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Spring semester - BA - IR - Year 4 Calendar view

Artificial Intelligence and Predictive Modelling (20-21)


Class
Eugenio Clavijo
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Short description: The course introduces the study of Artificial Intelligence (AI) for students in all course streams. It is designed to stand alone as an introduction to AI, but also to provide a background for more advanced study.

Artificial Intelligence Description

Level 6 (Year 4)

Credits: 10

Module leader: Eugenio Clavijo

Office hour: 10 am Monday

Google meet class: http://meet.google.com/qqi-gksg-nqz

Assessment methods

Learning Outcome

At the end of the module you will be able to:
LO1. Discuss main supervised and unsupervised learning algorithms. (Assessment 1)
LO2. Review further artificial intelligence learning algorithms (Assessment 1)
LO3. Build predictive models of different nature (parametric and non-parametric). (Assessment 1)

 

For more detail, please see the attached MSG:

YR4_(L6)_S2_(IBM)_AI-PMB_MSG_2020.pdf

Here is the class outline:

Week 1

Introduction to Artificial Intelligence and Machine Learning.

3 sections
Week description
Simple risk assessment
Examples

Week 2 - Artificial intelligence: types of algorithms

21 sections
Week description
Predictive modeling
e-Commerce comments analysis
datasets
practice
extra zika
exercise
new tree
Build tree
Last exercise
guideline for your first dashboard
a tree
spotify prediction
products with clasification tree
homework
Play tennis
tennis csv
50 euros award
reality
next class
Class Exercise