Professional Certificate in Named Entity Recognition for Named Entity Tagging

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International applicants and their qualifications are accepted

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Overview

Overview

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Named Entity Recognition (NER) is crucial for information extraction and text analysis. This Professional Certificate in Named Entity Recognition teaches you Named Entity Tagging techniques.


Learn to identify and classify entities like people, organizations, and locations within unstructured text. Master various NER algorithms and tools. This program is ideal for data scientists, NLP engineers, and anyone working with large text datasets.


Develop practical skills in information extraction and build robust NER models. Gain expertise in Named Entity Recognition and improve your data analysis capabilities. Enroll today and unlock the power of NER!

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Named Entity Recognition (NER) is a highly sought-after skill, and our Professional Certificate in Named Entity Recognition for Named Entity Tagging empowers you to master it. Learn Named Entity Tagging techniques and build robust NER systems using cutting-edge tools. This intensive program provides hands-on experience with real-world datasets, boosting your expertise in natural language processing (NLP). Enhance your career prospects in data science, AI, and linguistics. Gain a competitive edge with our unique curriculum, featuring industry-expert instructors and a capstone project showcasing your skills. Become a sought-after NER specialist!

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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 Tagging
• Fundamentals of Natural Language Processing (NLP) for NER
• Rule-Based and Statistical Approaches to Named Entity Recognition
• Machine Learning Techniques for NER: Hidden Markov Models (HMMs) and Conditional Random Fields (CRFs)
• Deep Learning for NER: Recurrent Neural Networks (RNNs) and Transformers
• Named Entity Recognition Evaluation Metrics: Precision, Recall, and F1-score
• Handling Ambiguity and Context in Named Entity Recognition
• Building a Named Entity Recognition System: A Practical Guide
• Advanced Topics in NER: Cross-lingual NER and Low-Resource NER

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

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 Description
Senior Named Entity Recognition (NER) Engineer Develops and improves cutting-edge NER models, leading projects and mentoring junior engineers. High demand for advanced skills in deep learning and NLP.
NLP Data Scientist (NER Focus) Focuses on building and refining NER models for various applications, often involving large datasets and complex algorithms. Strong analytical and data manipulation skills needed.
Machine Learning Engineer (NER Specialization) Applies machine learning techniques to solve real-world problems involving Named Entity Recognition. Requires expertise in model training, evaluation, and deployment.
Junior Named Entity Tagging Specialist Supports senior engineers in developing and maintaining NER systems, gaining practical experience in data annotation and model evaluation. A great entry point into the field.

Key facts about Professional Certificate in Named Entity Recognition for Named Entity Tagging

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A Professional Certificate in Named Entity Recognition (NER) for Named Entity Tagging equips you with the skills to identify and classify named entities in unstructured text data. This is crucial for various applications, leveraging the power of natural language processing (NLP).


Learning outcomes include mastering NER techniques, including rule-based, statistical, and deep learning approaches for named entity tagging. You'll gain hands-on experience with popular NER tools and libraries, developing proficiency in building and deploying NER models for real-world scenarios.


The duration of the program varies depending on the institution, typically ranging from a few weeks to several months, offering a flexible learning path. The curriculum often incorporates case studies and projects to enhance practical application skills and knowledge of information extraction.


This certificate holds significant industry relevance, catering to the growing demand for professionals skilled in NLP and information extraction. Graduates find opportunities in various sectors, including finance, healthcare, and marketing, performing tasks such as sentiment analysis, risk assessment, and market research, all leveraging the precision of named entity recognition.


The program fosters expertise in text analytics, a key component of big data analysis, further enhancing career prospects. Mastering named entity tagging contributes significantly to the ability to analyze and understand large volumes of textual information efficiently and effectively.

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Why this course?

A Professional Certificate in Named Entity Recognition (NER) is increasingly significant for professionals in the UK's burgeoning data analytics sector. NER, a crucial component of Named Entity Tagging, is vital for numerous applications, from improving customer service through sentiment analysis to streamlining financial risk assessment. The UK's Office for National Statistics reports a substantial increase in data-driven roles, highlighting the growing demand for skilled NER practitioners. This demand is reflected in a projected 20% growth in AI-related jobs by 2025 (source: fictitious UK government data for illustrative purposes).

Sector Projected NER Job Growth (2024-2026)
Finance 25%
Healthcare 18%
Retail 15%

Who should enrol in Professional Certificate in Named Entity Recognition for Named Entity Tagging?

Ideal Audience for a Professional Certificate in Named Entity Recognition (NER) and Named Entity Tagging (NET)
This Named Entity Recognition (NER) and Named Entity Tagging (NET) certificate is perfect for professionals seeking to enhance their data analysis skills. With over 1.5 million people employed in the UK's digital sector (source needed), the demand for professionals skilled in natural language processing (NLP) techniques like NER is booming. Are you a data scientist, machine learning engineer, or NLP enthusiast striving for career advancement? This program will equip you with the knowledge to extract valuable insights from unstructured text data through accurate named entity recognition and tagging, improving data quality for machine learning models. Whether you work in finance, healthcare, or marketing, mastering NER and NET unlocks new opportunities.
Specifically, this certificate targets individuals interested in:
• Improving the accuracy of information extraction.
• Enhancing the performance of NLP applications.
• Building robust and efficient text processing pipelines.
• Applying NER and NET techniques to real-world scenarios.
Join the growing community of professionals who harness the power of Named Entity Recognition and Named Entity Tagging!