Natural Language Processing ExpertTrack Pathway
Progress from text preprocessing to sentiment analysis, deep learning, and transformers on a practical NLP pathway.
Duration
Approx 9 weeks3 hrs per week
Turn language into insight with natural language processing
Natural Language Processing helps machines interpret, classify, and work with human language.
On this three-course ExpertTrack, you’ll move from preparing raw text for analysis to creating increasingly advanced systems for language understanding.
Start with the foundations of NLP, exploring how unstructured text is cleaned, normalised, and transformed into numerical features.
You’ll work with tokenisation, lemmatisation, n-grams, bag-of-words, and TF-IDF before assembling a reusable text preprocessing pipeline.
Move from text processing to prediction
Progress into text classification and sentiment analysis, exploring labelled datasets, linguistic features, supervised approaches, and word embeddings including Word2Vec and GloVe.
You’ll also examine challenges such as negation, sarcasm, and domain shift.
Explore deep learning and transformer models
Advance into RNNs, LSTMs, GRUs, attention, and transformer architecture before working with pretrained models such as BERT.
You’ll explore transfer learning and fine-tuning for tasks including named entity recognition, question answering, and text summarisation.
Apply NLP across real language tasks
Across the pathway, you’ll progress from structuring text to interpreting meaning and creating end-to-end language applications.
By the end, you’ll have practical NLP experience relevant to roles across AI, data science, machine learning, and language technology.
Key skills you will learn
- AI
- Machine Learning
- Natural language processing
Experience required
This ExpertTrack is ideal for aspiring NLP engineers, data scientists, machine learning practitioners, Python developers, and analysts who want to progress from text processing fundamentals to modern language understanding systems.
This is a progressive pathway that begins at introductory level. No previous NLP experience is required, but you should have a basic understanding of Python and fundamental programming concepts. Later courses build on earlier skills in text preprocessing, classification, model evaluation, and word embeddings before moving into deep learning and transformers.
Getting started
Choose this ExpertTrack if you want to understand how machines turn text into meaningful information and apply NLP techniques to real language problems.
It is especially relevant if you are aiming for roles in NLP, data science, machine learning, or AI, or want to work with text-driven products and insights across sectors such as technology, finance, healthcare, e-commerce, and research.
ExpertTrack course overview
Course 1
Natural Language Processing (NLP) and Text Processing Foundations
Discover how NLP transforms raw language into structured data using practical Python techniques for processing, and analysing data
3 tests
3 weeks
3 hours per week
Week 1
Foundations for NLP and Text Preparation
- Connect Human Language to NLP
- Transform Raw Text for NLP Workflows
- Clean and Normalise Text for Reliable Processing
Week 2
Transform Text into Features for NLP Models
- Tokenise and Normalise Text for Language Processing
- Reduce Word Variation with Stemming and Lemmatisation
- Represent Text with Linguistic and Numerical Features
Week 3
Build and Evaluate Classical NLP Solutions
- Prepare Complex Text for Real-World NLP
- Build and Assess Text Classification Models
- Implement an End-to-End Text Classification Workflow
Course 2
Text Classification and Sentiment Analysis
Apply NLP and machine learning techniques to classify text, interpret sentiment, and uncover meaning in real-world language data.
3 tests
3 weeks
3 hours per week
Week 1
Text Representations for NLP
- Handle Complex Vocabulary with Subword Tokenisation
- Adapt Tokenisation for Diverse Language Data
- Capture Meaning with Richer Text Representations
Week 2
From Sentiment Rules to Transformer Models
- Detect Sentiment with Lexicons and Rules
- Develop Machine Learning Sentiment Classifiers
- Advance Sentiment Analysis with Deep Learning
Week 3
Sentiment Analysis Across Real-World Contexts
- Track Sentiment Trends and Event Impact
- Explore Sentiment Across Aspects and Languages
- Promote Responsible Sentiment Analysis
Course 3
Transformer Models and Language Understanding Systems
Advance into deep learning, attention, and transformer models to create sophisticated systems for language understanding.
3 tests
3 weeks
3 hours per week
Week 1
From Neural Language Models to Transformers
- Explore Neural Architectures for Language Processing
- Capture Language Context with Attention
- Adapt Pretrained Models for NLP Tasks
Week 2
Neural and Transformer-Based Machine Translation
- Navigate Machine Translation Methods and Challenges
- Develop Neural Machine Translation Systems
- Enhance Translation with Transformer Models
Week 3
Intelligent Language Systems for Emerging Applications
- Connect Speech, Text and Visual Information
- Optimise NLP Systems for Efficient and Responsible Use
- Create Context-Aware Conversational Systems
Prove you're job ready
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- Learn the latest in your chosen industry or subject.
- Complete each course and pass assessments.
- Receive certificates validated by the educating organisation.
- Impress employers with learning outcomes you can add to your CV.
- Make your career dreams a reality.
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