What you will learn in Natural Language Processing Specialization Course
- Gain a comprehensive understanding of Natural Language Processing (NLP) and its applications.
- Learn fundamental NLP techniques like text processing, tokenization, and sentiment analysis.
- Develop machine learning models for NLP tasks, including text classification and named entity recognition.
- Explore deep learning approaches for NLP, including recurrent neural networks (RNNs) and transformers.
- Work with industry-standard NLP libraries such as NLTK, SpaCy, and Hugging Face Transformers.
- Apply NLP to real-world applications, including chatbots, text summarization, and machine translation.
Program Overview
Introduction to Natural Language Processing
⏱️4-6 weeks
- Understand the basics of NLP and its role in AI and data science.
- Learn text preprocessing techniques, tokenization, and part-of-speech tagging.
Text Classification & Sentiment Analysis
⏱️6-8 weeks
- Apply machine learning algorithms for text classification.
- Build a sentiment analysis model using Python and Scikit-Learn.
Deep Learning for NLP
⏱️8-10 weeks
- Explore neural networks, word embeddings, and sequence models.
- Understand transformers, BERT, and GPT for state-of-the-art NLP applications.
Advanced NLP Applications
⏱️10-12 weeks
- Learn how to build chatbots, machine translation models, and text summarization tools.
- Use Hugging Face Transformers and TensorFlow/PyTorch for NLP projects.
Capstone Project: Real-World NLP Application
⏱️12-14 weeks
- Work on a hands-on NLP project using real-world datasets.
- Develop a full NLP pipeline from data preprocessing to model deployment.
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Job Outlook
- NLP is one of the fastest-growing fields in AI, with increasing demand for NLP engineers and data scientists.
- NLP professionals work in tech companies, research labs, and industries like healthcare and finance.
- NLP-related jobs have high salaries, with an average of $100K+ per year for NLP engineers.
- Skills in machine learning, deep learning, and NLP frameworks open doors to careers in AI, data science, and software engineering.
- Growing adoption of chatbots, virtual assistants, and automated text analysis is fueling demand for NLP expertise.
Specification: Natural Language Processing Specialization
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