Best Natural Language Processing Courses [Top 5]

In this article we’ll cover:

1. What is Natural Language Processing (NLP) and is it worth learning?
2. Where can I study natural language processing?
3. How long it will take to learn NLP?
4. Top 5 NLP Courses Online. Our pick.
   1. Natural Language Processing Specialization – Coursera
   2. Natural Language Processing with Deep Learning in Python – Udemy
   3. Professional Certificate in Text Analytics with Python – edX
   4. Natural Language Processing Expert Nanodegree Program – Udacity
   5. Deep Learning Foundations: Natural Language Processing with TensorFlow – LinkedIn Learning
5. List of NLP related courses to consider

In an age where communication is key, Natural Language Processing (NLP) has become increasingly important. This fascinating field of study revolves around the interaction between computers and human language, allowing machines to understand and interpret words in a way that mimics human-like understanding.

With its ability to power chatbots, voice assistants, sentiment analysis tools and more – there’s no doubt NLP has taken over as one of the most sought-after skills in today’s job market.

But with so many resources available online these days, it can be hard to decide which natural language processing courses are worth your time. That’s why we’ve compiled a list of the top 5 best NLP courses you can find online!

What is Natural Language Processing (NLP) and is it worth learning?

Natural Language Processing (NLP) is a branch of artificial intelligence that focuses on the interaction between computers and humans.

It enables machines to understand human language in a way that mimics human-like understanding, allowing them to interpret, analyze and generate natural language content like chatbots, voice assistants, sentiment analysis tools and more.

As data continues to grow exponentially every day, NLP has become an increasingly important skill for businesses across industries. With its ability to help companies better understand customer feedback or automate repetitive tasks, mastering NLP can enhance your career prospects and make you stand out from the crowd.

Moreover, learning NLP is not only limited to those interested in AI development but also for marketing professionals who want to improve their digital marketing strategies.

By being equipped with this knowledge it becomes easier for marketers  to know what message will resonate effectively with their target audience thereby improving conversion rates.

Natural Language Processing is definitely worth learning as it opens up doors for various job opportunities such as machine learning engineer or data analyst while at the same time providing insights into how we communicate with one another digitally

Where can I study natural language processing?

If you are interested in studying Natural Language Processing (NLP), there are many options available for you to choose from. The first place to start is online, where some of the best NLP courses can be found.

Online platforms like Coursera, Udemy and edX offer a variety of NLP courses ranging from beginner to advanced levels. These courses usually include video lectures, assignments and quizzes that allow students to learn at their own pace.

For those looking for a more structured learning approach, universities such as Stanford and Columbia also offer NLP courses both on campus and online. These courses provide students with the opportunity to interact with professors and classmates while gaining valuable hands-on experience through projects.

In addition to these formal options, there are also numerous blogs, forums and tutorials available online that provide useful information related to NLP. Some recommended ones include “Speech & Language Processing” by Jurafsky & Martin’s blog or the “Natural Language Toolkit” (NLTK) community forum.

Whether you prefer self-paced learning or structured programs led by experts in the field, there is a vast array of resources for anyone interested in studying natural language processing.

How long it will take to learn NLP?

The duration it takes to learn natural language processing (NLP) depends on several factors such as your prior knowledge of computer science and programming languages. However, with the right resources and dedication, you can become proficient in NLP within a reasonable time frame.

Firstly, if you are already familiar with Python or other programming languages commonly used in NLP, then learning NLP will be relatively easy for you. But if not, then expect to spend some time getting up to speed before diving into NLP concepts.

Secondly, the complexity of the course materials also affects how long it takes to learn NLP. Some courses cover only basic concepts while others dive deeper into advanced topics like deep learning algorithms.

Additionally, your study schedule also plays a significant role in determining how long it will take for you to complete an NLP course successfully. Regular practice sessions and consistent effort can help reduce the amount of time required significantly.

There is no fixed timeline for mastering Natural Language Processing since everyone learns at their own pace depending on various factors mentioned above. Therefore it’s essential to create a realistic plan and dedicate enough time daily towards studying this exciting field!

Top 5 NLP Courses Online. Our pick.

We have carefully selected these courses based on their comprehensive content, experienced instructors, and positive student reviews. Whether you are a beginner looking to explore the fundamentals of NLP or an experienced practitioner seeking to enhance your skills, these courses offer a wealth of knowledge and practical insights.

Natural Language Processing Specialization – Coursera

It may be one of the best natural language processing courses on Coursera, offered by Andrew Ng’s DeepLearning AI, one of the pioneers in the industry.

This training enables learners to create NLP applications that can perform multiple functions, such as answering questions, analyzing sentiments, and translating languages.

By the end of the course, the learners will have acquired sufficient exposure to different concepts and gained practical experience building NLP applications.

Additionally, learners will gain a thorough understanding of dynamic programming, hidden Markov models, and how to implement autocorrect and autocomplete features, encoder-decoders, summarize texts, and perform machine translations.

