CDOSS Certificate

Big data mining for financial institutions and marketers

Profiles that can prepare this certification contents:

Financiers, Banqueters, Marketers, Managers, Administrative and financial directors, Data engineer, statistical engineer, Developer engineer, Applied Mathematics engineer and more.

Global knowledge to be acquired to pass this certification:

+ Dominate the basics and foundations of data mining; from information theory to machine learning.

+ Dominate a variety of tools, perspectives and approaches to be able to identify the most appropriate methods and models to use to solve each specific case.

+ Ability to use different types of data in real time to make complex predictions and large-scale calculations.

+ Ability to apply all these techniques in marketing, finance etc.

Detailed plan of preparation:

1) Data mining Vs machine learning Vs Big Data

2) Unsupervised learning

– Hierarchical ascending classification (Scipy library (python)).

– K-means (Scikit-learn library (python)).

– Choice of the number of clusters (Scikit-learn library (python)).

3) Supervised learning

– Decision tree (Scikit-learn library (Python)).

– Performance evaluation of classification models (confusion matrix, accuracy, recall, precision, f1-measure)

– Random forest (Scikit-learn library (Python))

– Artificial neural networks (Scikit-learn library (Python))

– Deep learning (DFFNN, CNN, RNN) (Keras library (Python), Tensorflow library (Python)).

4) Big Data Machine Learning with Apache Spark (pyspark)

– RDD Vs DataFrame

– Spark ML library