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Professional Certificate in Sentiment Classification Basics
-- ViewingNowThe Professional Certificate in Sentiment Classification Basics is a comprehensive course designed to equip learners with essential skills in sentiment analysis. This certificate course is crucial in today's data-driven world, where businesses rely heavily on customer feedback and opinions to make informed decisions.
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- Introduction to Sentiment Analysis and its Applications
- Sentiment Classification Techniques: Lexicon-based and Machine Learning Approaches
- Text Preprocessing for Sentiment Analysis: Cleaning and Normalization
- Feature Engineering for Sentiment Classification: N-grams and TF-IDF
- Building a Sentiment Classifier using Python and Scikit-learn
- Evaluating Sentiment Classification Models: Accuracy, Precision, Recall, and F1-Score
- Handling Negation and Context in Sentiment Analysis
- Advanced Sentiment Analysis: Aspect-Based Sentiment Analysis and Emotion Detection
- Deploying a Sentiment Classification Model
- Case Studies and Real-world Applications of Sentiment Classification
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Job Role Description Salary Range (GBP) Sentiment Analyst (NLP, Machine Learning) Analyze text data to understand customer opinions and brand perception.
Develop and implement sentiment analysis models. £35,000 - £65,000 Data Scientist (Sentiment Classification, Python) Build and deploy machine learning models for sentiment classification, contributing to business decision-making. £45,000 - £80,000 Machine Learning Engineer (Natural Language Processing, Sentiment Analysis) Design, develop and maintain machine learning systems for sentiment analysis, focusing on scalability and efficiency. £55,000 - £90,000 NLP Specialist (Text Mining, Sentiment Classification) Focus on developing and improving natural language processing techniques for tasks like sentiment analysis and text summarization. £40,000 - £75,000
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- BasicUnderstandingSubject
- ProficiencyEnglish
- ComputerInternetAccess
- BasicComputerSkills
- DedicationCompleteCourse
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- ThreeFourHoursPerWeek
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