Curriculum of the course includes:

• Classification and vector spaces in natural language processing
• Probabilistic models for natural language processing
• Sequence models for natural language processing
• Attention-based natural language processing

👉 Learn more about this course - Natural Language Processing Specialization – Coursera

Natural Language Processing with Deep Learning in Python – Udemy

With a focus on word2vec, GloVe, word embeddings, and sentiment analysis with recursive nets, this course promises to equip students with the necessary skills to tackle NLP tasks effectively.

Course Details:

• Rating: 4.7 out of 5
• Number of Ratings: 7,658
• Number of Students: 44,433
• Created by: Lazy Programmer Inc.
• Last updated: May 2023
• Language: English
• Additional Languages: English Auto, French Auto, and 5 more

Course Content:

The course covers a wide range of topics and provides in-depth knowledge and practical skills. Here are some key areas you will explore during the course:

• Understanding and implementing word2vec
• Exploring the CBOW method and skip-gram method in word2vec
• Learning about negative sampling optimization in word2vec
• Understanding and implementing GloVe using gradient descent and alternating least squares
• Utilizing recurrent neural networks for parts-of-speech tagging
• Applying recurrent neural networks for named entity recognition
• Understanding and implementing recursive neural networks for sentiment analysis
• Exploring recursive neural tensor networks for sentiment analysis
• Using Gensim to obtain pretrained word vectors and compute similarities and analogies

Course Experience:

The course provides a well-structured and engaging learning experience. Students have praised the course for its clear explanations, hands-on coding exercises, and practical applications of NLP techniques. The instructor’s teaching style has been commended for making complex concepts accessible to learners of all levels. With a current rating of 4.7 out of 5, this course has received positive feedback from thousands of students.

Pricing and Guarantee:

The course is currently priced at €64.99 and comes with a 30-day money-back guarantee. This allows students to enroll with confidence, knowing that they can request a refund if the course does not meet their expectations.

👉 Learn more about this course - Natural Language Processing with Deep Learning in Python – Udemy

Professional Certificate in Text Analytics with Python – edX

On edX, the University of Canterbury offers this specialization in natural language processing and text analytics.

Practically, learners will perform text analysis using Python programming and create machine learning pipelines for text classification.

Hands-on sessions offered by the program are crucial for gaining a deeper understanding of automated workflows, from data collection to visualization. For the scientific aspect of the course, the participants will learn about concepts like understanding languages computationally and the differences between how a human and an artificial intelligence view text documents.

Furthermore, learners will be able to understand the ethical requirements and limitations of specific computational approaches to language translation. Various real-world case studies are provided for the participants to engage practically and perform data science-related tasks to gain insights from unstructured data by performing text analytics.

By the end of the course, learners will be able to code applications using unstructured data such as news articles and tweets and apply machine learning classifiers to categorize documents.

Moreover, learners will be able to perform NLP tasks for identifying document similarity, visualizing and interpreting text analytics with statistical significance tests, and assessing different scientific and ethical foundations of text analytics applications.

Among the topics covered in the course are:

• Natural Language Processing: An Introduction
• Learn how artificial intelligence can help with language data in Module 1: Why Use Text Analytics?
• Learn what language looks like from the perspective of humans and machines in Module 2: Working with Text Data
• The third module covers text classification, where you will learn how to use machine learning to categorize documents based on content, authorship, and sentiment.

Natural Language Processing Visualization

• Text Similarity Module 1: Learning how to use machine learning to find similar words and documents.
• The Visualization of Text Analytics module consists of the following modules: Using visualization and significance testing to explain a model.
• Module 3: Using Text Analytics in New Fields: Applying computational linguistics to new problems and data sets.

DETAILS OF THE COURSE:

• Jonathan Dunn, Tom Coupe, Jeanette King, and Girish Prayag are the instructors
• Intermediate level
• The duration of the project is three months
• Review by user: N/A
• The price is $498.

👉 Learn more about this course - Professional Certificate in Text Analytics with Python – edX

Natural Language Processing Expert Nanodegree Program – Udacity

Course Details at a glance:

Main Features:

1. Comprehensive NLP Specialization: Master the skills required to process and manipulate human language, build models on real-world data, and excel in various NLP tasks.
2. Hands-on Experience: Gain practical experience in sentiment analysis, machine translation, and other relevant NLP tasks through hands-on projects.
3. Speech Processing and Analysis: Learn to process speech, analyze text, and build probabilistic and deep learning models for effective speech recognition.
4. Hidden Markov Models: Dive deep into Hidden Markov Models (HMM) and learn to train them using Viterbi and Baum-Welch algorithms. Use HMM for speech tagging model building.
5. Attention Mechanisms and Advanced Deep Learning: Understand and implement advanced deep learning methods, such as attention mechanisms, for machine translation, text summarization, and image captioning.

Course Overview:

The “Become a Natural Language Processing Expert Nanodegree Program” offered by Udacity is a comprehensive specialization that equips participants with the necessary skills to process and manipulate human language effectively. Throughout the course, learners will gain hands-on experience in various NLP tasks and learn to build models on real-world data.

