Artificial Intelligence In Aviation Industry (Module From Master Of Science In Aviation Engineering) - The Hong Kong Polytechnic University
課程名稱: |
Artificial Intelligence In Aviation Industry (Module From Master Of Science In Aviation Engineering) - The Hong Kong Polytechnic University |
|---|---|
院校名稱: |
香港理工大學 |
課程編號: |
36Z141274 |
範疇: |
工程及科技 |
上課模式: |
39 hours (FT/PT) |
為期: |
13 weeks |
學費: |
14,100.00 |
入學要求: |
(1) A Bachelor’S Degree With Honours In An Engineering, Science, Or Technology Related Subject Or Qualifications That Satisfy The Academic Requirements For Corporate Membership Of The Hong Kong Institution Of Engineers (Hkie), Or The Equivalent. (2) Applicants Who Are Not Native Speakers Of English Holding A Bachelor'S Degree Awarded By Institutions Where The Medium Of Instruction Is Not English Should Fulfil The Following University Minimum English Language Requirement: (A) A Test Of English As A Foreign Language (Toefl) Score Of 80 For The Internet Based Test Or 550 For The Paper-Based Test; Or (B) An Overall Band Score Of At Least 6 In The International English Language Testing System (Ielts). |
課程大綱: |
(1) Fundamental Of Machine Learning, Data Mining, Data Analytics And Artificial Intelligence (9 Hours): Basic Soft Computing Methods, Data Mining And Artificial Intelligence Algorithms In Airline And Airport Applications; Ai And Machine Learning Algorithm Design; Data Analytics, Managerial Implications And Actionable Insights With Aviation Case Studies Analysis. (2) Supervised Learning (6 Hours): Least Squares And Nearest Neighbours; Statistical Decision Theory; Linear Methods For Regression; Linear Discriminant Analysis; Classifications; Logistic Regression; Separating Hyperplanes; Support-Vector Machine. (3) Unsupervised Learning (6 Hours): Clustering; Association Dimensionality Reduction; K-Means Clustering; Knn; Neural Network; Principle Component Analysis. (4) Model Inference And Averaging (6 Hours): Bootstrap And Maximum Likelihood Methods; Bayesian Method; Relationship Between The Bootstrap And Bayesian Inference. (5) Advancement In Artificial Intelligence (6 Hours): Semi-Supervised Learning Algorithmic Architecture; Generative Adversarial Network; Self-Trained Naïve Bayes Classifier; Reinforcement Learning; Q-Learning; Model-Based Value Estimation; Deep Learning. (6) Data-Driven Optimisation And Time-Series Modelling (6 Hours): Air Traffic Demand Forecasting; Flight Delay Prediction; Operations Management And Dynamic Pricing. |
資歷名冊登記號碼: |
22/000692/L6 |
資歷架構級別: |
6 |