This specialization features Coursera Coach! A smarter way to learn with interactive, real-time conversations that help you test your knowledge, challenge assumptions, and deepen your understanding as you progress through the specialization.
In this hands-on specialization, you’ll gain practical expertise in Natural Language Processing (NLP) and Generative AI using Python. Learn to preprocess text, apply embeddings, build machine learning models, and fine-tune state-of-the-art transformer architectures to create real-world NLP applications.
It begins with foundational NLP concepts like tokenization, Bag of Words, Count Vectorizer, TF-IDF, and lemmatization. You’ll then advance to vector similarity and neural embeddings. The next section focuses on building machine learning models for tasks like spam detection, sentiment analysis, and summarization using Naive Bayes, logistic regression, and TextRank.
Finally, the specialization delves into generative AI tools like Huggingface and OpenAI. You'll learn transformer pipelines, model fine-tuning, retrieval-augmented generation (RAG), and deploy a climate change chatbot using vector databases.
This intermediate-level specialization is ideal for developers, data scientists, and ML practitioners with Python experience. Basic knowledge of machine learning is recommended.
By the end of the specialization, you will be able to build, fine-tune, and deploy advanced NLP solutions using machine learning and generative AI frameworks.
Applied Learning Project
Throughout the specialization, learners will engage in real-world projects such as building spam detection systems, sentiment classifiers, and text summarizers. In the final section, they’ll create and deploy a climate change chatbot using transformers, RAG, and vector databases. These projects emphasize hands-on coding, model evaluation, and application deployment, providing a practical foundation for real-world NLP and AI solutions.
