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In this post, I will share some of the best Natural Language Processing courses available on Udemy for Programmers and Software Engineers. In the first section, you will find a quick list, and in the next section, each course is described in detail. Please have a look:
Are you interested in learning more about Natural Language Processing courses? Check out the details below to see which Natural Language Processing course is right for you.
Best Natural Language Processing Courses on Udemy
NLP - Natural Language Processing with Python
★★★★★
$17.00 in stock
Udemy.com
as of July 17, 2024 10:00 am
Learn to use Machine Learning, Spacy, NLTK, SciKit-Learn, Deep Learning, and more to conduct Natural Language Processing
Created by: Jose Portilla
Head of Data Science at Pierian Training
Head of Data Science at Pierian Training
Rating:4.62 (12043reviews)
61751students enrolled
What Will I Learn?
- Learn to work with Text Files with Python
- Learn how to work with PDF files in Python
- Utilize Regular Expressions for pattern searching in text
- Use Spacy for ultra fast tokenization
- Learn about Stemming and Lemmatization
- Understand Vocabulary Matching with Spacy
- Use Part of Speech Tagging to automatically process raw text files
- Understand Named Entity Recognition
- Visualize POS and NER with Spacy
- Use SciKit-Learn for Text Classification
- Use Latent Dirichlet Allocation for Topic Modelling
- Learn about Non-negative Matrix Factorization
- Use the Word2Vec algorithm
- Use NLTK for Sentiment Analysis
- Use Deep Learning to build out your own chat bot
Requirements
- Understand general Python
- Have permissions to install python packages onto computer
- Internet connection
Target audience
- Python developers interested in learning how to use Natural Language Processing.
Machine Learning: Natural Language Processing in Python (V2)
★★★★★
$18.00 in stock
Udemy.com
as of July 17, 2024 10:00 am
NLP: Use Markov Models, NLTK, Artificial Intelligence, Deep Learning, Machine Learning, and Data Science in Python
Created by: Lazy Programmer Inc.
Artificial intelligence and machine learning engineer
Artificial intelligence and machine learning engineer
Created by: Lazy Programmer Team
Artificial Intelligence and Machine Learning Engineer
Artificial Intelligence and Machine Learning Engineer
Rating:4.76 (1375reviews)
6476students enrolled
What Will I Learn?
- How to convert text into vectors using CountVectorizer, TF-IDF, word2vec, and GloVe
- How to implement a document retrieval system / search engine / similarity search / vector similarity
- Probability models, language models and Markov models (prerequisite for Transformers, BERT, and GPT-3)
- How to implement a cipher decryption algorithm using genetic algorithms and language modeling
- How to implement spam detection
- How to implement sentiment analysis
- How to implement an article spinner
- How to implement text summarization
- How to implement latent semantic indexing
- How to implement topic modeling with LDA, NMF, and SVD
- Machine learning (Naive Bayes, Logistic Regression, PCA, SVD, Latent Dirichlet Allocation)
- Deep learning (ANNs, CNNs, RNNs, LSTM, GRU) (more important prerequisites for BERT and GPT-3)
- Hugging Face Transformers (VIP only)
- How to use Python, Scikit-Learn, Tensorflow, +More for NLP
- Text preprocessing, tokenization, stopwords, lemmatization, and stemming
- Parts-of-speech (POS) tagging and named entity recognition (NER)
Requirements
- Install Python, it's free!
- Decent Python programming skills
- Optional: If you want to understand the math parts, linear algebra and probability are helpful
Target audience
- Anyone who wants to learn natural language processing (NLP)
- Anyone interested in artificial intelligence, machine learning, deep learning, or data science
- Anyone who wants to go beyond typical beginner-only courses on Udemy
Deep Learning: Advanced Natural Language Processing and RNNs
★★★★★
$23.00 in stock
Udemy.com
as of July 17, 2024 10:00 am
Natural Language Processing (NLP) with Sequence-to-sequence (seq2seq), Attention, CNNs, RNNs, and Memory Networks!
Created by: Lazy Programmer Inc.
Artificial intelligence and machine learning engineer
Artificial intelligence and machine learning engineer
Rating:4.62 (4818reviews)
26467students enrolled
What Will I Learn?
