World Business StrategiesServing the Global Financial Community since 2000
Module Contents Date Hour Professor
1 Artificial Intelligence in Finance Landscape Tuesday, 5 March, 2019 06.00 – 09.00 pm Dr Miquel Noguer i Alonso
2 Alternative data Thursday, 7 March, 2019 06.00 – 09.00 pm Dr Petter Kolm
3 Econometrics and financial modeling review Tuesday, 12 March, 2019 06.00 – 09.00 pm Dr Petter Kolm
a. Univariate and Multivariate modeling Thursday, 14 March, 2019 06.00 – 09.00 pm Dr Petter Kolm
b. Continuous and Discrete models
c. Time Series Models
d. Linear Factor Models
e. Portfolio Allocation
f. Exercises
4 Python and coding –  Primer Tuesday, 19 March, 2019 06.00 – 09.00 pm Dr.Gilberto Batres Estrada
a. Python basics Thursday, 21 March, 2019 06.00 – 09.00 pm Dr.Gilberto Batres Estrada
b. Sci-kit Learn
c. XgBoost
d. Keras and Tensorflow
e. NLTK
f. Exercises
5 DataRobot Tuesday, 26 March, 2019 06.00 – 09.00 pm Dr John Boersma
6 Machine Learning Modeling and Metrics Thursday, 28 March, 2019 06.00 – 09.00 pm Dr Georges Lentzas
a. Preprocessing Tuesday, 2 April, 2019 06.00 – 09.00 pm Dr Georges Lentzas
        i. Features scaling and selection
        ii. Dimensionality Reduction
        iii. Sampling
b. Learning
        i. Model Selection
        ii. Cross-Validation
        iii. Performance Metrics
        iv. Hyperparameter optimization
c. Evaluation
d. Prediction
e. Exercises and Code
Module Contents Date Hour Professor
7 Supervised Learning
a. Classification Thursday, 4 April, 2019 06.00 – 09.00 pm Dr Georges Lentzas
     i. Logistic and Softmax Regression Tuesday, 9 April, 2019 06.00 – 09.00 pm Dr Georges Lentzas
     ii. K-Nearest Neighbors
     iii. Classification and Regression Trees
     iv. Support Vector Machines
     vi. Exercises and Code
b. Ensemble models Thursday, 11 April, 2019 06.00 – 09.00 pm Dr Miquel Noguer i Alonso
     i. Bagging: Random Forests Tuesday, 16 April, 2019 06.00 – 09.00 pm Dr Miquel Noguer i Alonso
     ii. Boosting – Adaboost and XGBoost
     iii. Exercises and Code
c. Regression Thursday, 18 April, 2019 06.00 – 09.00 pm Dr Josh Joseph
     i. Linear Regression Tuesday, 23 April, 2019 06.00 – 09.00 pm Dr Josh Joseph
     ii. Penalized Linear Regression: Lasso and Ridge
     iii. Non-Linear Regressions
     iv. Deep Regressions
8 Unsupervised Learning Thursday, 25 April, 2019 06.00 – 09.00 pm Dr Mike Atwal
a. Principal Component Analysis Tuesday, 30 April, 2019 06.00 – 09.00 pm Dr Mike Atwal
b. Clustering
c. Exercises and Code
9 Deep Learning Thursday, 2 May, 2019 06.00 – 09.00 pm Dr Larry Rudolph
a. The mathematics of deep learning Tuesday, 7 May, 2019 06.00 – 09.00 pm Dr Larry Rudolph
     i. Mathematical definition
     ii. Optimization
     iii. Drop out
d. Feedforward Neural Networks
c. Recurrent Neural Networks
d. Long Short Term Memory Networks
e. Convolutional Neural Networks
f. Generative Adversarial Networks
g. Interpretability
h. Exercises and Code
Module Contents Date Hour Professor
10 Reinforcement Learning Thursday, 9 May, 2019 06.00 – 09.00 pm Dr Igor Halperin
a. Markov decision Processes Tuesday, 14 May, 2019 06.00 – 09.00 pm Dr Igor Halperin
b. Deep Reinforcement Learning
c. Inverse Reinforcement Learning
11 Artificial Intelligence
a. Natural Language Processing Thursday, 16 May, 2019 06.00 – 09.00 pm Dr Miquel Noguer i Alonso
     i. Theory Tuesday, 21 May, 2019 06.00 – 09.00 pm Dr Miquel Noguer i Alonso
     ii. Deep Learning for NLP
     iii. Applications
     iv. Exercises and Code
12 Practical Cases I Thursday, 23 May, 2019 06.00 – 09.00 pm All professors
a. AI and Investing Tuesday, 28 May, 2019 06.00 – 09.00 pm All professors
b. AI and Risk and Banking
13 Final Exam Tuesday, 4 June, 2019 06.00 – 09.00 pm Faculty
14 Artificial Intelligence in Finance Project Tuesday, 11 June, 2019