CDOSS Certificate

Data Science Fundamentals

Profiles that can prepare this certification contents:

Financiers, Banqueters, Marketers, Managers, Administrative and financial directors, Data engineer, Data Scientist, 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 Science, Data Mining and 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, e-health etc.

Detailed plan of preparation:

1) Data Science Vs Data mining Vs Machine Learning Vs Big Data

2) Data pre-processing (Indexation, Onhotencoder, missing values…)

3) Unsupervised learning

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

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

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

4) Supervised learning (classification and regression)

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

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

– Performance evaluation of regression models (MSE, RMSE,R2)

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

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

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

5) Big Data Context

– Hadoop Ecosystem

– Apache Spark (ETL/ML)