- Build a text classification system (can be used for spam detection, sentiment analysis, and similar problems)
- Build a neural machine translation system (can also be used for chatbots and question answering)
- Build a sequence-to-sequence (seq2seq) model
- Build an attention model
- Build a memory network (for question answering based on stories)
Requirements
- Understand what deep learning is for and how it is used
- Decent Python coding skills, especially tools for data science (Numpy, Matplotlib)
- Preferable to have experience with RNNs, LSTMs, and GRUs
- Preferable to have experience with Keras
- Preferable to understand word embeddings
Target audience
- Students in machine learning, deep learning, artificial intelligence, and data science
- Professionals in machine learning, deep learning, artificial intelligence, and data science
- Anyone interested in state-of-the-art natural language processing
Natural Language Processing: NLP With Transformers in Python
★★★★★
$16.00 in stock
Udemy.com
as of July 17, 2024 10:00 am
Learn next-generation NLP with transformers for sentiment analysis, Q&A, similarity search, NER, and more
Created by: James Briggs
ML Engineer
ML Engineer
Rating:4.56 (970reviews)
18236students enrolled
What Will I Learn?
- Industry standard NLP using transformer models
- Build full-stack question-answering transformer models
- Perform sentiment analysis with transformers models in PyTorch and TensorFlow
- Advanced search technologies like Elasticsearch and Facebook AI Similarity Search (FAISS)
- Create fine-tuned transformers models for specialized use-cases
- Measure performance of language models using advanced metrics like ROUGE
- Vector building techniques like BM25 or dense passage retrievers (DPR)
- An overview of recent developments in NLP
- Understand attention and other key components of transformers
- Learn about key transformers models such as BERT
- Preprocess text data for NLP
- Named entity recognition (NER) using spaCy and transformers
- Fine-tune language classification models
Requirements
- Knowledge of Python
- Experience in data science a plus
- Experience in NLP a plus
Target audience
- Aspiring data scientists and ML engineers interested in NLP
- Practitioners looking to upgrade their skills
- Developers looking to implement NLP solutions
- Data scientist
- Machine Learning Engineer
- Python Developers
Natural Language Processing: Machine Learning NLP In Python
★★★★★
$14.00 in stock
Udemy.com
as of July 17, 2024 10:00 am
A Complete Beginner NLP Syllabus. Practicals: Linguistics, Flask,Sentiment, Scrape Tweets, Chatbot, Hugging Face & more!
Created by: Nidia Sahjara
NLP Engineer & Researcher
NLP Engineer & Researcher
Created by: Rajeev D. Ratan
Data Scientist, Computer Vision Expert & Electrical Engineer
Data Scientist, Computer Vision Expert & Electrical Engineer
Rating:4.44 (266reviews)
2228students enrolled
What Will I Learn?
- Use Flask to Deploy A Sentiment Analysis Model To A Web Interface
- Libraries: Hugging Face, NLTK, SpaCy, Keras, Sci-kit Learn, Tensorflow, Pytorch, Twint
- Linguistics Foundation To Help Learn NLP Concepts
- Deep Learning: Neural Networks, RNN, LSTM Theory & Practical Projects
- Scrape Unlimited Tweets Using An Open Source Intelligence Tool
- Machine Reading Comprehension: Create A Question Answering System with SQuAD
- No Tedious Anaconda or Jupyter Installs: Use Modern Google Colab Cloud-Based Notebooks for using Python
- How To Build Generative AI Chatbots
- Create A Netflix Recommendation System With Word2Vec
- Perform Sentiment Analysis on Steam Game Reviews
- Convert Speech To Text
- Machine Learning Modelling Techniques
- Markov Property - Theory & Practical
- Optional Python For Beginners Section
- Cosine-Similarity & Vectors
- Word Embeddings: My Favourite Topic Taught In Depth
- Speech Recognition
- LSTM Fake News Detector
- Context-Free Grammar Syntax
- Scrape Wikipedia & Create An Article Summarizer
Requirements
- No Tedious Installs
- No previous programming knowledge necessary. The lectures slowly explain the python syntax as you code alone with me.
- New to Python: you get explanations of the code as you code along with me but not only that - theory slides explain concepts to help you understand what's going on behind the code.
- No data science knowledge required: lectures teach how to work with data and key modelling concepts.
- No NLP knowledge required. Linguistic concepts are taught to give a strong foundation of NLP even before you get into practical coding. This helps you to grasp NLP modelling techniques and cleaning concepts better.
Target audience
- Anyone who is curious about data science & NLP
- Those who are in the Business & Marketing world - learn use NLP to gain insight into customers & products. Can help at interviews & job promotions.
