Program profile · official sources
Intro to NLP for AI
365 Data Science's 'Intro to NLP for AI' is an intermediate self-paced course taught by Lauren Newbould, focusing on foundational natural language processing techniques. Over a headline duration of four hours, the curriculum covers text preprocessing, tokenization, lemmatization, part-of-speech tagging, and named entity recognition. Students explore sentiment analysis, text vectorization using Bag of Words and TF-IDF, topic modeling with LDA and LSA, and building text classifiers with logistic regression, naive Bayes, and SVMs. The training culminates in an applied case study categorizing fake news and awards 4.5 CPE credits. Earning the verifiable certificate requires scoring 60% or higher on the 30-minute exam. The formal prerequisites state that basic Python is required and no prior NLP or machine-learning experience is necessary; the course description separately asks for basic Python and familiarity with machine learning. These source statements differ.
Facts checked 27 Sep 2026
- Price
- See pricing
Price observation recorded 27 Sep 2026 (not a current price): No total course price is stated. The platform-wide Self-Study plan displays a regular comparison price of $36/month, an observed $12.50/month billed annually offer, and an FAQ mentions a $29/month rate, as observed in United States captures dated 2026-09-27. ISO currency and a separately monthly-billed amount were not established; these subscription rates are not treated as a source-checked completion total. Certificates are included with the Self-study learning plan.
- Time
- 4 hours
- (provider headline; module and exam timings listed separately)
- Level
- Intermediate
- Credential
- Provider-issued certification
Verifiable credential with Credential ID and Credential Link; sharable on LinkedIn/resumes; downloadable upon passing. Certificates are included with the Self-study learning plan.
- Prerequisites
- Python (version 3.8 or later), Natural Language Toolkit (NLTK) and pandas libraries, and a code editor or IDE (e.g., Jupyter Notebook, Spyder, or VS Code) Basic understanding of Python programming is required. No prior experience with natural language processing or machine learning is necessary. The course description separately asks for familiarity with machine learning, conflicting with the formal no-prior-machine-learning-experience statement.
Commercial status: no commercial relationship is documented for this page. The verification link goes directly to the official provider source.
- Duration
- 4 hours (provider headline; module and exam timings listed separately)
- Level
- Intermediate
- Format
- 100% online, self-paced course
- Credential
- Provider-issued certification
- Prerequisites
- Python (version 3.8 or later), Natural Language Toolkit (NLTK) and pandas libraries, and a code editor or IDE (e.g., Jupyter Notebook, Spyder, or VS Code) Basic understanding of Python programming is required. No prior experience with natural language processing or machine learning is necessary. The course description separately asks for familiarity with machine learning, conflicting with the formal no-prior-machine-learning-experience statement.
Sources ↗
No accepted numeric price in this registry. See the sourced pricing details below.
See the full registry price landscape. Prices retain their stated payment scope; they are not comparable completion costs.
What’s covered
- Introduction
- Text Preprocessing
- Identifying Parts of Speech and Named Entities
- Sentiment Analysis
- Vectorizing Text
- Topic Modelling
- Builing your own text classifier
- Case Study: Categorizing Fake News
- The Future of NLP
- Course exam
Prerequisites: Python (version 3.8 or later), Natural Language Toolkit (NLTK) and pandas libraries, and a code editor or IDE (e.g., Jupyter Notebook, Spyder, or VS Code) Basic understanding of Python programming is required. No prior experience with natural language processing or machine learning is necessary. The course description separately asks for familiarity with machine learning, conflicting with the formal no-prior-machine-learning-experience statement.
What you actually do
- Introduction · 9 min; Section 1 · Source
- Text Preprocessing · 57 min; Section 2 · Source
- Identifying Parts of Speech and Named Entities · 33 min; Section 3 · Source
- Sentiment Analysis · 26 min; Section 4 · Source
- Vectorizing Text · 10 min; Section 5 · Source
- Topic Modelling · 25 min; Section 6 · Source
- Builing your own text classifier · 17 min; Section 7 · Source
- Case Study: Categorizing Fake News · 51 min; Section 8 · Source
- The Future of NLP · 9 min; Section 9 · Source
- Course exam · 30 min; Section 10 · Source
What the credential is
- Credential type
- Provider-issued certification · 365datascience.com / intro-to-nlp-for-ai
- Credential
- Course Certificate · 365datascience.com / certificates
- Issuer
- 365 Data Science · 365datascience.com / certificates
- Sharing
- Verifiable credential with Credential ID and Credential Link; sharable on LinkedIn/resumes; downloadable upon passing. Certificates are included with the Self-study learning plan. · 365datascience.com / certificates
- Exam requirement
- Pass the course exam; general certificate terms state 60% or above. Certificates are included with the Self-study learning plan. · 365datascience.com / certificates
- Credential expires
- provider does not state · 365datascience.com / intro-to-nlp-for-ai
- Renewal
- provider does not state · 365datascience.com / intro-to-nlp-for-ai
Who should skip it
- Check the differing preparation statements before enrolling: The formal prerequisites state that basic Python is required and no prior NLP or machine-learning experience is necessary; the course description separately asks for basic Python and familiarity with machine learning. These source statements differ. · Official source · 2026-09-27
Alternatives in the registry
Related by topic or level.
- Finetuning with Llama · Check official price; 2 hours (provider headline; section and exam times listed separately).
- Intro to LLMs · Check official price; 3 hours (provider headline; module and exam timings listed separately).
- Introduction to LLaMA · Check official price; 2 hours (provider headline; module and exam timings listed separately).
Change log
- : Initial recorded review of official program details. · Source
Cost details
The course requires Python 3.8+, NLTK, pandas, and an IDE. No course-specific completion fee is established; access is provided via platform-wide subscription plans.
Official source · 2026-09-27