Executive Development Programme in NLP for Data Analysts

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The Executive Development Programme in NLP for Data Analysts is a certificate course that holds immense importance in today's data-driven world. This programme integrates Natural Language Processing (NLP) and Data Analysis, two of the most in-demand skills in the industry.

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ใ“ใฎใ‚ณใƒผใ‚นใซใคใ„ใฆ

By enrolling in this course, learners will gain a comprehensive understanding of NLP techniques and their application in data analysis. They will be equipped with the skills to extract valuable insights from unstructured data, a task that is increasingly becoming crucial in various industries. The course not only focuses on technical skills but also develops learners' ability to communicate data insights effectively. This combination of technical and soft skills makes learners well-rounded professionals who are highly sought after in the industry. Investing in this course is a strategic move for career advancement. It opens up opportunities in various sectors such as tech, finance, healthcare, and marketing, where NLP and data analysis skills are essential. Start your journey towards becoming a proficient NLP Data Analyst today!

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ๅพ…ๆฉŸๆœŸ้–“ใชใ—

ใ‚ณใƒผใ‚น่ฉณ็ดฐ

โ€ข Introduction to NLP: Understanding the fundamentals of Natural Language Processing, its applications, and potential for data analysis.
โ€ข Data Preprocessing: Techniques for cleaning, preparing, and formatting text data for NLP analysis.
โ€ข Tokenization & Word Embeddings: Learning about tokenization, word embeddings, and their importance in NLP.
โ€ข Sentiment Analysis: Mastering the art of extracting subjective information from text data, enabling analysts to determine the attitude or emotion of the writer.
โ€ข Named Entity Recognition (NER): Understanding how to identify and categorize key information in text, including people, places, and organizations.
โ€ข Topic Modeling: Exploring unsupervised machine learning techniques to discover hidden thematic structures in a text body.
โ€ข Text Classification: Gaining insights into how to classify text data into various categories, enhancing data organization and interpretation.
โ€ข Deep Learning for NLP: Delving into deep learning models, such as Recurrent Neural Networks (RNNs) and Long Short-Term Memory (LSTM) networks, for advanced NLP applications.
โ€ข Evaluation Metrics in NLP: Measuring the performance of NLP models with metrics like accuracy, precision, recall, and F1 score.

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ใ“ใฎใ‚ณใƒผใ‚นใฎๆ”ฏๆ‰•ใ„ใฎใŸใ‚ใซไผš็คพ็”จใฎ่ซ‹ๆฑ‚ๆ›ธใ‚’ใƒชใ‚ฏใ‚จใ‚นใƒˆใ—ใฆใใ ใ•ใ„ใ€‚

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ใ‚ตใƒณใƒ—ใƒซ่จผๆ˜Žๆ›ธใฎ่ƒŒๆ™ฏ
EXECUTIVE DEVELOPMENT PROGRAMME IN NLP FOR DATA ANALYSTS
ใซๆŽˆไธŽใ•ใ‚Œใพใ™
ๅญฆ็ฟ’่€…ๅ
ใงใƒ—ใƒญใ‚ฐใƒฉใƒ ใ‚’ๅฎŒไบ†ใ—ใŸไบบ
London School of International Business (LSIB)
ๆŽˆไธŽๆ—ฅ
05 May 2025
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