Overview
With the availability of large amounts of text data (such as documents generated from business processes, user created content on social media websites), businesses have found it increasingly essential to analyse such data for insights with automated support. Roles like data scientists, machine learning engineers, natural language processing engineers, AI engineers, chatbot developers are being sought for to perform text mining tasks, build automated text analytics solutions, develop systems that can interact with users in natural language, etc.
This certificate course has been designed to provide you with the fundamental and advanced skills in practical language processing to perform the above tasks. You’ll learn to pre-process text data into structural representation, apply supervised and unsupervised learning approaches to text processing tasks like document classification, topic modeling, information extraction, etc. You’ll also leverage on deep learning techniques to build deep neural network models for sentence classification, sequence labeling, text generation, etc. The application of these essential language processing skills are detailed in sentiment mining for business and the development of conversational UIs (chatbots).
Key Takeaways:
- Pre-process textual data into suitable representation for text analytics
- Build and evaluate language models using appropriate text processing techniques for tasks like document classification, topic modeling, information extraction, etc.
- Apply deep learning techniques on large amounts of textual data to obtain high quality models
- Extract and classify the sentiment polarity opinions from texual data
- Build service chatbots using traditional and machine learning approaches
Graduate Certificate
Participants who wish to continue their learning journey towards the Graduate Certificate will have to complete the required modular courses and a practice module.