✓ Accredited international trainers
✓ Training materials and workbook
✓ Access to online resources
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