NLP - Machine Learning Online Course

NLP - Machine Learning Online Course

This course is a must-have for technical professionals aiming to master the fast-growing domain of natural language processing (NLP).

You’ll begin with a foundational overview of NLP concepts before progressing through structured sections, each centered around real-world problems. Core algorithms such as Naive Bayes, Logistic Regression, and Latent Dirichlet Allocation (LDA) are introduced with intuitive explanations to build a strong conceptual understanding.

Hands-on exercises and practical projects in Python will help you solidify your skills and apply machine learning techniques to real text data.

By the end of the course, you’ll have a solid grasp of key NLP methodologies and the practical experience needed to confidently apply them in real-world applications.

Who should should take this Course?

The NLP – Machine Learning Online Course is ideal for data scientists, machine learning engineers, AI researchers, and developers who want to specialize in Natural Language Processing. It’s also suitable for students, linguists, and professionals interested in building intelligent applications that can understand, interpret, and generate human language. A solid understanding of Python and basic machine learning concepts is recommended to get the most out of this course.

Course Curriculum

Welcome

• Introduction and Outline
• Special Offer

Getting Set Up

• Where To Get the Code
• How To Succeed in This Course

Spam Detection

• Spam Detection - Problem Description
• Naive Bayes Intuition
• Spam Detection - Exercise Prompt
• Aside: Class Imbalance, ROC, AUC, and F1 Score (pt 1)
• Aside: Class Imbalance, ROC, AUC, and F1 Score (pt 2)
• Spam Detection in Python

Sentiment Analysis

• Sentiment Analysis - Problem Description
• Logistic Regression Intuition (pt 1)
• Multiclass Logistic Regression (pt 2)
• Logistic Regression Training and Interpretation
• Sentiment Analysis - Exercise Prompt
• Sentiment Analysis in Python (pt 1)
• Sentiment Analysis in Python (pt 2)

Text Summarization

• Text Summarization Section Introduction
• Text Summarization Using Vectors
• Text Summarization Exercise Prompt
• Text Summarization in Python
• TextRank Intuition
• TextRank - How It Really Works (Advanced)
• TextRank Exercise Prompt (Advanced)
• TextRank in Python (Advanced)
• Text Summarization in Python - The Easy Way (Beginner)
• Text Summarization Section Summary

Topic Modeling

• Topic Modeling Section Introduction
• Latent Dirichlet Allocation (LDA) - Essentials
• LDA - Code Preparation
• LDA - Maybe Useful Picture (Optional)
• Latent Dirichlet Allocation (LDA) - Intuition (Advanced)
• Topic Modeling with Latent Dirichlet Allocation (LDA) in Python
• Non-Negative Matrix Factorization (NMF) Intuition
• Topic Modeling with Non-Negative Matrix Factorization (NMF) in Python
• Topic Modeling Section Summary

Latent Semantic Analysis (Latent Semantic Indexing)

• LSA / LSI Section Introduction
• SVD (Singular Value Decomposition) Intuition
• LSA / LSI: Applying SVD to NLP
• Latent Semantic Analysis / Latent Semantic Indexing in Python
• LSA / LSI Exercises