Professional Certificate in Applied AI for Educators
Training Provider: NANYANG TECHNOLOGICAL UNIVERSITY
Course Reference: TGS-2025059181
S$3,600
Original: S$7,200
Save S$3,600
About This Course
This innovative programme is designed to equip teachers with the knowledge and skills to effectively integrate Artificial Intelligence into their teaching practices. This programme aims to enhance the educational experience by leveraging Artificial Intelligence technologies to create more personalised, efficient, and engaging learning environments.
At the end of the programme, learners will be well-equipped to harness the power of Artificial Intelligence in their educational environments, ensuring that they are prepared for the future of teaching and learning.
What You'll Learn
- Write Python programmes and execute them using three different methods: Jupyter Notebooks, Python’s Integrated Development and Learning Environment (IDLE) and the command line.
- Import and use the Python standard and external libraries.
- Visualise 2D data using Matplotlib.
- Master data collection and preparation techniques.
- Gain proficiency in descriptive, inferential, and predictive analytics methods, enabling them to identify patterns, make data-driven decisions, and predict student outcome.
- Understand the fundamentals of machine learning and how it can be applied in education.
- Apply supervised and unsupervised learning techniques to analyse and interpret data.
- Evaluate and validate machine learning models using appropriate metrics and techniques.
- Explore real-world applications of machine learning through case studies.
- Apply machine learning techniques to a real-world dataset through a project.
- Understand the fundamentals of Natural Language Processing.
- Preprocess and prepare text data for analysis.
- Represent text data using different techniques.
- Apply Natural Language Processing techniques for text classification and sentiment analysis.
- Explore advanced Natural Language Processing topics such as Named Entity Recognition and Topic Modelling.
- Import and use the Python standard and external libraries.
- Visualise 2D data using Matplotlib.
- Master data collection and preparation techniques.
- Gain proficiency in descriptive, inferential, and predictive analytics methods, enabling them to identify patterns, make data-driven decisions, and predict student outcome.
- Understand the fundamentals of machine learning and how it can be applied in education.
- Apply supervised and unsupervised learning techniques to analyse and interpret data.
- Evaluate and validate machine learning models using appropriate metrics and techniques.
- Explore real-world applications of machine learning through case studies.
- Apply machine learning techniques to a real-world dataset through a project.
- Understand the fundamentals of Natural Language Processing.
- Preprocess and prepare text data for analysis.
- Represent text data using different techniques.
- Apply Natural Language Processing techniques for text classification and sentiment analysis.
- Explore advanced Natural Language Processing topics such as Named Entity Recognition and Topic Modelling.
Entry Requirements
There are no formal entry requirements or prior qualifications needed.
Course Details
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Note: To apply for this course, visit or contact the training provider directly.
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