Skip to content
  1. Online
  2. IT
  3. Artificial Intelligence
Practical NLP Projects & Case Studies cover image
Play overlay
Preview this course

Practical NLP Projects & Case Studies
Xcel Learning

Assessment Included • Free Certificate • 24/7 Support • No Hidden Fees

Summary

Price
£22 inc VAT
Study method
Online, On Demand 
Duration
1.1 hours · Self-paced
Qualification
No formal qualification
Certificates
  • Reed Courses Certificate of Completion - Free
Assessment details
  • Review Questions and Assessments (included in price)
Additional info
  • Tutor is available to students

Add to basket or enquire

Overview

Practical NLP Projects & Case Studies is a hands-on, industry-focused course designed to bridge the gap between theoretical Natural Language Processing concepts and real-world implementation. The course guides learners through end-to-end NLP system development, covering text preprocessing, representation techniques, classification, named entity recognition, clustering, information retrieval, language modeling, question answering, conversational AI, summarization, social media analytics, and production deployment. Emphasis is placed on practical experimentation, model evaluation, scalability, ethical considerations, and system integration. Through case studies and applied assessments, students build robust, production-ready NLP solutions that address real business challenges. By the end of the course, learners will be equipped to design, implement, evaluate, and deploy intelligent language-driven applications with confidence and professional rigor.

Certificates

Assessment details

Review Questions and Assessments

Included in course price

Curriculum

13
sections
13
lectures
1h 8m
total

Description

Exciting Journey Ahead: Discover What Awaits in This Course!

Chapter 1: Foundations of Practical NLP

  1. NLP Applications in Industry
  2. Text Preprocessing Techniques (Tokenization, Lemmatization, Cleaning)
  3. Working with Text Data Formats (CSV, JSON, APIs)
  4. Exploratory Data Analysis (EDA) for Text
  5. Setting Up NLP Development Environment (Python, Jupyter, Libraries)

Chapter 2: Text Representation Techniques

  1. Bag of Words (BoW)
  2. TF-IDF Vectorization
  3. Word Embeddings (Word2Vec, GloVe)
  4. Contextual Embeddings (BERT Basics)
  5. Feature Engineering for Text Models

Chapter 3: Text Classification Projects

  1. Spam Detection System
  2. Sentiment Analysis for Product Reviews
  3. News Topic Classification
  4. Toxic Comment Detection
  5. Model Evaluation Metrics (Accuracy, F1, ROC-AUC)

Chapter 4: Named Entity Recognition (NER) Case Studies

  1. Rule-Based vs ML-Based NER
  2. Custom NER Model Training
  3. Resume Information Extraction
  4. Healthcare Entity Recognition
  5. Evaluation & Error Analysis for NER

Chapter 5: Text Clustering & Topic Modeling

  1. K-Means for Document Clustering
  2. Hierarchical Clustering for Text
  3. Topic Modeling with LDA
  4. Dynamic Topic Modeling
  5. Visualizing Topics and Clusters

Chapter 6: Information Retrieval & Search Systems

  1. Building a Basic Search Engine
  2. Inverted Index Implementation
  3. Semantic Search with Embeddings
  4. Ranking Algorithms (BM25 Basics)
  5. Case Study: FAQ Retrieval System

Chapter 7: Sequence Modeling & Language Models

  1. N-gram Language Models
  2. RNN & LSTM for Text Generation
  3. Transformer Architecture Overview
  4. Fine-Tuning Pretrained Models
  5. Case Study: Auto-Complete System

Chapter 8: Question Answering Systems

  1. Extractive Question Answering
  2. Building QA with Transformers
  3. Context Passage Retrieval
  4. Evaluating QA Systems (EM, F1)
  5. Case Study: Customer Support Bot

Chapter 9: Chatbots & Conversational AI

  1. Rule-Based Chatbots
  2. Intent Classification & Slot Filling
  3. Dialogue State Management
  4. Retrieval vs Generative Chatbots
  5. Case Study: E-commerce Chatbot