- If you intend to enrol in an NLP/Data Science course but are a total newbie, complete this course before to avoid being lost in class since it can seem overwhelming if classmates already have a foundation in Python or Datascience.
2022 Natural Language Processing in Python for Beginners
★★★★★
$16.00 in stock
Udemy.com
as of July 17, 2024 10:00 am
Text Cleaning, Spacy, NLTK, Scikit-Learn, Deep Learning, word2vec, GloVe, LSTM for Sentiment, Emotion, Spam & CV Parsing
Created by: Laxmi Kant
Principal Data Scientist at mBreath and KGPTalkie
Principal Data Scientist at mBreath and KGPTalkie
Rating:4.24 (503reviews)
5322students enrolled
What Will I Learn?
- Learn complete text processing with Python
- Learn how to extract text from PDF files
- Use Regular Expressions for search in text
- Use SpaCy and NLTK to extract complete text features from raw text
- Use Latent Dirichlet Allocation for Topic Modelling
- Use Scikit-Learn and Deep Learning for Text Classification
- Learn Multi-Class and Multi-Label Text Classification
- Use Spacy and NLTK for Sentiment Analysis
- Understand and Build word2vec and GloVe based ML models
- Use Gensim to obtain pretrained word vectors and compute similarities and analogies
- Learn Text Summarization and Text Generation using LSTM and GRU
Requirements
- Have a desire to learn
- Elementary level math
- Have basic understanding of Python and Machine Learning
Target audience
- Beginners in Natural Language Processing
- Data Scientist curious to learn NLP
Data Science: Transformers for Natural Language Processing
★★★★★
$74.99 in stock
Udemy.com
as of July 17, 2024 10:00 am
BERT, GPT, Deep Learning, Machine Learning, & NLP with Hugging Face, Attention in Python, Tensorflow, PyTorch, & Keras
Created by: Lazy Programmer Team
Artificial Intelligence and Machine Learning Engineer
Artificial Intelligence and Machine Learning Engineer
Created by: Lazy Programmer Inc.
Artificial intelligence and machine learning engineer
Artificial intelligence and machine learning engineer
Rating:4.83 (278reviews)
1388students enrolled
What Will I Learn?
- Apply transformers to real-world tasks with just a few lines of code
- Fine-tune transformers on your own datasets with transfer learning
- Sentiment analysis, spam detection, text classification
- NER (named entity recognition), parts-of-speech tagging
- Build your own article spinner for SEO
- Generate believable human-like text
- Neural machine translation and text summarization
- Question-answering (e.g. SQuAD)
- Zero-shot classification
- Understand self-attention and in-depth theory behind transformers
- Implement transformers from scratch
- Use transformers with both Tensorflow and PyTorch
- Understand BERT, GPT, GPT-2, and GPT-3, and where to apply them
- Understand encoder, decoder, and seq2seq architectures
- Master the Hugging Face Python library
Requirements
- Install Python, it's free!
- Beginner and intermediate level content: Decent Python programming skills
- Expert level content: Good understanding of CNNs and RNNs and ability to code in PyTorch or Tensorflow
Target audience
- Anyone who wants to master natural language processing (NLP)
- Anyone who loves deep learning and wants to learn about the most powerful neural network (transformers)
- Anyone who wants to go beyond typical beginner-only courses on Udemy
Data Science: Natural Language Processing (NLP) in Python
★★★★★
$25.00 in stock
Udemy.com
as of July 17, 2024 10:00 am
Applications: decrypting ciphers, spam detection, sentiment analysis, article spinners, and latent semantic analysis.
Created by: Lazy Programmer Inc.
Artificial intelligence and machine learning engineer
Artificial intelligence and machine learning engineer
Rating:4.64 (11148reviews)
42855students enrolled
What Will I Learn?
- Write your own cipher decryption algorithm using genetic algorithms and language modeling with Markov models
- Write your own spam detection code in Python
- Write your own sentiment analysis code in Python
- Perform latent semantic analysis or latent semantic indexing in Python
- Have an idea of how to write your own article spinner in Python
Requirements
- Install Python, it's free!
- You should be at least somewhat comfortable writing Python code
- Know how to install numerical libraries for Python such as Numpy, Scipy, Scikit-learn, Matplotlib, and BeautifulSoup
- Take my free Numpy prerequisites course (it's FREE, no excuses!) to learn about Numpy, Matplotlib, Pandas, and Scikit-Learn, as well as Machine Learning basics
- Optional: If you want to understand the math parts, linear algebra and probability are helpful
Target audience
- Students who are comfortable writing Python code, using loops, lists, dictionaries, etc.
