Udemy – NLP in Python: Probability Models, Statistics, Text Analysis 2025-2

Apr 18, 2025 - 18:44

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NLP in Python: Probability Models, Statistics, Text Analysis. This comprehensive, hands-on course teaches you how to master natural language processing (NLP) using probability-based approaches with the Python programming language. Whether you’re a data scientist, software engineer, or machine learning enthusiast, this course will take you from beginner to NLP expert. Whether you want to improve your career prospects in data science, enhance your organization’s text analysis capabilities, or simply understand the mathematics behind modern NLP systems, this course offers the right balance of theory and practical implementation.

What you will learn:

Design and deploy a complete sentiment analysis pipeline for analyzing customer opinions, combining rules-based and machine learning approaches
Mastery of text preprocessing techniques and feature extraction methods, including TF-IDF, Word Embeddings, and implementation of custom text classification systems
Developing production-ready Named Entity Recognition systems using probabilistic approaches and integrating them with modern NLP libraries such as spaCy
Create and train complex language models using Bayesian methods, including Naive Bayes classifiers and Bayesian networks for text analysis.
Building a comprehensive e-commerce opinion analysis system that combines sentiment analysis, entity recognition, and topic modeling in a real-world application
Build and implement probability-based natural language processing models from scratch using Python, including N-grams, Hidden Markov Models (HMMs), and PCFGs

This course is suitable for people who:

Data scientists and analysts who want to add text processing and natural language analysis to their skill set, especially those working with customer feedback or document analysis
Software developers looking to enter the field of natural language processing, especially those interested in building text analysis features into their applications
Machine learning engineers seeking expertise in probabilistic language models and text classification systems for production environments
Students and academics in computer science, linguistics, or data science who are looking for hands-on experience with practical NLP implementations and real-world projects
Business professionals from any field who work with text data and want to automate text analysis tasks, even with limited programming experience

Course details NLP in Python: Probability Models Statistics Text Analysis

Publisher: Udemy
Instructor: Meta Brains , Skool of AI
Training level: Beginner to advanced
Training duration: 6 hours and 24 minutes
Number of lessons: 56

Course headings

Prerequisites for the NLP in Python: Probability Models Statistics Text Analysis course

Basic Python programming experience – familiarity with functions, loops, and data structures. No advanced Python knowledge required.
Understanding of basic probability and statistics concepts (mean, variance, distributions). High school level math is sufficient.
A computer with Python 3.7+ installed. All required libraries will be covered in the setup section of the course.
Basic understanding of data structures and algorithms. If you can work with lists and dictionaries in Python, you’re ready.
No prior Natural Language Processing or Machine Learning experience needed – we’ll build from the ground up.
Complete beginners welcome! Each concept is explained step-by-step with practical examples and guided projects. These requirements: Set realistic expectations Keep the barrier to entry low Specify exact technical needs Encourage beginners to join Highlight the course’s supportive approach Would you like me to adjust any of these requirements to better match your target audience? CopyRetryClaude can make mistakes. Please double-check responses.