Description
This short learning programme aims to equip participants with the foundational knowledge and practical skills to implement deep learning and neural network solutions using
TensorFlow 2.0, enabling them to design, build, and evaluate AI models that drive business growth and innovation across diverse real-world contexts.
Tentative Training Schedule
Note: Depending on the numbers of participants, training groups could be combined if participants numbers are too few.
| Day | Students (Fridays) |
| 1 | 6 March 2026 09:30 – 12:30 Topics: Intro to AI & Deep Learning; Neural Networks: Structure & Learning; MLPs and Perceptron |
| 2 | 13 March 2026 09:30 – 12:30 Topics: Convolutional Neural Networks (CNNs): Introduction, Architecture, Key Concepts |
| 3 | 20 March 2026 09:30 – 12:30 Topics: Recurrent Neural Networks (RNNs): Architecture, LSTM, GRU, Challenges |
| 4 | 27 March 2026 09:30 – 12:30 Topics: Natural Language Processing (NLP): Tokenization, Word Embeddings, Sentiment Analysis |
| 5 | 3 April 2026 09:30 – 12:30 Topics: Transfer Learning, Model Deployment, AI Ethics & Responsible AI |