- Students who want to learn more about machine learning but don't want to do a lot of math
- Professionals who are interested in applying machine learning and NLP to practical problems like spam detection, Internet marketing, and sentiment analysis
- This course is NOT for those who find the tasks and methods listed in the curriculum too basic.
- This course is NOT for those who don't already have a basic understanding of machine learning and Python coding (but you can learn these from my FREE Numpy course).
- This course is NOT for those who don't know (given the section titles) what the purpose of each task is. E.g. if you don't know what "spam detection" might be useful for, you are too far behind to take this course.
Natural Language Processing with Deep Learning in Python
★★★★★
$19.00 in stock
Udemy.com
as of July 17, 2024 10:00 am
Complete guide on deriving and implementing word2vec, GloVe, word embeddings, and sentiment analysis with recursive nets
Created by: Lazy Programmer Inc.
Artificial intelligence and machine learning engineer
Artificial intelligence and machine learning engineer
Rating:4.64 (7057reviews)
42008students enrolled
What Will I Learn?
- Understand and implement word2vec
- Understand the CBOW method in word2vec
- Understand the skip-gram method in word2vec
- Understand the negative sampling optimization in word2vec
- Understand and implement GloVe using gradient descent and alternating least squares
- Use recurrent neural networks for parts-of-speech tagging
- Use recurrent neural networks for named entity recognition
- Understand and implement recursive neural networks for sentiment analysis
- Understand and implement recursive neural tensor networks for sentiment analysis
- Use Gensim to obtain pretrained word vectors and compute similarities and analogies
Requirements
- Install Numpy, Matplotlib, Sci-Kit Learn, and Theano or TensorFlow (should be extremely easy by now)
- Understand backpropagation and gradient descent, be able to derive and code the equations on your own
- Code a recurrent neural network from basic primitives in Theano (or Tensorflow), especially the scan function
- Code a feedforward neural network in Theano (or Tensorflow)
- Helpful to have experience with tree algorithms
Target audience
- Students and professionals who want to create word vector representations for various NLP tasks
- Students and professionals who are interested in state-of-the-art neural network architectures like recursive neural networks
- SHOULD NOT: Anyone who is not comfortable with the prerequisites.
Natural Language Processing (NLP) in Python with 8 Projects
★★★★★
$18.00 in stock
Udemy.com
as of July 17, 2024 10:00 am
Work on 8 Projects, Learn Natural Language Processing Python, Machine Learning, Deep Learning, SpaCy, NLTK, Sklearn, CNN
Created by: Ankit Mistry
Software Developer | I want to Improve your life & Income.
Software Developer | I want to Improve your life & Income.
Created by: Vijay Gadhave
Data Scientist and Software Developer
Data Scientist and Software Developer
Created by: Data Science & Machine Learning Academy
Helping people to analyze data
Helping people to analyze data
Rating:4.4 (357reviews)
3656students enrolled
What Will I Learn?
- The Complete understanding of Natural Language Processing
- Implement NLP related task with Scikit-learn, NLTK and SpaCy
- Apply Machine Learning Model to Classify Text Data
- Text Classification (Spam Detection, Amazon product Review Classification)
- Text Summarization (Turn 5000 word article into 200 Words)
- Calculate Sentiment Score from Recently Posted Tweet (Tweeter API)
- Refresh your Deep Learning Concepts (ANN, CNN & RNN)
- Build your own Word Embedding (Word2vec) Model with Keras
- Word Embeddings application with Google Pretrained Model
- Spam Message Detection with Neural Network Based CNN and RNN Model
- Automatic Text Generation using TensorFlow, Keras and LSTM
- Working with Text Files & PDF in Python (PyPDF2 module)
- Tokenization, Stemming and Lemmatization
- Stop Words, Parts of Speech (POS) Tagging with NLTK
- Vocabulary, Matching, Named Entity Recognition (NER)
- Data Analysis with Numpy and Pandas
- Data Visualization with Matplotlib library
Requirements
- Basic understanding of Python Programming
Target audience
- Anyone who is interested to learn Natural Language Processing
Price Statistics
- All prices mentioned above are in United States dollar.
- This product is available at Udemy.
- At udemy.com you can purchase Natural Language Processing: Machine Learning NLP In Python for only $14.00
- The lowest price of Data Science: Transformers for Natural Language Processing was obtained on July 17, 2024 10:00 am.
