Global Certificate in Textual Data Analytics
-- ViewingNowThe Global Certificate in Textual Data Analytics is a comprehensive course designed to empower learners with the essential skills required to thrive in today's data-driven world. This course is critical for individuals seeking to gain a competitive edge in their careers, as textual data analytics has become increasingly important across industries.
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⢠Data Preprocessing for Textual Data: Data cleaning, tokenization, stemming, lemmatization, stop words removal, and vectorization.
⢠Natural Language Processing (NLP): Text processing, part-of-speech tagging, named entity recognition, and sentiment analysis.
⢠Machine Learning for Text Analytics: Supervised and unsupervised learning algorithms, model evaluation, and hyperparameter tuning.
⢠Deep Learning for NLP: Word embeddings, recurrent neural networks (RNNs), long short-term memory (LSTM) networks, and transformers.
⢠Topic Modeling and Text Summarization: Latent Dirichlet allocation (LDA), latent semantic analysis (LSA), and text summarization techniques.
⢠Information Retrieval and Search: Information retrieval models, search algorithms, and ranking strategies.
⢠Text Classification and Clustering: Multi-class and multi-label classification, hierarchical and k-means clustering.
⢠Ethical Considerations in Textual Data Analytics: Bias, fairness, transparency, and privacy concerns.
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