Data science without a Ph.D. Using IBM SPSS Modeler V18.1.1 (0A018G) Training

Live Online & Classroom Enterprise Certification Training

This course focuses on reviewing concepts of data science, where participants will learn the stages of a data science project.

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What is Data science without a Ph.D. Using IBM SPSS Modeler V18.1.1 (0A018G) Certification Training about?

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.

What are the objectives of Data science without a Ph.D. Using IBM SPSS Modeler V18.1.1 (0A018G) Certification Training ?

Please refer to course overview

Who is Data science without a Ph.D. Using IBM SPSS Modeler V18.1.1 (0A018G) Certification Training for?

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

What are the prerequisites for Data science without a Ph.D. Using IBM SPSS Modeler V18.1.1 (0A018G) Certification Training?

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

Available Training Modes

Live Online Training

6 Hours

Classroom Training

1 Days

Course Outline Expand All

Expand All

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 model

2: Setting measurement levels

Explain the concept of field measurement level

Explain the consequences of incorrect measurement levels

Modify a fields measurement level

3: Exploring the data

Audit the data

Check for invalid values

Take action for invalid values

Impute missing values

Replace outliers and extremes

4: Using automated data preparation

Automatically exclude low quality fields

Automatically replace missing values

Automatically replace outliers and extremes

5: Partitioning the data

Explain the rationale for partitioning the data

Partition the data into a training set and testing set

6: Selecting predictors

Automatically select important predictors (features) to predict a target

Explain the limitations of automatically selecting features

7: Using automated modeling

Find the best model for categorical targets

Find the best model for continuous targets

Explain what an ensemble model is

8: Evaluating models

Evaluate models for categorical targets

Evaluate models for continuous targets

9: Deploying models

List two ways to deploy models

Export scored data

Who is the instructor for this training?

The Trainer is IBM certified Instructor with extensive domain experience, including years of experience training & mentoring professionals in the industry.

Data science without a Ph.D. Using IBM SPSS Modeler V18.1.1 (0A018G) Certification Training - Certification & Exam

SpringPeople is the Authorized Training Partner of IBM through Tech Data
For any queries, feel free to reach us at ibm@springpeople.com

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