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What You'll Learn

Master text analytics with natural language processing (NLP). Learn to extract meaning from text data, analyze sentiment, and gain valuable insights from unstructured text.

Course Benefits
Industry Certification

Internationally recognized qualification

Expert Instructors

Learn from industry professionals

Dedicated Support

Assistance during and after training

Practical Skills

Apply knowledge immediately

Comprehensive 5-day curriculum with all materials included
Hands-on exercises and real-world case studies
Valuable networking opportunities with peers and experts
Post-course resources and refresher materials
Training on Text Analytics with Natural Language Processing (NLP) - Course Cover Image
Duration 5 Days
Level Advanced
Format In-Person

Course Overview

Featured

This course provides a comprehensive introduction to Text Analytics using Natural Language Processing (NLP). It is designed to help participants understand the techniques and tools used to analyze, process, and derive insights from textual data. The course covers key concepts such as text preprocessing, tokenization, sentiment analysis, topic modeling, and text classification. Through hands-on exercises and real-world examples, participants will learn how to apply NLP techniques to various applications, including sentiment analysis, customer feedback analysis, and automated content generation.

Course Duration

5 Days

Who Should Attend

  • Data scientists
  • Data analysts
  • Machine learning engineers
  • Business analysts
  • Anyone interested in leveraging text data for insights

Course Impact

Organizational Impact

  • Unlocks insights from unstructured text data to understand customer sentiment, market trends, and operational issues.

  • Enables actionable intelligence for better products, services, and customer satisfaction.

  • Automates tasks like support ticket routing and spam detection, improving efficiency and reducing costs.

  • Strengthens competitive position through faster, data-driven responses to market signals.

Personal Impact

  • Develops specialized skills in NLP and text analytics, essential for senior data science or analytics roles.

  • Empowers participants to transform unstructured data into valuable business insights.

  • Builds confidence to lead and champion advanced text analytics initiatives.

Course Objectives

By the end of this course, participants will be able 

  • Understand the fundamentals of natural language processing
  • Preprocess text data for analysis
  • Apply various NLP techniques to extract information from text
  • Build text classification and sentiment analysis models
  • Utilize NLP for information retrieval and summarization

Course Outline

Module 1: Unlocking the World of Natural Language Processing (NLP)

  • Discover how machines understand human language
  • What NLP is and why it matters
  • Tokenization, stemming, lemmatization & stop-word removal
  • NLP applications across industries
  • Case Study:How global tech companies use NLP for personalization and automation
  • Practical Session:Build a simple preprocessing workflow (tokenization & stop-word removal)

Module 2: Transforming Raw Text Into Usable Data – Text Preprocessing

  • Prepare and refine text for deeper analysis
  • Text cleaning and normalization
  • Handling incomplete or noisy text
  • Bag-of-Words & TF-IDF
  • N-grams and basic language models
  • Case Study:Cleaning and preparing social media data for large-scale analysis
  • Practical Session:Clean a real text dataset and generate TF-IDF & N-gram features

Module 3: Crafting Powerful Features – Feature Engineering for Text

  • Turn text into meaningful numerical insights
  • Text feature extraction
  • Feature selection & dimensionality reduction
  • Word embeddings (Word2Vec, GloVe)
  • Case Study:Use of text embeddings in detecting patterns for fraud prevention
  • Practical Session:Train Word2Vec and explore word similarity relationships

Module 4: Building Intelligent Models – Text Classification & Sentiment Analysis

Develop models that read and interpret language

  • Supervised text classification
  • Naive Bayes, SVM, Random Forest
  • Sentiment analysis techniques
  • Model performance metrics
  • Case Study:Sentiment analysis for brand monitoring and customer insights
  • Practical Session:Build and evaluate a sentiment classifier using real text data

Module 5: Exploring Cutting-Edge NLP

Step into advanced and emerging NLP technologies

  • Named Entity Recognition (NER)
  • Text summarization
  • Information retrieval
  • Natural Language Generation (NLG)
  • Case Study:Automated summarization and entity extraction in news intelligence
  • Practical Session:Extract named entities and generate short text summaries

Prerequisites

No specific prerequisites required. This course is suitable for beginners and professionals alike.

Course Administration Details

Customized Training

This training can be tailored to your institution needs and delivered at a location of your choice upon request.

Requirements

Participants need to be proficient in English.

Training Fee

The fee covers tuition, training materials, refreshments, lunch, and study visits. Participants are responsible for their own travel, visa, insurance, and personal expenses.

Certification

Upon successful completion of this course, participants will be issued with a certificate from Ideal Workplace Solutions certified by the National Industrial Training Authority (NITA) under License NO: NITA/TRN/2734.

Accommodation

Accommodation can be arranged upon request. Contact via email for reservations.

Payment

Payment should be made before the training starts, with proof of payment sent to outreach@idealworkplacesolutions.org.

For further inquiries, please contact us on details below:

Register for the Course

Select a date and location that works for you.

