Arrow Electronics, Inc.

Data science without a Ph.D. Using IBM SPSS Modeler (v18.1.1)

CODE: ZL1_0A018

DURÉE: 1 Jours

PRIX H.T.: €1 490,00

Description

This course focuses on reviewing concepts of data science, where participants will learn the stages of a data science project. Topics include using automated tools to prepare data for analysis, build models, evaluate models, and deploy models. To learn about these data science concepts and topics, participants will use IBM SPSS Modeler as a tool.

Objectifs

  • Introduction to data science and IBM SPSS Modeler
  • Setting measurement levels
  • Exploring the data
  • Using automated data preparation
  • Partitioning the data
  • Selecting predictors
  • Using automated modeling
  • Evaluating models
  • Deploying models

Audience

• Business Analysts • Data Scientists • Participants who want to get started with data science

Prérequis

• It is recommended that you have an understanding of your business data

Programme

1:  Introduction to data science and IBM SPSS Modeler    •  Explain the stages in a data-science project, using the CRISP-DM methodology    •  Create IBM SPSS Modeler streams    •  Build and apply a machine learning model2:  Setting measurement levels    •  Explain the concept of "field measurement level"    •  Explain the consequences of incorrect measurement levels    •  Modify a field's measurement level3:  Exploring the data    •  Audit the data    •  Check for invalid values    •  Take action for invalid values    •  Impute missing values    •  Replace outliers and extremes4:  Using automated data preparation    •  Automatically exclude low quality fields    •  Automatically replace missing values    •  Automatically replace outliers and extremes5:  Partitioning the data    •  Explain the rationale for partitioning the data    •  Partition the data into a training set and testing set6:  Selecting predictors    •  Automatically select important predictors (features) to predict a target    •  Explain the limitations of automatically selecting features7:  Using automated modeling    •  Find the best model for categorical targets    •  Find the best model for continuous targets    •  Explain what an ensemble model is8:  Evaluating models    •  Evaluate models for categorical targets    •  Evaluate models for continuous targets9:  Deploying models    •  List two ways to deploy models    •  Export scored data

Informations supplémentaires

Prior to enrolling, IBM Employees must follow their Division/Department processes to obtain approval to attend this public training class. Failure to follow Division/Department approval processes may result in the IBM Employee being personally responsible for the class charges.

GBS practitioners that use the EViTA system for requesting external training should use that same process for this course. Go to the EViTA site to start this process:

http://w3.ibm.com/services/gbs/evita/BCSVTEnrl.nsf

Once you enroll in a GTP class, you will receive a confirmation letter that should show:

  • The current GTP list price
  • The 20% discounted price available to IBMers. This is the price you will be invoiced for the class.

Dates de session

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