Certificate Programme in Named Entity Recognition for Named Entity Parsing

Thursday, 12 February 2026 17:59:18

International applicants and their qualifications are accepted

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Overview

Overview

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Named Entity Recognition (NER) is crucial for many applications. This Certificate Programme provides comprehensive training in Named Entity Parsing.


Learn to identify and classify entities like names, organizations, and locations within unstructured text. Master NER techniques and algorithms.


Ideal for data scientists, NLP engineers, and anyone working with text data. Develop skills in information extraction and named entity disambiguation.


Gain practical experience with real-world datasets and projects. Named Entity Recognition is essential for today's data-driven world.


Enroll today and unlock the power of Named Entity Recognition! Explore the programme details and start your journey now.

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Named Entity Recognition (NER) is the focus of this intensive Certificate Programme, equipping you with expert-level skills in identifying and classifying named entities within text. Master named entity parsing techniques and learn to build robust NER systems. This programme offers hands-on training with real-world datasets and projects, boosting your career prospects in NLP, data science, and information extraction. Gain a competitive edge with our unique focus on advanced algorithms and cutting-edge tools. Complete the program and unlock exciting job opportunities as an NER specialist. Develop proficiency in Named Entity Recognition and transform your career.

Entry requirements

The program operates on an open enrollment basis, and there are no specific entry requirements. Individuals with a genuine interest in the subject matter are welcome to participate.

International applicants and their qualifications are accepted.

Step into a transformative journey at LSIB, where you'll become part of a vibrant community of students from over 157 nationalities.

At LSIB, we are a global family. When you join us, your qualifications are recognized and accepted, making you a valued member of our diverse, internationally connected community.

Course Content

• Introduction to Named Entity Recognition (NER) and Named Entity Parsing
• Regular Expressions for NER
• Machine Learning for NER: Supervised Learning Techniques
• Deep Learning for NER: Recurrent Neural Networks (RNNs) and Transformers
• Feature Engineering for Improved NER Performance
• Evaluation Metrics for NER Systems: Precision, Recall, F1-score
• Named Entity Recognition using SpaCy and Stanford NER
• Handling Ambiguity and Context in NER
• Advanced NER Techniques: Contextualized Word Embeddings

Assessment

The evaluation process is conducted through the submission of assignments, and there are no written examinations involved.

Fee and Payment Plans

30 to 40% Cheaper than most Universities and Colleges

Duration & course fee

The programme is available in two duration modes:

1 month (Fast-track mode): 140
2 months (Standard mode): 90

Our course fee is up to 40% cheaper than most universities and colleges.

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Awarding body

The programme is awarded by London School of International Business. This program is not intended to replace or serve as an equivalent to obtaining a formal degree or diploma. It should be noted that this course is not accredited by a recognised awarding body or regulated by an authorised institution/ body.

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  • Start this course anytime from anywhere.
  • 1. Simply select a payment plan and pay the course fee using credit/ debit card.
  • 2. Course starts
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Got questions? Get in touch

Chat with us: Click the live chat button

+44 75 2064 7455

admissions@lsib.co.uk

+44 (0) 20 3608 0144



Career path

Career Role (Named Entity Recognition & Parsing) Description
NLP Engineer (Named Entity Recognition) Develop and deploy NER models; crucial for information extraction and knowledge graph construction. High demand in UK tech.
Data Scientist (NER Specialist) Focus on applying NER techniques to various datasets; analysing trends and insights for business decisions. Strong analytical skills needed.
Machine Learning Engineer (Named Entity Parsing) Build and optimize NER parsing pipelines; integrate with broader ML systems. Expertise in Python and relevant libraries essential.
AI Research Scientist (Named Entity Recognition) Conduct cutting-edge research in NER; improving accuracy and efficiency of models. PhD preferred, high salary potential.

Key facts about Certificate Programme in Named Entity Recognition for Named Entity Parsing

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This Certificate Programme in Named Entity Recognition (NER) provides comprehensive training in Named Entity Parsing, equipping participants with the skills to identify and classify named entities within unstructured text data. The program focuses on practical application, enabling students to build robust NER systems.


Learning outcomes include mastering various NER techniques, including rule-based, statistical, and deep learning approaches. Participants will gain proficiency in using NER tools and libraries, and learn to evaluate NER system performance using standard metrics like precision and recall. A solid understanding of Natural Language Processing (NLP) fundamentals is assumed, but the course covers necessary components of information extraction.


The program's duration is typically 6-8 weeks, delivered through a flexible online format. This allows participants to balance their learning with other commitments. The curriculum is designed to be highly engaging, utilizing a combination of theoretical instruction, practical exercises, and real-world case studies.


Named Entity Recognition is highly relevant across diverse industries. From financial institutions using NER for risk assessment and fraud detection to healthcare organizations leveraging it for patient data management, and marketing departments employing it for social media analysis, the demand for skilled NER professionals is continuously growing. This certificate demonstrates a valuable skill set highly sought after in the job market, enhancing career prospects in data science, NLP, and related fields. This program also incorporates training in Machine Learning techniques.


The program offers participants the opportunity to develop a portfolio of projects, demonstrating their mastery of Named Entity Recognition and Named Entity Parsing techniques. This practical experience significantly enhances their job application competitiveness. Upon successful completion, participants receive a certificate of completion, validating their expertise in this critical area of NLP.

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Why this course?

A Certificate Programme in Named Entity Recognition (NER) is increasingly significant for Named Entity Parsing (NEP) professionals in today’s UK market. The rapid growth of data-driven industries necessitates skilled individuals capable of efficiently extracting meaningful information from unstructured text. According to a recent survey (hypothetical data for illustration), 70% of UK businesses now utilize NEP for various applications, from customer service automation to fraud detection. This demand fuels the need for certified NER experts.

Industry Sector NER Adoption Rate (%)
Finance 85
Healthcare 60
Retail 55

The Certificate Programme equips learners with practical skills in various NER techniques, including rule-based, statistical, and deep learning approaches, directly addressing current industry needs. This specialized knowledge becomes highly valuable in building robust NEP pipelines, leading to improved data analysis and decision-making. Graduates are better prepared for roles demanding expertise in Named Entity Recognition and Named Entity Parsing, securing a competitive edge in the evolving UK job market.

Who should enrol in Certificate Programme in Named Entity Recognition for Named Entity Parsing?

Ideal Audience for our Named Entity Recognition (NER) and Named Entity Parsing Certificate Programme Description
Data Scientists Professionals already working with large datasets needing to improve their named entity parsing skills. The UK currently has a growing demand for skilled data scientists, and NER expertise is highly valuable.
NLP Engineers Individuals focusing on natural language processing applications will significantly benefit from mastering named entity recognition techniques and understanding entity parsing. This will allow for more efficient and accurate text analysis.
Software Developers Developers seeking to incorporate advanced text processing capabilities into their applications will find this programme invaluable. The ability to accurately identify and parse named entities is crucial for many applications.
AI/ML Researchers Researchers in AI and machine learning can leverage this programme to enhance their understanding of text analysis and improve the performance of their NLP models. This boosts their competitiveness in the UK's rapidly advancing AI sector.
Graduates & Career Changers Ambitious graduates or career changers aiming for roles in data science, NLP, or AI will gain a competitive edge through this specialised certificate programme. The programme offers a clear career pathway in a rapidly expanding field.