Advanced Certificate in Text Analytics and Data Mining Techniques
-- ViewingNowThe Advanced Certificate in Text Analytics and Data Mining Techniques is a comprehensive course that equips learners with critical skills in analyzing and interpreting big data. This program is crucial in today's data-driven world, where businesses rely heavily on data for decision-making.
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⢠Advanced Machine Learning Algorithms:
Explore complex machine learning techniques such as deep learning, ensemble methods, and reinforcement learning, and their applications in text analytics and data mining.
⢠Natural Language Processing (NLP):
Understand and apply various NLP techniques, including tokenization, part-of-speech tagging, parsing, semantic analysis, and sentiment analysis.
⢠Text Preprocessing and Feature Engineering:
Master techniques for preparing and transforming text data, including cleaning, normalization, stemming, lemmatization, and feature extraction.
⢠Data Mining Techniques:
Explore data mining methods, such as clustering, association rule mining, and anomaly detection, and their application to text analytics and data mining.
⢠Text Analytics Tools and Libraries:
Get hands-on experience with popular text analytics and data mining tools and libraries, such as NLTK, spaCy, Gensim, and Scikit-learn.
⢠Deep Learning for Text Analytics:
Learn about deep learning models, such as recurrent neural networks, convolutional neural networks, and transformers, and their application to text analytics.
⢠Evaluation Metrics for Text Analytics:
Understand and apply various evaluation metrics, such as accuracy, precision, recall, F1 score, and ROC curves, to assess the performance of text analytics models.
⢠Ethics and Bias in Text Analytics:
Explore the ethical considerations and potential biases in text analytics and data mining, and learn how to address them in practical scenarios.
⢠Big Data Analytics:
Understand and apply big data analytics techniques, such as Hadoop, Spark, and NoSQL databases, to text analytics and data mining.
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