Natural Language Processing (NLP) (Synchronous E-learning)
About This Course
Natural Language Processing (NLP) techniques for real-world applications. Covering the full workflow—from text preprocessing and word embeddings to sequence models, machine translation, speech/audio analytics, and optimisation—learners will develop both conceptual understanding and practical expertise. Assessments combine written exams (testing conceptual knowledge) with project presentations (demonstrating applied ability), ensuring balanced learning outcomes. By the end of the course, participants will be able to critically evaluate NLP methods, justify their applications, and refine models for accurate and efficient deployment in business contexts
What You'll Learn
- Identify application areas and common tasks associated with Natural Language Processing
- Apply text preprocessing and word embedding techniques to prepare textual data for language modelling
- Develop language models for textual data using n-gram language models
- Determine suitable deep learning architectures for Natural Language Processing tasks
- Train NLP models using backpropagation, regularisation, and loss functions to optimise performance
- Enhance NLP models using encoder-decoder architectures, memory networks, and Bayesian reasoning techniques
Entry Requirements
Age: 25 years and above
Education: At least a GCE 'O' Level certificate/ GCE ‘N’ Level (Normal Academic stream), Nitec or Higher Nitec qualifications. Applicants without formal academic qualifications may also be considered if they have relevant work experience and computer knowledge
Digital Proficiency: Comfortable using digital tools and workplace software (e.g., Microsoft Excel, cloud-based platforms). Able to perform basic computer tasks such as internet search, creating folders, and copy-paste operations
Technical Experience: No coding experience is required