Chapter 10: Text Summarization Projects

  1. Extractive Summarization Techniques
  2. Abstractive Summarization with Transformers
  3. Summarizing News Articles
  4. Meeting Transcript Summarization
  5. Evaluation Metrics (ROUGE, BLEU Basics)

Chapter 11: NLP for Social Media Analytics

  1. Hashtag & Trend Analysis
  2. Fake News Detection
  3. Emotion & Sarcasm Detection
  4. Social Network Text Mining
  5. Case Study: Brand Sentiment Dashboard

Chapter 12: Productionizing NLP Systems

  1. Model Deployment with APIs
  2. Building NLP Pipelines
  3. Model Monitoring & Drift Detection
  4. Scaling NLP with Cloud Services
  5. Capstone Project: End-to-End NLP Solution

Unleash Your Potential: Join Us Today and Elevate Your Skills with a Prestigious Digital Certificate upon Course Completion!

Who is this course for?

This course is designed for aspiring data scientists, AI engineers, and software developers who want hands-on experience with Natural Language Processing. It’s ideal for learners familiar with Python and basic machine learning, aiming to build real-world NLP applications, solve practical problems, and gain industry-relevant skills through projects and case studies.

Questions and answers

There are currently no Q&As for this course. Be the first to ask a question.

Ask a question

Reviews

Currently there are no reviews for this course. Be the first to leave a review.

Leave a review

Legal information

This course is advertised on Reed.co.uk by the Course Provider, whose terms and conditions apply. Purchases are made directly from the Course Provider, and as such, content and materials are supplied by the Course Provider directly. Reed is acting as agent and not reseller in relation to this course. Reed's only responsibility is to facilitate your payment for the course. It is your responsibility to review and agree to the Course Provider's terms and conditions and satisfy yourself as to the suitability of the course you intend to purchase. Reed will not have any responsibility for the content of the course and/or associated materials.

FAQs

Study method describes the format in which the course will be delivered. At Reed Courses, courses are delivered in a number of ways, including online courses, where the course content can be accessed online remotely, and classroom courses, where courses are delivered in person at a classroom venue.

CPD stands for Continuing Professional Development. If you work in certain professions or for certain companies, your employer may require you to complete a number of CPD hours or points, per year. You can find a range of CPD courses on Reed Courses, many of which can be completed online.

A regulated qualification is delivered by a learning institution which is regulated by a government body. In England, the government body which regulates courses is Ofqual. Ofqual regulated qualifications sit on the Regulated Qualifications Framework (RQF), which can help students understand how different qualifications in different fields compare to each other. The framework also helps students to understand what qualifications they need to progress towards a higher learning goal, such as a university degree or equivalent higher education award.

An endorsed course is a skills based course which has been checked over and approved by an independent awarding body. Endorsed courses are not regulated so do not result in a qualification - however, the student can usually purchase a certificate showing the awarding body's logo if they wish. Certain awarding bodies - such as Quality Licence Scheme and TQUK - have developed endorsement schemes as a way to help students select the best skills based courses for them.
View all
Similar subjects: Artificial Intelligence, IT
Related searches: Online courses

Interest free credit agreements provided by Zopa Bank Limited trading as DivideBuy are not regulated by the Financial Conduct Authority and do not fall under the jurisdiction of the Financial Ombudsman Service. Zopa Bank Limited trading as DivideBuy is authorised by the Prudential Regulation Authority and regulated by the Financial Conduct Authority and the Prudential Regulation Authority, and entered on the Financial Services Register (800542). Zopa Bank Limited (10627575) is incorporated in England & Wales and has its registered office at: 1st Floor, Cottons Centre, Tooley Street, London, SE1 2QG. VAT Number 281765280. DivideBuy's trading address is First Floor, Brunswick Court, Brunswick Street, Newcastle-under-Lyme, ST5 1HH. © Zopa Bank Limited 2026. All rights reserved.