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Artificial Intelligence and Predictive Modelling (2022-2023)
Class
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Eduardo Rivera
Lessons
Here is the class outline:
Join the class onlineYou can find here: 1- The Google Meet link to connect to class online. 2. A link to the folder with all the recordings of the sessions. 1 section
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Week 1 - Introduction to Artificial Intelligence and Machine LearningSession 1 - Introduction to the module Session 2 - Scratch and LearningML 3 sections
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Week 2 – Introduction to Data Cleaning and VisualizationSession 1 - Introduction to Knime and Data Visualization Session 2 - Data Cleaning 3 sections
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Week 3 – Classification and Decision TreesSession 1 - Classification and Decision Trees Session 2 - Practical Exercises 4 sections
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Weeks 4, 5 and 6 – Model Evaluation and Further Classification AlgorithmsSession 1 - Model Evaluation Session 2 - Model Comparison, Random Forest and Boosted Trees Session 3 - Practical Exercise Session 4 - K-Nearest Neighbors Session 5 - Classification Summary and Extra exercises 11 sections
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Weeks 6 and 7 – RegressionSession 1 - Introduction to Regression Problems and Linear Regression Session 2 - Disadvantages and Improvements of Linear Regression, and Evaluation of Regression Models 5 sections
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Week 7 – Natural Language ProcessingSession 1 - Natural Language Processing 2 sections
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Spring Holidays |
Week 8 – Neural NetworksSession 1 - Neural Networks and ChatGPT 2 sections
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Weeks 8 and 9 – Presentations: Applications of Machine LearningSessions 1 and 2 - Student's Presentation and Further Applications of Neural Networks 3 sections
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Weeks 9, 10 and 11 – ClusteringSession 1 - Introduction to Clustering Session 2 - Clustering - Limitations and Challenges Session 3 - Clustering - Practical Exercises and Dimensionality Reduction Session 4 - Bank holiday Session 5 - Clustering - Practical Exercises II 7 sections
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Dimensionality ReductionNote: Dimensionality Reduction was covered together with Clustering in the previous sessions, but the materials associated to it are included in this lesson. 2 sections
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Week 12 – Further Tools used in Machine LearningSession 1 - Programming and BigML Session 1 - Power BI 3 sections
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Week 13 - Recapitulation, Remarks, DoubtsSessions 1 and 2 2 sections
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Week 14 - Final ProjectSessions 1 and 2 1 section
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