Skip to content
Write a review
UdemyData SciencePaid courseAll LevelsCertificate

Data Science: Natural Language Processing (NLP) in Python (Udemy.com)

Applications: decrypting ciphers, spam detection, sentiment analysis, article spinners, and latent semantic analysis.

4.6
12,915 reviews

Created by: Lazy Programmer Inc.

Last updated August 2026

Our take

Based on the ratings of 12,915 students, a sample of their written reviews and the syllabus, as the course stood in August 2026. No course pays to be reviewed.

This is a project-based tour of classic NLP in Python. Students build a cipher decryptor with Markov models and genetic algorithms, then a spam detector, a sentiment analyzer, latent semantic analysis and an article spinner. It runs about 12 hours over 90 lectures, with no quizzes or coding exercises. The description name-drops ChatGPT, but the syllabus covers older foundations, not transformers. Expect to need working Python and some machine learning basics, since a good chunk of the early material is a review.

Most of the 12,915 ratings are good: 7,365 five-star and 4,523 four-star. Reviewers like the simple explanations, the quick Q&A answers and the code being kept current. Instructor Lazy Programmer Inc. teaches clearly for most, though a handful of low-star reviews call the style sarcastic or condescending, and some say tangents wander off topic. Others want more depth, real-world applications and a section on text preprocessing. One reviewer found the structure disconnected, with a long ML review and an appendix that should both be shorter.

The course was last updated in August 2026, so the refresh is recent. Reviewers describe it as a good first step into NLP, and one says it can be finished in two days if you already know basic ML. It does not go deep, and one student says the instructor is upfront about where to go for more. We would call it a solid, short, practical starting point. Skip it if you want modern deep learning NLP or a lot of hand-holding.

Best forPython users with some ML basics who want short, hands-on NLP projects without heavy math.
Skip it ifYou want transformers or modern LLM work, or you need a gentler, more supportive teaching style.

Pros

  • Four projects built from scratch, from cipher decryption to an article spinner
  • Reviewers say explanations are simple and easy to follow if you know basic Python and ML
  • Q&A gets answered quickly and code examples are kept up to date, per reviewers
  • Short at about 12 hours, and one reviewer says it can be finished in two days

Cons

  • Some reviewers say it stays shallow and lacks real-world applications
  • A few low-star reviews call the instructor condescending or say tangents wander off topic
  • No quizzes or coding exercises, and one reviewer says text preprocessing is missing
Excellent starting point to learn NLP. Good material and simple teaching which help to grasp the content easily and fast. Code examples are kept up to date by instructor.
Jaymin Desai, a student

Listed for all levels, but it assumes working Python and basic ML. One data science student found it too hard.

icon
What you will 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
  • Understand important foundations for OpenAI ChatGPT, GPT-4, DALL-E, Midjourney, and Stable Diffusion

Course content

16 sections · 90 lectures · 12 hours of video

  1. 1Natural Language Processing - What is it used for? 2 free previews3 lectures · 22 min
  2. 2Course Preparation3 lectures · 17 min
  3. 3Machine Learning Basics Review11 lectures · 1.7 hours
  4. 4Markov Models13 lectures · 1.8 hours
  5. 5Decrypting Ciphers 1 free preview13 lectures · 1.6 hours
  6. 6Build your own spam detector11 lectures · 1.1 hours
  7. 7Build your own sentiment analyzer7 lectures · 1 hour
  8. 8NLTK Exploration4 lectures · 9 min
  9. 9Latent Semantic Analysis5 lectures · 44 min
  10. 10Write your own article spinner6 lectures · 37 min

Who it is for

The instructor says it suits

  • 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.

What you need before you start

  • 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

How it compares

Against the other 461 rated Udemy courses in Data Science on CourseDuck:

  • Rating4.6 out of 5higher than 67% of them
  • Reviews12,915#14 of 462 by number of reviews
  • Length11.9 hourslonger than 62% of them
  • Last updatedAugust 2026more recently than 88% of them

icon
Course Description

Ever wondered how AI technologies like OpenAI ChatGPT, GPT-4, DALL-E, Midjourney, and Stable Diffusion really work? In this course, you will learn the foundations of these groundbreaking applications.

