Natural Language Processing (NLP) Training Course

ICTI and Partners Certification

1 Week

20 hours

Classroom, In-House, Online

Price: £3500

Group discounts available. Get Registered for more details.

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The Natural Language Processing (NLP) Training Course at Imperial Corporate Training Institute is a comprehensive and industry-focused artificial intelligence training course designed to equip professionals with advanced skills in text analytics, language modelling, and intelligent automation. Natural Language Processing is one of the fastest-growing domains in artificial intelligence, enabling machines to understand, interpret, and generate human language. From chatbots and virtual assistants to sentiment analysis and machine translation, NLP powers many of today’s most innovative technologies. This course provides a structured pathway from foundational linguistic concepts to advanced deep learning models used in real-world AI systems.

Participants will gain hands-on experience in building NLP applications using modern tools and frameworks. The course covers text preprocessing, feature extraction, machine learning algorithms, transformer-based architectures, and real-time deployment strategies. Delivered as part of our artificial intelligence training course portfolio, this programme combines theoretical depth with practical implementation to ensure participants can design, develop, and optimise NLP solutions for enterprise use. By the end of this training, learners will confidently apply NLP techniques to solve complex business problems, automate text-driven workflows, and develop intelligent systems that understand human language with accuracy and efficiency.

Objectives

By the end of this Natural Language Processing (NLP) Training Course, participants will be able to:

Understand the core concepts of Natural Language Processing and computational linguistics
Perform effective text preprocessing and data cleaning techniques
Apply tokenisation, stemming, lemmatisation, and part-of-speech tagging
Implement machine learning algorithms for text classification and sentiment analysis
Build language models using statistical and deep learning approaches
Develop chatbot and conversational AI solutions
Use transformer-based models such as BERT and GPT architectures
Evaluate NLP model performance using industry-standard metrics
Deploy NLP solutions into production environments
Integrate NLP systems with enterprise applications and business intelligence platforms

Target Audience

This artificial intelligence training course is ideal for:

Data scientists and AI engineers
Software developers interested in AI applications
Machine learning professionals seeking NLP specialisation
IT managers overseeing AI-driven projects
Business intelligence analysts working with text data
Digital transformation professionals
Researchers and academics in artificial intelligence
Technology consultants implementing AI solutions
Professionals in finance, healthcare, retail, and telecom industries
Anyone seeking advanced knowledge in Natural Language Processing within enterprise environments

Course Modules

Overview of NLP and its business applications
History and evolution of NLP technologies
Key NLP tasks and use cases in modern industries
Understanding text data structures
Challenges in language processing

Text cleaning and normalization techniques
Tokenisation methods
Stop-word removal and text filtering
Stemming and lemmatisation
Part-of-speech tagging and syntactic analysis
Named Entity Recognition (NER) fundamentals

Bag-of-Words model
TF-IDF representation
Word embeddings and vectorisation techniques
Word2Vec and GloVe concepts
Contextual embeddings
Handling imbalanced datasets

Supervised vs unsupervised learning in text analytics
Text classification models
Sentiment analysis techniques
Naïve Bayes, SVM, and logistic regression for NLP
Topic modelling with LDA
Model evaluation metrics (Precision, Recall, F1-score, Accuracy)

Introduction to neural networks for language processing
Recurrent Neural Networks (RNNs)
LSTM and GRU architectures
Sequence-to-sequence models
Attention mechanisms
Practical implementation of deep learning models

Introduction to transformer architecture
BERT and its applications
GPT-based language models
Fine-tuning pre-trained language models
Transfer learning in NLP
Building custom NLP pipelines

Designing conversational agents
Intent recognition and entity extraction
Dialogue management systems
Integration with messaging platforms
Voice-based NLP systems
Testing and optimisation of chatbot performance

Sentiment analysis for customer feedback
Social media analytics
Document summarisation
Information extraction from reports
Fraud detection using text mining
Compliance and risk monitoring

Model optimisation techniques
API development for NLP models
Cloud deployment strategies
Real-time inference systems
Monitoring and maintaining NLP models
Ethical considerations and bias mitigation

FAQs

What is Natural Language Processing (NLP)?

Natural Language Processing is a branch of artificial intelligence that enables computers to understand, interpret, and generate human language in text and speech formats.

Is this course suitable for beginners?

This course is designed for professionals with basic knowledge of programming and machine learning. However, foundational concepts are covered before moving to advanced topics.

What tools and technologies are covered in this NLP training?

Participants will work with popular NLP libraries and frameworks such as Python-based NLP tools, deep learning frameworks, and transformer-based models.

Will there be practical exercises?

Yes, this artificial intelligence training course includes hands-on labs, real-world case studies, and a capstone project to ensure practical application of knowledge.

How can NLP benefit my organisation?

NLP can automate customer support, analyse large volumes of text data, improve decision-making, enhance user experiences, and reduce operational costs.

Course Dates

Availiable Dates

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July 6, 2026

May 18, 2026

October 17, 2026

January 16, 2027

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