Certificate Programme in Named Entity Recognition Basics

Sunday, 28 September 2025 17:44:53

International applicants and their qualifications are accepted

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Overview

Overview

Named Entity Recognition (NER) is crucial for many applications. This Certificate Programme in Named Entity Recognition Basics provides a foundational understanding of NER techniques.


Learn to identify and classify named entities like people, organizations, and locations within text data. This program covers information extraction, natural language processing (NLP), and machine learning concepts relevant to NER.


Designed for beginners and professionals, this course is ideal for data scientists, linguists, and anyone working with text data. Master NER algorithms and build robust NER systems.


Named Entity Recognition is the key to unlocking valuable insights. Enroll today and embark on your journey towards NER expertise!

Named Entity Recognition (NER) is a rapidly growing field, and our Certificate Programme in Named Entity Recognition Basics provides practical, hands-on training. Master the fundamentals of NER, including information extraction and natural language processing (NLP) techniques. This program equips you with in-demand skills for careers in data science, NLP engineering, and AI development. Gain expertise in building NER models and using existing tools, boosting your resume and opening doors to exciting opportunities. Our unique curriculum features real-world case studies and personalized feedback, ensuring you're job-ready after completion. Enroll now and unlock the power of Named Entity Recognition!

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 its applications
• Core Concepts: Entities, Types, and Annotation
• Rule-based NER Systems and their limitations
• Statistical Methods for NER: Hidden Markov Models (HMMs) and Conditional Random Fields (CRFs)
• Machine Learning for NER: Deep Learning approaches and Neural Networks
• Evaluating NER Systems: Precision, Recall, and F1-score
• Named Entity Recognition tools and libraries
• Handling Ambiguity and Context in NER
• Real-world applications of NER: Information Extraction and Question Answering

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

40% Cheaper

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

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+44 75 2064 7455

admissions@lsib.co.uk

+44 (0) 20 3608 0144



Career path

NER Specialist Job Market Trends in the UK

Career Role Description
Named Entity Recognition (NER) Engineer Develops and implements NER models for various applications, including chatbots and sentiment analysis. High demand for Python and machine learning skills.
Data Scientist (NER Focus) Applies NER techniques to extract insights from large datasets for business intelligence and market research. Requires strong statistical modeling and data visualization skills.
NLP and Machine Learning Engineer (NER Specialisation) Builds and deploys complex NLP systems with a focus on NER accuracy and efficiency. Requires expertise in deep learning frameworks like TensorFlow or PyTorch.
Junior NER Developer Assists senior engineers in building and maintaining NER pipelines. A great entry-level role for those learning NER basics.

Key facts about Certificate Programme in Named Entity Recognition Basics

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This Certificate Programme in Named Entity Recognition Basics provides a foundational understanding of NER techniques and their applications. Participants will learn to identify and classify named entities within text data, a crucial skill in various fields.


Learning outcomes include mastering core NER concepts, implementing basic NER algorithms using popular tools and libraries (like spaCy and NLTK), and evaluating the performance of different NER models. You'll gain practical experience through hands-on exercises and projects, building your proficiency in natural language processing (NLP) and machine learning.


The programme's duration is typically four weeks, with flexible online learning modules designed to fit busy schedules. This intensive yet manageable timeframe allows for quick skill acquisition and immediate application in your professional life or research.


Named Entity Recognition is highly relevant across numerous industries. From improving customer service via sentiment analysis to enhancing search engine optimization (SEO) and powering advanced analytics, the applications are vast. This certificate will boost your employability in data science, machine learning engineering, and other related fields requiring NLP expertise.


Upon completion, you'll receive a certificate showcasing your newly acquired Named Entity Recognition skills, bolstering your resume and demonstrating your commitment to professional development in the exciting world of information extraction and text mining.

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Why this course?

A Certificate Programme in Named Entity Recognition Basics is increasingly significant in today's UK market. The rapid growth of big data and the demand for advanced data analytics have created a surge in opportunities for professionals skilled in Natural Language Processing (NLP). Named Entity Recognition (NER), a core component of NLP, is crucial for tasks like information extraction, sentiment analysis, and knowledge graph construction. According to a recent survey, 75% of UK-based data science companies now utilize NER in their operations. This highlights a significant skills gap and growing demand for professionals proficient in NER techniques.

Sector NER Skill Demand
Finance High
Healthcare Medium-High
Retail Medium
Technology High

Who should enrol in Certificate Programme in Named Entity Recognition Basics?

Ideal Audience for Named Entity Recognition (NER) Basics Certificate Programme Description
Data Scientists Leveraging NER for text analysis and machine learning projects, improving the accuracy of data processing and information retrieval. (The UK has seen a 30% increase in data science roles in the last 5 years, according to [Insert credible UK source here]).
NLP Professionals Boosting their expertise in natural language processing by mastering the fundamentals of named entity recognition, enhancing their capabilities in information extraction.
Software Developers Integrating NER capabilities into applications, automating tasks such as data tagging and relationship extraction for improved efficiency.
Linguistics Graduates Applying their linguistic knowledge to real-world problems via information extraction, strengthening their practical skills in computational linguistics.
Business Analysts Using information extraction techniques for improved business intelligence, enhancing decision-making processes.