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Certificate Programme in Sentiment Analysis for Social Media
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CourseDetails
- Introduction to Sentiment Analysis and Social Media
- Text Preprocessing for Sentiment Analysis (tokenization, stemming, lemmatization)
- Sentiment Classification Techniques (machine learning algorithms, lexicon-based approaches)
- Feature Engineering for Sentiment Analysis (n-grams, TF-IDF, word embeddings)
- Building a Sentiment Analysis Model (using Python and relevant libraries)
- Evaluating Sentiment Analysis Models (precision, recall, F1-score, accuracy)
- Advanced Topics in Sentiment Analysis (aspect-based sentiment analysis, emotion detection)
- Sentiment Analysis Applications in Social Media Marketing
- Ethical Considerations in Sentiment Analysis
CareerPath
Job Role Description Sentiment Analyst (Social Media) Analyze social media data to understand public opinion and brand sentiment.
Requires strong natural language processing (NLP) and data analysis skills.
Social Media Data Scientist Extract insights from social media using machine learning and statistical methods.
Focuses on predictive modeling and trend forecasting related to social sentiment.
NLP Engineer (Social Media Focus) Develop and improve NLP models specifically designed for analyzing social media text for sentiment and emotion.
Key skills include sentiment analysis and text mining.
Brand Reputation Manager (Digital) Manage and improve brand reputation leveraging social media sentiment analysis to proactively address negative feedback and improve online presence.
Market Research Analyst (Social Media) Conduct market research using social media data.
Utilizes sentiment analysis techniques to understand customer preferences and product perception.
EntryRequirements
- BasicUnderstandingSubject
- ProficiencyEnglish
- ComputerInternetAccess
- BasicComputerSkills
- DedicationCompleteCourse
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- NotAccreditedRecognized
- NotRegulatedAuthorized
- ComplementaryFormalQualifications
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- ThreeFourHoursPerWeek
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