CPD course All Levels

U&P AI - Natural Language Processing (NLP) with Python

4 enrolled 5h 50m of learning Updated Nov 2026
CertificateOn completion
5h 50mSelf-paced
66 lessonsOn the UISC learning portal
All LevelsNo prior training needed

Course curriculum

1 modules 66 lessons 5h 50m total
01 U&P AI - Natural Language Processing (NLP) with Python 66 lessons
  1. Module 01: Introduction to NLP
  2. Module 02: By the End of This Section
  3. Module 03: Installation
  4. Module 04: Tips
  5. Module 05: U – Tokenization
  6. Module 06: P – Tokenization
  7. Module 07: U – Stemming
  8. Module 08: P – Stemming
  9. Module 09: U – Lemmatization
  10. Module 10: P – Lemmatization
  11. Module 11: U – Chunks
  12. Module 12: P – Chunks
  13. Module 13: U – Bag of Words
  14. Module 14: P – Bag of Words
  15. Module 15: U – Category Predictor
  16. Module 16: P – Category Predictor
  17. Module 17: U – Gender Identifier
  18. Module 18: P – Gender Identifier
  19. Module 19: U – Sentiment Analyzer
  20. Module 20: P – Sentiment Analyzer
  21. Module 21: U – Topic Modeling
  22. Module 22: P – Topic Modeling
  23. Module 23: Summary
  24. Module 01: Introduction
  25. Module 02: One Hot Encoding
  26. Module 03: Count Vectorizer
  27. Module 04: N-grams
  28. Module 05: Hash Vectorizing
  29. Module 06: Word Embedding
  30. Module 07: FastText
  31. Module 02: In-built corpora
  32. Module 03: External Corpora
  33. Module 04: Corpuses & Frequency Distribution
  34. Module 05: Frequency Distribution
  35. Module 06: WordNet
  36. Module 07: Wordnet with Hyponyms and Hypernyms
  37. Module 08: The Average according to WordNet
  38. Module 01: Introduction and Challenges
  39. Module 02: Building your Vocabulary Part-01
  40. Module 03: Building your Vocabulary Part-02
  41. Module 04: Building your Vocabulary Part-03
  42. Module 05: Building your Vocabulary Part-04
  43. Module 06: Building your Vocabulary Part-05
  44. Module 07: Tokenization Dot Product
  45. Module 08: Similarity using Dot Product
  46. Module 09: Reducing Dimensions of your Vocabulary using token improvement
  47. Module 10: Reducing Dimensions of your Vocabulary using n-grams
  48. Module 11: Reducing Dimensions of your Vocabulary using normalizing
  49. Module 12: Reducing Dimensions of your Vocabulary using case normalization
  50. Module 13: When to use stemming and lemmatization?
  51. Module 14: Sentiment Analysis Overview
  52. Module 15: Two approaches for sentiment analysis
  53. Module 16: Sentiment Analysis using rule-based
  54. Module 17: Sentiment Analysis using machine learning – 1
  55. Module 18: Sentiment Analysis using machine learning – 2
  56. Module 19: Summary
  57. Module 02: Bag of words in detail
  58. Module 03: Vectorizing
  59. Module 04: Vectorizing and Cosine Similarity
  60. Module 05: Topic modeling in Detail
  61. Module 06: Make your Vectors will more reflect the Meaning, or Topic, of the Document
  62. Module 07: Sklearn in a short way
  63. Module 08: Summary
  64. Module 01: Keyword Search VS Semantic Search
  65. Module 02: Problems in TI-IDF leads to Semantic Search
  66. Module 03: Transform TF-IDF Vectors to Topic Vectors under the hood

About this course

Overview:

Welcome to "U&P AI Natural Language Processing"! This course offers a comprehensive exploration of Natural Language Processing (NLP) techniques using artificial intelligence. NLP is a field of AI that focuses on enabling computers to understand, interpret, and generate human language. In this course, you'll delve into the principles and applications of NLP, learning how to build NLP models for tasks such as text classification, sentiment analysis, and language translation.

  • Interactive video lectures by industry experts
  • Instant e-certificate and hard copy dispatch by next working day
  • Fully online, interactive course with Professional voice-over
  • Developed by qualified first aid professionals
  • Self paced learning and laptop, tablet, smartphone friendly
  • 24/7 Learning Assistance
  • Discounts on bulk purchases

Main Course Features:

  • Thorough coverage of NLP fundamentals, including tokenization, stemming, and part-of-speech tagging
  • Hands-on projects and exercises for practical application of NLP techniques
  • Introduction to popular NLP libraries and frameworks such as NLTK, SpaCy, and Transformers
  • Exploration of advanced NLP tasks such as named entity recognition and text summarization
  • Real-world case studies and examples showcasing NLP applications in various domains
  • Access to datasets and resources for experimenting with NLP models
  • Supportive online community for collaboration and assistance throughout the course
  • Regular updates to keep pace with the latest advancements in NLP and AI technologies

Who Should Take This Course:

  • Data scientists and AI enthusiasts interested in delving into the field of Natural Language Processing
  • Software engineers and developers looking to incorporate NLP capabilities into their applications
  • Students and professionals seeking to enhance their skills in AI and machine learning with a focus on NLP
  • Linguists and language enthusiasts curious about the intersection of AI and human language processing

Learning Outcomes:

  • Understand the core concepts and techniques of Natural Language Processing
  • Build and train NLP models for various tasks, including text classification and sentiment analysis
  • Implement advanced NLP techniques such as named entity recognition and text summarization
  • Explore popular NLP libraries and frameworks for developing NLP applications
  • Apply NLP models to real-world datasets and analyze their performance
  • Develop a portfolio of NLP projects showcasing proficiency in NLP techniques and tools
  • Stay updated with the latest advancements and trends in Natural Language Processing and AI
  • Contribute to the advancement of NLP research and applications through continued learning and experimentation.

Certification

Once you’ve successfully completed your course, you will immediately be sent a digital certificate. All of our courses are fully accredited, providing you with up-to-date skills and knowledge and helping you to become more competent and effective in your chosen field. Our certifications have no expiry dates, although we do recommend that you renew them every 12 months.

Assessment

At the end of the Course, there will be an online assessment, which you will need to pass to complete the course. Answers are marked instantly and automatically, allowing you to know straight away whether you have passed. If you haven’t, there’s no limit on the number of times you can take the final exam. All this is included in the one-time fee you paid for the course itself.

Your certificate

CPD certificate — download it when you finish

Issued the moment you complete the final module. Every certificate lists the course aims and objectives, anticipated learning outcomes, the quality-assurance process — the elements required for verifiable CPD. Non-registrants can use it as CQC training evidence and for appraisals.

Aims & objectives Learning outcomes Unique certificate number

Common questions

Where do I take the course?

On the UISC learning portal. "Enrol now" takes you to this course there, where you pay securely, get your login and study at your own pace. Your certificate is issued there when you finish.

When can I start?

Immediately. Access opens the moment your order is confirmed and you can learn from any device, in any order, as many times as you like.

How is the course assessed?

A short multiple-choice or scenario-based assessment at the end of the course with instant results. You can retake it as many times as you need at no extra cost.

Can I enrol my whole team?

Yes. Organisations can buy multiple places on one invoice and receive a training record for every learner. Contact us for team pricing.

£39.00 5h 50m · All Levels
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