Best YouTube Channels to Learn NLP
Best YouTube Channels to Learn NLP
When I first started learning about Artificial Intelligence (AI), I was immediately drawn to one of its most fascinating subfields—Natural Language Processing (NLP).
For me, NLP felt like the bridge between human communication and machine understanding. It’s incredible how we’ve taught computers to read, interpret, and respond to human language in a meaningful way.
I learned that at its core, NLP is all about enabling interaction between humans and machines through natural language.
With it, machines can read text, recognize speech, interpret context, understand sentiment, and even generate responses—just like humans do.
What I Understood About the Key Components of NLP
As I dug deeper, I realized NLP isn’t just about fancy AI chatbots; it’s made up of several fundamental building blocks:
Text Processing: I learned to break raw text into smaller units like sentences and words through techniques like tokenization. Removing stop words like “is” or “and” and reducing words to their root form with stemming or lemmatization made a lot of sense once I saw it in action.
Syntax Analysis (Parsing): This taught me how to recognize the grammatical structure of a sentence—like figuring out who did what to whom.
Semantics: Understanding word meanings based on context was fascinating. I now understand why “bank” can mean very different things depending on the sentence.
Named Entity Recognition (NER): I found it super helpful for extracting names, locations, dates, etc., from text. For example, identifying “Apple” as a company and “Steve Jobs” as a person.
Sentiment Analysis: I started seeing how NLP can be used to detect emotions in texts—whether a tweet is positive, negative, or neutral.
Machine Translation: I was amazed to learn how models like Google Translate handle language conversion while understanding grammar and context across different languages.
Speech Recognition & Generation: When I looked into how tools like Siri or Alexa work, I understood the power of converting speech to text and back again using NLP.
Techniques That Helped Me Learn NLP
As I progressed, I explored different NLP methods:
- Rule-Based Systems: I started here because they’re easy to understand, even if a bit rigid.
- Statistical Methods: I saw how probability and data-driven models help computers learn language patterns.
- Deep Learning Models: Eventually, I started playing with powerful models like BERT, GPT-4, and ChatGPT. These use neural networks to understand context and meaning at a deep level.
Real-World Applications That Got Me Excited
What really motivated me was seeing how NLP is used in everyday tools:
- Chatbots & Virtual Assistants
- Search Engines
- Spam Detection
- Voice Assistants
- Language Translation
- Grammar Checking
- Content Recommendation
- Social Media Monitoring
Challenges I Faced While Studying NLP
Of course, it wasn’t all smooth sailing. I ran into challenges like:
- Ambiguity: So many words have multiple meanings!
- Context Understanding: I realized how much meaning relies on context and culture.
- Sarcasm and Emotion: Machines still struggle with humor or sarcasm.
- Language Diversity: Different languages, dialects, and scripts brought a lot of complexity.
My Top 3 YouTube Channels for Learning NLP
As AI started booming, I knew I had to stay updated or risk falling behind. So I focused on studying NLP through YouTube—it was free, accessible, and taught by real practitioners. Here are the three channels that truly made a difference in my learning journey:
(1) CampusX by Nitish Singh
When I was just starting, CampusX was a game changer. Nitish Singh’s way of teaching is clear, calm, and beginner-friendly. His playlist on NLP may only have a handful of videos, but it runs over 15 hours, each video packed with deep explanations.
He focused mostly on the theory behind NLP, which I found invaluable. At first, I was a little disappointed that there wasn’t a lot of coding, but later I realized that understanding the why and how behind NLP techniques gave me a huge advantage when I started building projects.
Whether it was text preprocessing, tokenization, stop words, stemming, lemmatization, or vectorization, he made sure I understood the foundation before jumping into Python libraries like NLTK or spaCy. I genuinely appreciated how he connected abstract concepts to real-world examples—it made everything stick.
If you’re just getting started with NLP, start here. CAMPUX gave me the theoretical grounding I needed to move forward with confidence.
(2) Codebasics by Dhaval Patel
Once I had a grip on the theory, I was ready to code. That’s when I turned to Codebasics, and I’m glad I did.
Dhaval Patel focuses on real-world applications of data science, and his NLP tutorials are no exception. His teaching style is super practical—he helps you build actual projects like text classifiers, chatbots, and sentiment analyzers using libraries like NLTK and spaCy.
What stood out to me is how industry-relevant his content is. I began understanding how companies use NLP in everyday scenarios, and I was able to build projects that I later showcased on my GitHub.
His channel made it easy to transition from theory to practice, and I know many learners like me have used Codebasics to break into data science careers.
(3) freeCodeCamp
Once I had both theory and some hands-on practice, I was ready for deep dives—and freeCodeCamp was perfect for that.
I found long-form, high-quality tutorials that didn’t just scratch the surface. These were practical and detailed and helped me build end-to-end NLP pipelines. I learned to work with Hugging Face Transformers, build chatbots, do text classification, and more.
What I love most is that freeCodeCamp doesn’t just show you what to do—it walks you through the why, the how, and the actual coding in one cohesive flow. I could directly use these projects in my portfolio, which helped me gain confidence and credibility.
If you’re serious about applying NLP in the real world, freeCodeCamp is where you level up.
(4) CodeBeyond – Arpit Jain
I want to share my experience with a great mentor I came across in the field of Data Science, AI, and Machine Learning—Arpit Jain from Codebeyond.
If you’re just starting out or looking to build a solid foundation in these areas, I highly recommend checking out his course.
What really stood out to me was his approachable teaching style and the way he simplifies complex topics. He’s a very good mentor, especially for beginners, and his explanations are clear and easy to follow.
One of the highlights of his course is the section on Natural Language Processing (NLP). It includes 10 dedicated lectures on NLP, which is a big plus if you’re interested in working with text data, chatbots, language models, or anything in that space.
While I wouldn’t say the lectures go super deep into advanced NLP techniques, they’re definitely detailed enough to help you understand the core concepts.
Topics like text preprocessing, tokenization, sentiment analysis, and basic language models are covered in a way that makes them accessible, even if you’re new to the subject.
I’ve personally watched all the NLP lectures, and I found them to be a very good starting point. They helped me understand the basics clearly and gave me the confidence to explore more advanced resources later.
In my opinion, this course is a great stepping stone if you’re aiming to specialize in NLP within the broader field of AI and ML.
Overall, I’d rate the course a solid 4 out of 5. It’s not the deepest dive into each topic, but for the clarity, structure, and value it provides to beginners, it’s definitely worth your time. If you’re looking to get started in data science and AI, this is a good place to begin.
Final Thoughts
NLP has completely changed how I look at language and technology. What started as a curiosity became a passion. Thanks to YouTube channels like CAMPUX, Codebasics, and freeCodeCamp, I’ve gone from learning the theory to building real projects I can be proud of.
If you’re starting your journey in NLP, I’d recommend following a similar path:
CAMPUX for theory → Codebasics for hands-on practice → freeCodeCamp for advanced real-world projects.
Whether you’re a student, a working professional, or someone switching careers, if I can do it, so can you.