Certificate Sentiment Analysis using Twitter Data

Name: Certificate Sentiment Analysis using Twitter Data
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The Certificate in Sentiment Analysis using Twitter Data is a comprehensive course that focuses on the practical application of Natural Language Processing (NLP) and Machine Learning techniques to analyze social media data. This course highlights the importance of sentiment analysis in understanding customer opinions, brand reputation, and market trends.

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AboutThisCourse

In today's data-driven world, there is a high demand for professionals who can extract valuable insights from vast amounts of data. This course equips learners with the essential skills to analyze Twitter data using Python, machine learning algorithms, and sentiment analysis libraries such as TextBlob and NLTK. By the end of this course, learners will have a solid foundation in sentiment analysis and will be able to apply these skills in various industries, including marketing, market research, and data science, thereby enhancing their career prospects. Enroll in this course and gain a competitive edge in the job market by mastering the art of sentiment analysis using Twitter data.

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CourseDetails

• Unit 1: Introduction to Sentiment Analysis
• Unit 2: Twitter Data & its Collection
• Unit 3: Natural Language Processing (NLP) Basics
• Unit 4: Preprocessing Twitter Data
• Unit 5: Sentiment Analysis Techniques using Twitter Data
• Unit 6: Machine Learning Models for Sentiment Analysis
• Unit 7: Deep Learning Models for Sentiment Analysis
• Unit 8: Evaluation Metrics for Sentiment Analysis
• Unit 9: Real-world Applications of Sentiment Analysis on Twitter Data
• Unit 10: Best Practices & Ethics in Sentiment Analysis

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EntryRequirements

BasicUnderstandingSubject
ProficiencyEnglish
ComputerInternetAccess
BasicComputerSkills
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FastTrack GBP £140

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AcceleratedLearningPath

ThreeFourHoursPerWeek
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StandardMode GBP £90

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FlexibleLearningPace

TwoThreeHoursPerWeek
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CERTIFICATE SENTIMENT ANALYSIS USING TWITTER DATA

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London School of International Business (LSIB)

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05 May 2025

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