In this course you will build MULTIPLE practical systems using natural language processing, or NLP - the branch of machine learning and data science that deals with text and speech. This course is not part of my deep learning series, so it doesn't contain any hard math - just straight up coding in Python. All the materials for this course are FREE.

After a brief discussion about what NLP is and what it can do, we will begin building very useful stuff. The first thing we'll build is a cipher decryption algorithm. These have applications in warfare and espionage. We will learn how to build and apply several useful NLP tools in this section, namely, character-level language models (using the Markov principle), and genetic algorithms.

The second project, where we begin to use more traditional "machine learning", is to build a spam detector. You likely get very little spam these days, compared to say, the early 2000s, because of systems like these.

Next we'll build a model for sentiment analysis in Python. This is something that allows us to assign a score to a block of text that tells us how positive or negative it is. People have used sentiment analysis on Twitter to predict the stock market.

We'll go over some practical tools and techniques like the NLTK (natural language toolkit) library and latent semantic analysis or LSA.

Finally, we end the course by building an article spinner. This is a very hard problem and even the most popular products out there these days don't get it right. These lectures are designed to just get you started and to give you ideas for how you might improve on them yourself. Once mastered, you can use it as an SEO, or search engine optimization tool. Internet marketers everywhere will love you if you can do this for them!

This course focuses on "how to build and understand", not just "how to use". Anyone can learn to use an API in 15 minutes after reading some documentation. It's not about "remembering facts", it's about "seeing for yourself" via experimentation. It will teach you how to visualize what's happening in the model internally. If you want more than just a superficial look at machine learning models, this course is for you.

"If you can't implement it, you don't understand it"

  • Or as the great physicist Richard Feynman said: "What I cannot create, I do not understand".

  • My courses are the ONLY courses where you will learn how to implement machine learning algorithms from scratch

  • Other courses will teach you how to plug in your data into a library, but do you really need help with 3 lines of code?

  • After doing the same thing with 10 datasets, you realize you didn't learn 10 things. You learned 1 thing, and just repeated the same 3 lines of code 10 times...
Read More All Levels All Levels product length iconTime: 11.9h

icon
Udemy Discount

The discount is applied through our link. Open the course from here and Udemy's current promotional price is applied at checkout on most courses, no code to type.

Get the Udemy discount

Some courses are excluded from Udemy's promotions. If the price does not drop, clear your browser cookies and use the button again.

icon
Instructor Details

Lazy Programmer Inc.

The Lazy Programmer is a seasoned online educator with an unwavering passion for sharing knowledge. With over 10 years of experience, he has revolutionized the field of data science and machine learning by captivating audiences worldwide through his comprehensive courses and tutorials.


Equipped with a multidisciplinary background, the Lazy Programmer holds a remarkable duo of master's degrees. His first foray into academia led him to pursue computer engineering, with a specialized focus on machine learning and pattern recognition. Undeterred by boundaries, he then ventured into the realm of statistics, exploring its applications in financial engineering.


Recognized as a trailblazer in his field, the Lazy Programmer quickly embraced the power of deep learning when it was still in its infancy. As one of the pioneers, he fearlessly embarked on instructing one of the first-ever online courses on deep learning, catapulting him to the forefront of the industry.


Read More

icon
More courses by Lazy Programmer Inc.

$99.99

$149.99

$15.99

$79.99

$109.99

$99.99

All courses by Lazy Programmer Inc.

icon
More Data Science courses

Free

Free

Free

Free

$124.99

Free

All Data Science courses

icon
Reviews

4.6

12,915 ratings on Udemy

Select a bar to show only those reviews.Select the bar again to show every rating.

