- Course Overview - DO NOT SKIP THIS LECTURE PLEASE. IMPORTANT INFO HERE!
- Quick Check
- Curriculum Overview
- Installation and Setup Lecture
- FAQ - Frequently Asked Questions
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Quick facts
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Medium of instructions
English
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Mode of learning
Self study
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Mode of Delivery
Video and Text Based
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Course and certificate fees
Fees information
certificate availability
certificate providing authority
The syllabus
Introduction
Python Text Basics
- Introduction to Python Text Basics
- Working with Text Files with Python - Part One
- Working with Text Files with Python - Part Two
- Working with PDFs
- Regular Expressions Part One
- Regular Expressions Part Two
- Python Text Basics - Assessment Overview
- Python Text Basics - Assessment Solutions
Natural Language Processing Basics
- Introduction to Natural Language Processing
- Spacy Setup and Overview
- What is Natural Language Processing?
- Spacy Basics
- Tokenization - Part one
- Tokenization - Part Two
- Stemming
- Lemmatization
- Stop Words
- Phrase Matching and Vocabulary - Part One
- Phrase Matching and Vocabulary - Part Two
- NLP Basics Assessment Overview
- NLP Basics Assessment Solution
Part of Speech Tagging and Named Entity Recognition
- Introduction to Section on POS and NER
- Part of Speech Tagging
- Visualizing Part of Speech
- Named Entity Recognition - Part One
- Named Entity Recognition - Part Two
- Visualizing Named Entity Recognition
- Sentence Segmentation
- Part Of Speech Assessment
- Part Of Speech Assessment - Solutions
Text Classification
- Introduction to Text Classification
- Machine Learning Overview
- Classification Metrics
- Confusion Matrix
- Scikit-Learn Primer - How to Use SciKit-Learn
- Scikit-Learn Primer - Code Along Part One
- Scikit-Learn Primer - Code Along Part Two
- Text Feature Extraction Overview
- Text Feature Extraction - Code Along Implementations
- Text Feature Extraction - Code Along - Part Two
- Text Classification Code Along Project
- Text Classification Assessment Overview
- Text Classification Assessment Solutions
Semantics and Sentiment Analysis
- Introduction to Semantics and Sentiment Analysis
- Overview of Semantics and Word Vectors
- Semantics and Word Vectors with Spacy
- Sentiment Analysis Overview
- Sentiment Analysis with NLTK
- Sentiment Analysis Code Along Movie Review Project
- Sentiment Analysis Project Assessment
- Sentiment Analysis Project Assessment - Solutions
Topic Modeling
- Introduction to Topic Modeling Section
- Overview of Topic Modeling
- Latent Dirichlet Allocation Overview
- Latent Dirichlet Allocation with Python - Part One
- Latent Dirichlet Allocation with Python - Part Two
- Non-negative Matrix Factorization Overview
- Non-negative Matrix Factorization with Python
- Topic Modeling Project - Overview
- Topic Modeling Project - Solutions
Deep Learning for NLP
- Introduction to Deep Learning for NLP
- The Basic Perceptron Model
- Introduction to Neural Networks
- Keras Basics - Part One
- Keras Basics - Part Two
- Recurrent Neural Network Overview
- LSTMs, GRU, and Text Generation
- Text Generation with LSTMs with Keras and Python - Part One
- Text Generation with LSTMs with Keras and Python - Part Two
- Text Generation with LSTMS with Keras - Part Three
- Chat Bots Overview
- Creating Chat Bots with Python - Part One
- Creating Chat Bots with Python - Part Two
- Creating Chat Bots with Python - Part Three
- Creating Chat Bots with Python - Part Four
Bonus Section: Thank You!
- Bonus Lecture
Instructors
Mr Jose Portilla
Head of Data Science
Udemy
Other Bachelors, M.S