Last updated: June 2026. Written by Josh Hutcheson, OnlineCourseing editor. See our review methodology.
QUICK VERDICT
Bottom line: For a credential and a structured path, take the NLP Specialization from DeepLearning.AI (4.6★, 6,192 reviews) on Coursera. For a cheaper, hands-on start in Python, Data Science: NLP in Python (4.7★) is the best Udemy pick.
- Best overall / credential: Coursera NLP Specialization (DeepLearning.AI)
- Best value: Lazy Programmer’s Udemy NLP courses (4.7★)
- Prerequisites: comfortable Python; the deep-learning pick assumes some ML background
See Our Top Pick on Coursera →
Natural language processing sits behind search, chatbots, sentiment analysis, and the large language models everyone now builds on. Learning it well means pairing the theory — tokenization, embeddings, attention — with real Python practice, and the courses below split cleanly between those two emphases.
We checked each course was live and confirmed its rating before recommending it. One honest caveat up front: NLP is not a beginner-friendly first programming course. Every pick assumes you can already write Python, and the deep-learning option assumes some machine-learning grounding too. We earn a commission if you enroll through our links, which never changes the ranking.
HOW WE PICKED
We weighed instructor authority, how current the material is (NLP moves fast — transformers and LLMs matter now), learner ratings at scale, and whether the course is theory-first or build-first. Every pick holds a 4.5★ rating or higher.
1. Best overall & for a credential — Coursera: NLP Specialization (DeepLearning.AI)
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Built by DeepLearning.AI and taught by Younes Bensouda Mourri and Lłukasz Kaiser (a co-author of the Transformer paper), this four-course specialization is the most credible structured path in NLP. It runs from classification and vector spaces through to attention models and transformers, and ends with a recognized certificate. It holds a 4.6★ rating across 6,192 reviews.
Best for: anyone who wants depth and a credential employers recognize. Worth knowing: it’s math-aware — you’ll meet linear algebra and probability, not just code.
Enroll on Coursera (free trial) →
2. Best hands-on Python intro — NLP – Natural Language Processing with Python
Jose Portilla’s course is the most practical on-ramp: you work directly with NLTK and spaCy and build real text-processing pipelines rather than wading through theory first. If you learn by typing code, start here. It holds a 4.5★ rating.
Best for: Python developers who want to build NLP projects quickly. Worth knowing: lighter on the deep-learning math than the Coursera or Lazy Programmer options.
RECOMMENDED PARTNER — COURSERA
A recognized NLP credential
The DeepLearning.AI specialization is on Coursera Plus — one subscription also covers its Machine Learning and Deep Learning specializations if you want the full track.
Affiliate partnership — we may earn commission when you sign up via this link. We only recommend courses we’d send a friend to.
3. Best for the machine-learning angle — Data Science: NLP in Python
From the instructor known as the Lazy Programmer, this course frames NLP as applied machine learning — spam detection, sentiment analysis, and article spinning built from the algorithms up. It’s the best pick if you want to understand why the models work, not just call a library. At 4.7★ it’s the highest-rated Udemy option here.
Best for: learners who want the ML reasoning behind NLP. Worth knowing: expects working Python and basic ML familiarity.
4. Best for deep-learning NLP — Natural Language Processing with Deep Learning in Python
Also from the Lazy Programmer, this is the step up — word2vec, GloVe, recurrent networks, and the neural architectures modern NLP is built on. Take it after you’ve got the fundamentals; it’s the bridge from classical NLP to the deep-learning models behind today’s language systems. It also holds a 4.7★ rating.
Best for: learners moving from classical NLP into neural methods. Worth knowing: the steepest prerequisites on the list — bring real ML and Python experience.
NLP courses compared
| Course | Best for | Provider | Rating |
|---|---|---|---|
| NLP Specialization | Depth + credential | Coursera / DeepLearning.AI | 4.6 (6,192) |
| NLP with Python | Hands-on Python intro | Udemy (Portilla) | 4.5 |
| Data Science: NLP in Python | The ML angle | Udemy (Lazy Programmer) | 4.7 |
| NLP: Deep Learning in Python | Neural methods | Udemy (Lazy Programmer) | 4.7 |
Is an NLP certification worth it?
There’s no single industry-standard NLP certification the way there is for, say, cloud platforms. What you can earn:
- The DeepLearning.AI specialization certificate — the most respected option here. DeepLearning.AI is a known name in ML, so the certificate carries real signal and pairs well with a portfolio.
- Udemy completion certificates — fine for showing what you’ve studied, but not a formal credential.
In NLP, what actually gets you hired is demonstrable work — a sentiment classifier, a fine-tuned model, a project on GitHub. Treat any certificate as a complement to that, not a substitute.
NLP is one branch of machine learning. For the foundations and adjacent skills, see our picks for the best machine learning courses, best Python courses, and best AI courses.
Frequently asked questions
What is the best NLP course overall?
The NLP Specialization from DeepLearning.AI (4.6★, 6,192 reviews) on Coursera is the strongest all-round choice — credible instructors, a structured path from fundamentals to transformers, and a recognized certificate.
Do I need to know Python before learning NLP?
Yes. Every course here assumes you can already write Python. If you can’t yet, start with a Python course first — NLP builds directly on libraries like NLTK, spaCy, and PyTorch.
How much do NLP courses cost?
The Udemy courses are usually $15–$20 on sale with lifetime access. The Coursera specialization runs on a monthly subscription (commonly around $49–$59), so finishing faster costs less; you can also audit individual courses free without the certificate.
Which NLP course covers transformers and LLMs?
The DeepLearning.AI specialization reaches attention models and transformers, and the Lazy Programmer’s deep-learning course covers the neural foundations they’re built on. Both are better routes into modern LLM work than the lighter intro courses.