Write a review

By Vatsal Sinha on 12/7/2022

This course is a very good start for a new person getting into NLP, as this course teaches all the basics and also shows 3-4 hands on projects being built from scratch, thus it will build your confidence and motivate you into getting into advanced stuff of NLP. You must take the Advanced NLP Course otherwise you will leave on all the usable practical concepts and models which are in use in today's world. The best thing about this course is that it is a small course and if you have any basic knowledge about ML then you can finish this course in 2 days and move on to the next for building projects and reaching your goal with a greater confidence. Overall, it is a nice and simple course which breaks your insecurities toward NLP bsaics.

By Marcos Chaves Martins on 7/21/2021

For me it suited me well on my objective of gaining a basic understanding of NLP, Data Science and Deep Learning. We have Q&A answered promplty, which is really awesome. Also, the instructor is very transparent on his objectives, what you are getting in this course and where you should go for covering gaps or extending the knowledge.

By Timothy Lim on 6/6/2021

The content is excellent. It's nice to see that the content is kept up to date and the coding lectures have been updated with google colab. The conceptual portion is kept light, so it can be a good course for beginners. The cipher decryption section was a bit hard, but I enjoyed the challenge.

By Raj Nanda on 4/22/2021

I really liked the course organization. The instructor taught in a very clear way and also pointed out additional exercises and extensions at every section. The contents were helpful and Q&A forum will answer your doubts quickly. Instructor has clearly explained each step and why it's useful to do them.

By Shahbaz Akhtar on 4/9/2021

A really great course, especially for beginners like me who are new to this field. Successfully explained the important concepts of NLP by example. I feel really lucky to have taken this course. I highly recommend this course for beginners in NLP as it is a one stop course including all the essential topics in one place. Thanks to the instructor for bringing this nice course for machine learning students.

By Cian O'Sullivan on 2/3/2021

I think it's good beginner course into NLP for someone who just wants some quick information that later, can be used to looked into further, and to learn some fundamental basics about NLP. An example of what I mean is that it covers Machine Learning but doesn't explain or go into depth into how the Machine Learning algorithms work as that is out of the scope of this course and would be for another, Machine Learning focused course to do. I bought this course to learn more about NLP and specifically sentiment analysis and I got the information that I was looking for, that will help me to learn more about and understand NLP.

By Kenn Lau on 10/24/2020

I purchased this course simply for the article spinning section. To put it kindly without the expletive, it was absolutely underwhelming. Do not expect that you'll have a functioning article spinner at the end of the section. I will most likely stir away from this instructor and/or company.

By Indrajit Bose on 9/24/2020

good

By shruchin b on 9/18/2020

Got to learn new libraries and there functionality. Presenter has made the course interactive by sharing the codes which we can try apply after learning it.

By Neelkanth Mehta on 8/29/2020

It's well organized, in that each section comprises of a sub-top and each sub-top comprises of intro, theory, code and guidance for further learning. That said, the effective video duration of the NLP content is ~4.5 hrs. while ~4.5 hrs. is basic instructional material. Not that quantity of learning hours matters, but the extra efforts could be directed towards, say building industrial quality NLP applications (using spaCy).

By Ashish Verma on 8/22/2020

good and great

By Matias Romo on 8/14/2020

The course is really well explained and detailed with many examples but I would like to see more use cases

Showing 12 of 317 reviews

icon
Quality Score

No CourseDuck member has rated this course yet. Taken it? Give each part a thumbs up or down.

Content Quality
/
Video Quality
/
Qualified Instructor
/
Course Pace
/
Course Depth & Coverage
/

Overall Score : 92 / 100

Data Science: Natural Language Processing (NLP) in Python
Visit course on Udemy Write a review
  • Video Duration: icon 11.9h
  • Price: $22.99
  • Provider: icon Udemy
  • Updated: icon August 2026
  • Level: All Levels All Levels
  • Language: icon English
  • Certificate: icon Yes
  • Lectures:90 in 16 sections
  • Students:53,500
  • Subtitles:1 language
30-day money-back guarantee on most paid courses

Udemy Coupon Price Tracker

Udemy price history

For any issues or feature requests please email CourseDuck's Co-Founder at mkuhlman12@gmail.com