Skip to content
View menu
MIUC
Log in
Spring semester - BA - IR - Year 4 Calendar view

Artificial Intelligence and Predictive Modelling


Class
Eugenio Clavijo
Enrolment for this class is currently closed.

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: 16 on Wednesday

Google meet class: https://meet.jit.si/ArtificialIntelligenceandPredictiveModelling 

Live tutorial session for online students: Wednesday 16:00
Link on google meet upon request.

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:

MSG_template_2021-22_BA_MIUC_AI-PMB_YR4_(L6)_S2_(IBM).pdf

Here is the class outline:

Join the class online

1 section
Join the class online

Week 1 Introduction

4 sections
Week description
svm decision tree
Examples
Simple risk assessment

Week 2 - Artificial intelligence: types of algorithms

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

Week 3 - Evaluation strategies for machine learning models

3 sections
Week description
Movies revenue prediction
online platforms

Week 4 - Linear models

5 sections
Week description
Bitcoin
bitcoin2014
Bitcoin_2013_2014_train_2015_test
Bitcon Excel Analysis

Week 5 - Regularization

5 sections
Week description
Car accidents
BTC using API
currency identification
crime

Week 6 - k-Nearest Neighbours

4 sections
Week description
Price uplift prediction
Random forest
Hierarchical clustering

Week 7 - Random Forest

6 sections
Week description
Forecasting
Correlation comparison
weather forecast
disease
datathon

Week 8 - Support Vector Machines

3 sections
Week description
Insurance price analysys
booking prices

Week 9 - K-Means algorithm

6 sections
Week description
real estate analysis
Support Vector Machine
SVM vs. Random Forest
cross validation
elbow

Week 10 - Non-negative matrix factorization

2 sections
Week description
Social network sentimental analysis

Week 11 - Evolutionary Algorithms: representation and heuristic optimization

3 sections
Week description
Classification using Naive Bayes
Predictive models comparision

Week 12 - A* search strategy

4 sections
Week description
Sales channel prediction
Pricing discount analysis
reinforcement

Week 13-14 - Project submission and Recapitulation, Remarks, Doubts

2 sections
Week description
Stocks