Masterclass Certificate in Machine Learning for Sentiment Analysis

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์–ด๋””์„œ๋“  ํ•™์Šต

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์™„๋ฃŒ๊นŒ์ง€ 2๊ฐœ์›”

์ฃผ 2-3์‹œ๊ฐ„

์–ธ์ œ๋“  ์‹œ์ž‘

๋Œ€๊ธฐ ๊ธฐ๊ฐ„ ์—†์Œ

๊ณผ์ • ์„ธ๋ถ€์‚ฌํ•ญ

  • Introduction to Sentiment Analysis and its Applications
  • Text Preprocessing for Sentiment Analysis: Cleaning and Normalization
  • Feature Extraction Techniques for Sentiment Analysis (TF-IDF, Word Embeddings)
  • Machine Learning Models for Sentiment Analysis (Naive Bayes, SVM, Logistic Regression)
  • Deep Learning Models for Sentiment Analysis (RNNs, LSTMs)
  • Evaluating Sentiment Analysis Models: Metrics and Performance
  • Handling Complex Sentiment: Sarcasm, Negation, and Context
  • Sentiment Analysis Case Studies and Best Practices
  • Building a Sentiment Analysis Pipeline
  • Deployment and Real-world Applications of Sentiment Analysis

๊ฒฝ๋ ฅ ๊ฒฝ๋กœ

Career Role Description Machine Learning Engineer (Sentiment Analysis) Develop and deploy machine learning models for sentiment analysis, focusing on NLP and deep learning techniques.

High demand in UK tech.

Data Scientist (Sentiment Analysis Focus) Analyze large datasets using sentiment analysis to extract insights and inform business decisions.

Strong statistical modeling skills required.

AI/ML Consultant (Sentiment Analysis Expertise) Advise clients on the implementation and application of sentiment analysis solutions.

Requires strong communication and consulting skills.

NLP Engineer (Sentiment Analysis Specialist) Specializes in natural language processing, with expertise in building and improving sentiment analysis models.

Highly sought after in the UK.

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์™œ ์‚ฌ๋žŒ๋“ค์ด ๊ฒฝ๋ ฅ์„ ์œ„ํ•ด ์šฐ๋ฆฌ๋ฅผ ์„ ํƒํ•˜๋Š”๊ฐ€

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์ด ๊ณผ์ •์˜ ๋น„์šฉ์„ ์ง€๋ถˆํ•˜๊ธฐ ์œ„ํ•ด ํšŒ์‚ฌ๋ฅผ ์œ„ํ•œ ์ฒญ๊ตฌ์„œ๋ฅผ ์š”์ฒญํ•˜์„ธ์š”.

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์ƒ˜ํ”Œ ์ธ์ฆ์„œ ๋ฐฐ๊ฒฝ
MASTERCLASS CERTIFICATE IN MACHINE LEARNING FOR SENTIMENT ANALYSIS
์—๊ฒŒ ์ˆ˜์—ฌ๋จ
ํ•™์Šต์ž ์ด๋ฆ„
์—์„œ ํ”„๋กœ๊ทธ๋žจ์„ ์™„๋ฃŒํ•œ ์‚ฌ๋žŒ
London School of International Business (LSIB)
์ˆ˜์—ฌ์ผ
05 May 2025
๋ธ”๋ก์ฒด์ธ ID: s-1-a-2-m-3-p-4-l-5-e
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