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.
CPE Credits: 35
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
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To make it even easier to learn, you can finance your program through Affirm.
Loans offered through Affirm are available in the U.S. and Canada.
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
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
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
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
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