Advanced Data Science for Finance Professional Certificate

This Professional Certificate is a sequel to the Data Science Professional Certificate. Advanced Data Science tools are developed to help you solve complex analytical problems in Finance. You will also be introduced to the latest big data technologies.

Prerequisite knowledge:

• Basic probability and statistics
• Some familiarity with financial securities and derivatives
• Python or R Development
• Basic Data Science toolkit: Dataframes, Linear Regression and Classifiers, PCA

CURRICULUM

Day 1

MODULE 1: THE DATA SCIENTIST WORKFLOW

• Data Collection and Cleaning
• Feature Engineering
• Model Selection
• Model Validation
• Overview of Machine Learning tools
• Statistics vs. Machine Learning

MODULE 2 - WORKSHOP: BAYESIAN VS. DECISION TREE

MODULE 3: ELEMENTS OF STATISTICAL LEARNING

• Bias vs Variance error,
• Regularization and Overfitting
• Ensemble Methods

MODULE 4 - WORKSHOP: BUILDING A RECOMMENDER SYSTEM

Day 2

MODULE 1: FACTOR ANALYSIS

• Principal Component Analysis
• Independent Component Analysis

MODULE 2: WORKSHOP: ISOLATING MARKET COMPONENT FROM SINGLE STOCK SIGNAL

MODULE 3: CLUSTERING

• K-Means
• Aggregative Clustering
• Semi-supervised learning
• Introduction to Deep Learning : Learning Hierarchical Structures

MODULE 4 - WORKSHOP: CLIENT SEGMENTATION

Day 3

MODULE 1: NLP TOOLKIT

• Text pre-processing
• Bag of word Model
• Word Embedding - Word2Vec

MODULE 2 - WORKSHOP: BUILDING A SENTIMENT ANALYSIS TOOL WITH NLTK

MODULE 3: DEEP LEARNING

• History and Applications
• Convolutional Neural Network
• Recurring Neural Networks
• Amazon Cloud and GPU setup for Tensorflow

MODULE 4 - WORKSHOP: BUILDING A CLASSIFIER WITH TENSORFLOW

Day 4

MODULE 1: BIG DATA TECHNOLOGIES

• Current Technologies Landscape
• Data Ingestion
• Data Processing - Batch
• Data Processing - Streaming
• NoSQL Databases

MODULE 2 - WORKSHOP: DISTRIBUTED COMPUTING WITH APACHE SPARK

MODULE 3 - WORKSHOP: NOSQL DATABASE

MODULE 4 - WORKSHOP: REAL TIME STREAMING WITH APACHE KAFKA

Day 5

MODULE 1: RESEARCH PROCESS

• Features Design and Selection
• Unsupervised features
• Designing a meta-predictor

MODULE 2 - WORKSHOP: BUILDING AN END-TO END PREDICTIVE MODEL

MODULE 3: PREDICTIVE ANALYSIS IN FINANCIAL SERVICES

• Alpha design
• Model Validation with noisy output
• Vizualization

MODULE 4 - WORKSHOP : VALIDATING A PREDICTIVE MODEL FOR STOCK MARKETS

WHAT YOU'LL LEARN

• Understand the Data Scientist approach and research process
• Combine Machine Learning building blocks into powerful algorithms
• Master Natural Langage Processing techniques, including Deep Neural Networks
• Get familiar with the latest disruptive big data technologies