Natural Language Processing (NLP)

Course Content:

Fundamentals of Natural Language Processing:
Introduction to NLP and its importance in artificial intelligence.
Basic principles of computational linguistics and language representation.
Statistical and rule-based models for text processing.

Textual Data Preprocessing:
Text cleaning and normalization techniques: tokenization, stemming, lemmatization.
Stop words removal and missing data handling.
Text representation: Bag of Words (Bag of Words), TF-IDF, and Word Embeddings (Word2Vec, GloVe).

Classical NLP models:
Markov and n-gram models for text generation.
Text classification with supervised algorithms such as Naive Bayes, SVM and Random Forest.
Sentiment analysis, spam detection and topic classification.

Deep Learning for NLP:
Recurrent neural networks (RNN) and LSTM for text sequences.
Transformers and BERT: Pretrained models and their adaptation to specific tasks.
GPT (Generative Pre-trained Transformer) applications in text generation and chatbots.

Speech Processing and Speech Recognition:
Introduction to speech signal processing.
Techniques for automatic speech recognition (ASR) and speech synthesis (TTS).
Application of NLP in virtual assistants and dialog systems.

Advanced NLP applications:
Machine Translation (Machine Translation) and its implementation with sequence-to-sequence models.
Text Summarization and summary generation.
Named Entity Recognition (NER) and analysis of relationships between entities.

Ethical Challenges and Considerations in NLP:
Biases in NLP models and how to mitigate them.
Privacy and security in handling textual and speech data.
Ethical considerations in the implementation of NLP technologies.

Final Project:
Development of a comprehensive project in NLP, which may include from the creation of an intelligent chatbot to a sentiment analysis system in social networks.
Presentation and evaluation of the project with feedback from NLP experts.

Additional Benefits:

Certification in Natural Language Processing (NLP):
Upon completion of the course, you will receive a recognized certification that validates your proficiency in advanced NLP techniques, prized in technology industries.

Access to Specialized Tools and Resources:
You’ll gain access to NLP libraries and platforms, exclusive datasets and development environments optimized for language processing.

Mentoring and Networking:
During the course, you will be able to interact with NLP practitioners and experts, participate in webinars and networking events, and receive mentoring for your projects.

Course Duration: 4 months

Modality: 100% online, with live sessions, practical exercises and access to recorded content.