The curriculum covers a wide range of topics, including language processing techniques, tokenization, stemming, lemmatization, speech tagging, named entity recognition, and more. Learners will also explore Hidden Markov Models (HMM) and gain insights into training and utilizing them for speech tagging models. The course delves into the extraction of features from text, embedding algorithms like Word2Vec and GloVe, and the application of deep learning models in NLP, such as machine translation, sentiment analysis, and topic models.

Furthermore, learners will dive into advanced topics like attention mechanisms, which are crucial for advanced NLP applications. Concepts like additive and multiplicative attention for machine translation, text summarization, and image captioning will be covered. The course also explores information extraction, information retrieval systems, question answering, and communication using natural language.

Led by instructors Luis Serrano, Jay Alammar, Arpan Chakraborty, and Dana Sheahen, this program offers valuable insights and practical knowledge. The duration of the course is 3 months.

The user reviews for this course are highly positive, with an average rating of 4.5/5 from 508 reviews.

As part of the Nanodegree program, this course is available for a monthly subscription fee of $299 or a discounted access fee of $763 for a 3-month period.

In conclusion, the “Become a Natural Language Processing Expert Nanodegree Program” on Udacity is a highly recommended course for intermediate to advanced learners seeking to excel in NLP. With its comprehensive curriculum, hands-on projects, and experienced instructors, this program provides a valuable learning experience in the field of NLP.

👉 Learn more about this course - Natural Language Processing Expert Nanodegree Program – Udacity

Deep Learning Foundations: Natural Language Processing with TensorFlow – LinkedIn Learning

Course Details:

Main Features:

1. NLP and Deep Learning: Learn to leverage the power of NLP and deep learning models for textual data analysis.
2. TensorFlow for Tokenization: Understand word encoding and utilize TensorFlow for tokenization.
3. Word Embeddings: Explore the concepts of word embedding and implement TensorFlow for classifying movie reviews.
4. LSTM Implementation: Dive deep into LSTM concepts and learn techniques to improve movie review classifiers.
5. Text Generation: Train RNNs to predict the next word in a sentence and generate original text.

Course Overview:

The “Deep Learning Foundations - Natural Language Processing with TensorFlow” course, available on LinkedIn Learning, empowers learners to harness the potential of NLP and deep learning models for making informed decisions with textual data. Throughout the course, participants will gain a comprehensive understanding of recurrent neural networks (RNNs), word encoding, tokenization using TensorFlow, and more.

The curriculum covers various essential topics, such as word embeddings, text classification using TensorFlow, and projecting vectors. Learners will delve into building a text classifier and explore the implementation of LSTM for improving movie review classifiers. Additionally, the course provides insights into text generation techniques and predicting the next word in a sentence.

Led by instructor Harshit Tyagi, this course offers practical knowledge and hands-on exercises to enhance understanding. The duration of the course is 1 hour and 47 minutes.

As this is a LinkedIn Learning course, specific user reviews and ratings are not available. However, the course can be accessed with a 1-month free trial on the platform, with charges applicable after the trial period.

The “Deep Learning Foundations - Natural Language Processing with TensorFlow” course on LinkedIn Learning is a valuable resource for intermediate learners seeking to deepen their understanding of NLP and its application in deep learning. With Harshit Tyagi as the instructor, this course provides practical insights and techniques to leverage TensorFlow for NLP tasks.

👉 Learn more about this course - Deep Learning Foundations: Natural Language Processing with TensorFlow – LinkedIn Learning

List of NLP related courses to consider

And, yes, there are much more NLP related courses to recommend. Here is a list worth exploring:

1. Applied Text Mining in Python - University of Michigan on Coursera
2. NLP Natural Language Processing with Python - Stanford University on Coursera
3. NLP - Zero to Hero - Deep Learning with TensorFlow - Udemy
4. Practical Natural Language Processing - IBM on Coursera
5. Advanced Natural Language Processing - University of Illinois at Urbana-Champaign on Coursera
6. Natural Language Processing in TensorFlow - deeplearning.ai on Coursera
7. Introduction to Natural Language Processing - University of Washington on Coursera
8. Deep Learning for Natural Language Processing - National Research University Higher School of Economics on Coursera
9. Natural Language Processing - University of California, Berkeley on edX
10. Natural Language Processing with Probabilistic Models - Stanford University on Coursera
11. Natural Language Processing - University of Colorado Boulder on Coursera
12. Deep Learning for NLP - Oxford University on edX
13. Natural Language Processing for Python Developers - DataCamp
14. Introduction to Natural Language Processing - Microsoft on edX
15. Natural Language Processing in Python - DataCamp
16. Deep Learning and NLP - Stanford University on Coursera
17. Natural Language Processing Specialization - University of Michigan on Coursera
18. Text Mining and Analytics - University of Illinois at Urbana-Champaign on Coursera
19. Natural Language Processing Fundamentals - University of California, Santa Cruz on Coursera
20. Natural Language Processing - Columbia University on edX

These courses offer a diverse range of NLP topics and are provided by reputable institutions and platforms. Take your time to explore them and choose the ones that best suit your learning needs.