Natural Language Processing (NLP) Courses and Certifications

MLOps World: Machine Learning in Production

How Many Labelled Examples Do You Need for a BERT-sized Model to Beat GPT4 on Predictive Tasks?

Examines how labeled-data requirements shape comparisons between BERT-sized models and GPT-4 on predictive language tasks.

• YouTube
• 28 minutes
• Self-Paced
• Free Video

UofU Data Science

Natural Language Processing - Fall 2025

Trace NLP from word embeddings and transformers to retrieval-augmented generation, instruction tuning, and reasoning-model evaluation.

• YouTube
• 1 day 6 hours 2 minutes
• Self-Paced
• Free Video

UofU Data Science

Natural Language Processing - Fall 2024

A broad NLP course spanning classical parsing and tagging through transformers, multilingual LLMs, retrieval, fine-tuning, and evaluation.

• YouTube
• 1 day 10 hours 45 minutes
• Self-Paced
• Free Video

media.ccc.de

51 Ways to Spell the Image Giraffe - The Hidden Politics of Token Languages in Generative AI

Experiments with token spellings reveal how generative AI vocabularies shape image generation and encode cultural and political biases.

• YouTube
• 38 minutes
• Self-Paced
• Free Video

Career Certificate

DeepLearning.AI TensorFlow Developer

25405 ratings at Coursera

Build and train deep learning models in TensorFlow, from convolutional networks for image classification to natural language processing and sequence and time series prediction.

• Coursera
• 8 weeks, 10 hours a week
• Self-Paced
• Paid Course
• 4 courses

Graham Neubig

Advanced NLP - Experimental Design and Data Annotation - Lecture 9

1 rating

A lecture on designing experiments and annotating data for advanced NLP research.

• YouTube
• 1 hour 17 minutes
• Self-Paced
• Free Video

Toronto Machine Learning Series (TMLS)

Deep Learning for ESG: Advances and Limitations

1 rating

Examines how transformers and transfer learning can support ESG analysis, and where current NLP still needs human oversight.

• YouTube
• 24 minutes
• Self-Paced
• Free Video

Data Science Dojo

Tokenization in NLP: From Basics to Advanced Techniques

1 rating

Tokenization turns text into model-ready inputs through token IDs, Byte Pair Encoding, sliding-window sampling, embeddings, and positional encoding.

• YouTube
• 1 hour
• Self-Paced
• Free Video

Natural Language Processing with spaCy

679 ratings at DataCamp

Meet spaCy, an Industry-Standard for NLP In this course, you will learn how to use spaCy, a fast-growing industry-standard library, to perform various natural language processing tasks such as tokenization, sentence segmentation, parsing, and named entit…

• DataCamp
• 4 hours
• Self-Paced
• Free Trial Available

Deep Learning for Natural Language - The Basics - Lecture 5

An introduction to natural language processing through text vectorization and the bag-of-words model, with a Colab demonstration.

• YouTube
• 1 hour 17 minutes
• Self-Paced
• Free Video

Open Data Science

Teaching Machines Through Human Explanations

An explanation-based learning framework uses human natural-language explanations to make NLP models more label-efficient, reliable, and easier to correct.

• YouTube
• 45 minutes
• Self-Paced
• Free Video

Open Data Science

Riding the Tailwind of NLP Explosion

A practical tour of NLP’s evolution, transformer applications, production pipeline modernization, and challenges such as long documents, prompting, and model explainability.

• YouTube
• 40 minutes
• Self-Paced
• Free Video

Graham Neubig

CMU Advanced NLP: Structured Learning Algorithms

A lecture on structured learning for NLP, covering globally normalized models, structured perceptrons, max-margin objectives, and remedies for exposure bias.

• YouTube
• 1 hour 20 minutes
• Self-Paced
• Free Video

Graham Neubig

CMU Advanced NLP: Information Extraction and Knowledge-Based QA

Explore knowledge graphs, relation extraction, and knowledge-based question answering through embeddings and language-model probing.

• YouTube
• 1 hour 18 minutes
• Self-Paced
• Free Video

Graham Neubig

Advanced NLP: Text-based QA

Explore text-based question answering through machine reading datasets, context encoding, retrieval, generative QA, and multi-hop reasoning.

• YouTube
• 1 hour 19 minutes
• Self-Paced
• Free Video