Workshop practical data analysis

Direct data-based decisions


Analyze any data set to exploit them to design better software products.

In just 3 intensive days, you will learn the tools, techniques and fundamental concepts of data science.During the program you will work several data problem obtaining experience and resources to design a data product.

The data scientist is one who has all analytical skills to be able to transform data into an intelligent product that generates value.

· Who is going:

This training is widely recommended for:

  • Companies that wish to develop analyzing your data
  • Developers who want to add an important skill in their career
  • Python developers who want to do more with language

· Pre-requirements:


  • Solid programming bases
  • Essential knowledge of mathematics
  • Know the development in Python
  • Knowledge in Statistics

· Content of the training:

  • Introduction to data analysis
    • Introduction to data analysis
    • First steps with Jupyter and pandas
    • Manipulating numerical and categorical data with pandas
    • Principles of exploratory analysis
    • Introduction to data visualization
    • Applications of statistical data analysis
    • Cohort study model
    • Case study: Analyzing the behavior of my clients with cohorts
  • Analysis of time series
    • Introduction to time series analysis
    • Basic Concepts of Time Series Correlation
    • Durbin-watson test
    • Time series prediction models
    • Model Holt-Winters Weighted Moving Average
    • Model Arma.
    • Arima model
    • Case study: predicting the inventory
    • Logistic regression model
    • Model of linear discriminant analysis
    • Case study: predicting time series with data from Yahoo Finance
  • Classification and data grouping
    • Introduction to the data classification
    • Model of analysis of main components
    • Trees model
    • Model of vector support machines
    • Case Study: Credit Record Rating
    • Introduction to the data pool
    • Understanding the concept of distance
    • Kmeans model
    • Case study: Segmenting my clients