World Business StrategiesServing the Global Financial Community since 2000

Course Syllabus at a glance

Artificial Intelligence in Finance – Dr. Miquel Noguer
Big Data in Finance Modeling I – Dr. Miquel Noguer

a. Supervised learning
b. Unsupervised
c. NLP and RL

Quantitative Finance – Petter Kolm 
RL in Finance – William Kelly
Python and coding – Primer – Nicole Koenigstein
a. Python basics
b. Supervised Learning Algorithms

Supervised Learning – Dr. Noguer / Vanegas 
a. Supervised Learning Framework
b. NN, SVM, CART, XgBoost

Machine Learning and Market Microstructure – Sasha Stoikov 
Unsupervised Learning – Stefan Jansen 
a. Unsupervised Learning Rationale
b. Clustering
c. Auto-Encoders
d. Dimension reduction: PCA

Python and coding – Machine Learning – Nicole Koenigstein 
a. Python Sci kit Learn

Generative Models – David Pacheco 
RL Basics – David Pacheco 
Ml In Finance – Dhagash Mehta 
NLP Basics – Asier Gutierrez 
ML and Factor Models – Vincent Zoonekynd 
Python and coding – Machine Learning – Nicole Königstein

Deep Learning Applications – Stefan Jansen 
a. DL computational aspects
b. Factor Models

RL in Finance – Gordon Ritter 

Deep Learning –Dr. Matthew Dixon 
b. Neural Networks Architectures
II. Recurrent Neural Networks
III. Long Short Term Memory Networks
IV. Convolutional Neural Networks
V. Generative Adversarial Networks

Reinforcement Learning – Dr. Matthew Dixon 
a. Reinforcement Learning in Finance
b. RL in Dynamic Rep and Hedging
c. Markov Decision processes
d. Taxonomy of RL
e. Tabular Learning and Bellman Equation
f. Deep Q-Networks

Machine Learning in Finance – Nicholas Westray 

Reinforcement Learning II – Amine Aboussalah 
a. Reinforcement Learning Definitions
b. Trading Example

Mathworks – Marshall Alphonso 

Natural Language Processing – Dr. Miquel Noguer 
a. NLP Pipeline
b. Text Pre-Processing
c. Word Tokenization
d. Deep Learning NLP

NLP Deep Learning – Tinghao Li 
a. Transformers

NLP applied to ESG and SDG – Richard Rothenberg 

RL in Finance – Igor halperin