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Data skills

• Databases / Data warehouses
  • MySQL, PostgreSQL, DB Browser
• Data wrangling
  • ETL
    • SQL Server
  • Cleaning, imputation, outliers handling, transformation

    • R: tidyverse, dyplr, stringr, etc.

      Python: Numpy, Pandas, SciPy.

• Data Analysis
  • Exploration (univariate, bivariate and multivariate analysis)

    • R: FactoMiner, ade4, ggplot2, plotly, etc.

      Python: Matplotlib, Seaborn

  • Visualization / Reporting

    • Dashboards : Tableau, RShiny, Flexdashboard

      Rmarkdown, Jupyter Notebook.

  • Machine learning / Statistical modeling
    • Dimensionality Reduction : Factorial analysis (PCA, MFA, FAMD, etc.), NMDS, etc.
    • Regression: Linear models, Random Forest, SVM, Kriging, etc.
    • Classification: Logistic Regression, Decision trees, Random Forest, etc.
    • Clustering: HCPC, KNN, K-MEANS, CLARA, etc.

      • R: caret, randomforest, cluster, e1071, rpart, etc.

        Python: Scikit learn, TensorFlow.

• Big data
  • Cloud computing
    • Azure
  • High Performance Computing
    • HPC cluster : meso@LR
  • Parallel computing
    • R: Parallel, Multidyplr​.