Global Certificate in Textual Data Analytics
-- viewing nowThe 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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Course Details
• 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.
Career Path
Entry Requirements
- Basic understanding of the subject matter
- Proficiency in English language
- Computer and internet access
- Basic computer skills
- Dedication to complete the course
No prior formal qualifications required. Course designed for accessibility.
Course Status
This course provides practical knowledge and skills for professional development. It is:
- Not accredited by a recognized body
- Not regulated by an authorized institution
- Complementary to formal qualifications
You'll receive a certificate of completion upon successfully finishing the course.
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