In-Person Training Schedules


January 2026
Date Days Venue Fee (VAT Incl.) Register
5 Jan - 9 Jan 2026 5 days Nairobi, Kenya KES 99,000 | USD 1,400 Enroll Now
5 Jan - 9 Jan 2026 5 days Cape Town, South Africa USD 3,500 Enroll Now
5 Jan - 9 Jan 2026 5 days Dubai, United Arabs Emirates USD 4,000 Enroll Now
5 Jan - 9 Jan 2026 5 days Zanzibar, Tanzania USD 2,200 Enroll Now
12 Jan - 16 Jan 2026 5 days Mombasa, Kenya KES 115,000 | USD 1,500 Enroll Now
12 Jan - 16 Jan 2026 5 days Kigali, Rwanda USD 1,800 Enroll Now
12 Jan - 16 Jan 2026 5 days Accra, Ghana USD 5,950 Enroll Now
12 Jan - 16 Jan 2026 5 days Kampala, Uganda USD 2,200 Enroll Now
19 Jan - 23 Jan 2026 5 days Dar es Salaam, Tanzania USD 2,000 Enroll Now
19 Jan - 23 Jan 2026 5 days Johannesburg, South Africa USD 3,100 Enroll Now
19 Jan - 23 Jan 2026 5 days Nakuru, Kenya KES 105,000 | USD 1,400 Enroll Now
19 Jan - 23 Jan 2026 5 days Dakar, Senegal USD 3,500 Enroll Now
26 Jan - 30 Jan 2026 5 days Pretoria, South Africa USD 3,100 Enroll Now
26 Jan - 30 Jan 2026 5 days Kisumu, Kenya KES 105,000 | USD 1,500 Enroll Now
26 Jan - 30 Jan 2026 5 days Naivasha, Kenya KES 105,000 | USD 1,400 Enroll Now
26 Jan - 30 Jan 2026 5 days Arusha, Tanzania USD 2,000 Enroll Now
5 Jan - 9 Jan 2026
5 days
Venue:
Nairobi, Kenya
Fee (VAT Incl.):
KES 99,000
USD 1,400
Enroll Now
5 Jan - 9 Jan 2026
5 days
Venue:
Cape Town, South Africa
Fee (VAT Incl.):
USD 3,500
Enroll Now
5 Jan - 9 Jan 2026
5 days
Venue:
Dubai, United Arabs Emirates
Fee (VAT Incl.):
USD 4,000
Enroll Now
5 Jan - 9 Jan 2026
5 days
Venue:
Zanzibar, Tanzania
Fee (VAT Incl.):
USD 2,200
Enroll Now
12 Jan - 16 Jan 2026
5 days
Venue:
Mombasa, Kenya
Fee (VAT Incl.):
KES 115,000
USD 1,500
Enroll Now
12 Jan - 16 Jan 2026
5 days
Venue:
Kigali, Rwanda
Fee (VAT Incl.):
USD 1,800
Enroll Now
12 Jan - 16 Jan 2026
5 days
Venue:
Accra, Ghana
Fee (VAT Incl.):
USD 5,950
Enroll Now
12 Jan - 16 Jan 2026
5 days
Venue:
Kampala, Uganda
Fee (VAT Incl.):
USD 2,200
Enroll Now
19 Jan - 23 Jan 2026
5 days
Venue:
Dar es Salaam, Tanzania
Fee (VAT Incl.):
USD 2,000
Enroll Now
19 Jan - 23 Jan 2026
5 days
Venue:
Johannesburg, South Africa
Fee (VAT Incl.):
USD 3,100
Enroll Now
19 Jan - 23 Jan 2026
5 days
Venue:
Nakuru, Kenya
Fee (VAT Incl.):
KES 105,000
USD 1,400
Enroll Now
19 Jan - 23 Jan 2026
5 days
Venue:
Dakar, Senegal
Fee (VAT Incl.):
USD 3,500
Enroll Now
26 Jan - 30 Jan 2026
5 days
Venue:
Pretoria, South Africa
Fee (VAT Incl.):
USD 3,100
Enroll Now
26 Jan - 30 Jan 2026
5 days
Venue:
Kisumu, Kenya
Fee (VAT Incl.):
KES 105,000
USD 1,500
Enroll Now
26 Jan - 30 Jan 2026
5 days
Venue:
Naivasha, Kenya
Fee (VAT Incl.):
KES 105,000
USD 1,400
Enroll Now
26 Jan - 30 Jan 2026
5 days
Venue:
Arusha, Tanzania
Fee (VAT Incl.):
USD 2,000
Enroll Now

Request Custom Training


We offer customized training solutions tailored to your organization's specific needs:

  • Training at your preferred location
  • Customized content to address your specific challenges
  • Flexible scheduling to accommodate your team
  • Cost-effective solution for training multiple employees
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Frequently Asked Questions

Find answers to common questions about this course

The goal is to equip you with the skills to use Natural Language Processing (NLP) to analyze large volumes of text data, extract valuable insights, and inform business decisions.
Text analytics is the process of extracting insights from text, while NLP provides the tools and techniques (like sentiment analysis or topic modeling) to perform that analysis.
You will learn core techniques like text cleaning, tokenization, and vectorization, as well as more advanced methods for sentiment analysis, named entity recognition, and topic modeling.
You'll learn to apply text analytics to customer feedback, social media, and other text data to identify trends, improve services, and make data-driven decisions.
The training will focus on using Python with popular libraries like NLTK, spaCy, and scikit-learn, which are industry standards for NLP tasks.
Training on Text Analytics with Natural Language Processing (NLP)

Next class starts 5 Jan 2026

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