Training options

Training options

Smart Vision has a worldwide training organization. The training organization offers training across most of SPSS software products and offers a variety of training options to meet our client’s needs.

Smart Vision offers a variety of training options that will provide more in-depth training on the product. You can choose the end-user options that best meet your needs, to quickly and easily realize the benefits of SPSS technologies.  We provide pricing information on the different types of training programs below:

All courses are available in SPSS training centres or alternatively can be provided as part of a private on-site training program.

Maximum Number of attendees         Up to 10 Persons

Our training staff is composed of experienced data miners and statisticians, many of whom have master’s or PhD degrees in advanced fields or have participated in the programming and construction of our software tools

Introductory SV Analytica Modeler Courses

Introduction to SV Analytica Modeler

Duration: 2 days

The two-day Introduction to Modeler course reviews the basic operations and environment of the SPSS Modeler data mining software. You will learn how to read, explore and manipulate data within Modeler. Within the context of data mining, you will be introduced to such machine learning techniques as rule induction, neural networks, Kohonen networks and association rules, and will apply them to business data.

Data Manipulation with SV Analytica Modeler

Duration: 2 days

The two-day course, designed for current users of Modeler, reviews a number of data manipulation techniques available within Modeler. Attendees will see how to combine and manipulate files, sample data, handle missing values, and work with dates and sequence data.

Predictive Modeling with SV Analytica Modeler

Duration: 1 day

This course demonstrates how to develop models to predict categorical and continuous outcomes, using such techniques as neural networks, decision trees, logistic regression, support vector machines, and Bayesian network models. Use of the binary classifier and numeric predictor nodes to automate model selection is included. Feature selection and detection of outliers are discussed. Expert options for each modeling node are reviewed in detail and advice is provided on when and how to use each model. You will also learn how to combine two or more models to improve prediction.

Advanced SV Analytica Modeler Courses

Automated Data Mining with SV Analytica Modeler

Duration: 2 days

This class will show you how to use SV Analytica Modeler to automate the building of predictive models. The course will show you how to build predictive models for customer behavior and build customer segmentation using various cluster models. You will learn how to read data from various sources and automatically prepare data for modeling using a variety of methods. Scoring new data using the model will also be discussed.

Clustering and Association Models with SV Analytica Modeler

Duration: 1 day

This course demonstrates how to segment or cluster data with all the clustering techniques available in SV Analytica Modeler. The course also provides examples of creating association models to find rules describing the relationships among a set of items, and of creating sequence models to find rules describing the relationships over time among a set of items.

Classifying Customers using SV Analytica Modeler

Duration: 1 day

Classifying Customers Using SV Analytica Modeler is a one day, instructor-led classroom, intermediate level course that provides an overview of how to use Modeler to predict the category to which a customer belongs based on selected data. Some examples include: whether a customer switches to another provider or brand, whether a customer responds to a particular advertising campaign, or how well a student will perform in a specific academic setting.

Predicting Continuous Targets using SV Analytica Modeler

Duration: 1 day

Predicting Continuous Targets Using SV Analytica Modeler is a one-day intermediate level course that provides an overview of how to use Modeler to predict a target field that describes numeric values. Some examples include: predicting the length of subscription (for newspapers, telecommunication), predicting claim amount (insurance), predicting donation amount (charity), and predicting revenues (sales).

Introductory & Intermediate SPSS Statistics Courses

Introduction to Statistics & SPSS Statistics

Duration: 2 days

This course targets those with little statistical background and an appropriate refresher for those whose main statistical experience was gained many years ago. It examines data using exploratory data interrogation techniques allowing the analyst to produce reliable results to draw informed conclusions.

The audience should have a PC literate and have a Keyboard and mouse skills. Experience of working in the Windows environment and a general understanding of key Windows features. No prior knowledge of Statistics is required.

The course covers basic statistical analysis and introduces many of the most popular statistical tests. It covers reliability of data, and provides a solid grounding in statistical analysis. However for those who wish to progress into more advanced and powerful statistical procedures, this course provides you with the knowledge, ability and confidence required to attend higher-level statistical courses.

  • Introduction to statistics
  • Statistics Measurement Level
  • Sampling Techniques Normal Distribution
  • Measurement of Central tendency & dispersion
  • Shape of Distribution (Skewness & Kurtosis)
  • Principles of research design and Identify different types of data
  • Introduction to Research Methodology (CRISP methodology)
  • Open, enter, edit, define, and modify your data.
  • Choose the appropriate techniques for exploring, summarizing and testing the data, Exploratory Data Analysis: Interval Scale Data
  • Interpret your output and draw appropriate conclusions about the data.
  • Describing and Comparing Groups of Categorical Data.
  • Define appropriate Variable Properties
  • Define and handling Missing Values
  • Reading Data from Different Data Sources (Database, Excel, ASCII, …)

Data Management & Manipulation

Duration: 3 days

This course is a natural follow-on to the 'Introduction to SPSS' and 'Introduction to SPSS & Statistics 'courses and is designed for anyone wishing to become more competent with the full range of file and data manipulation options, and generally increase their efficiency with SPSS.

You must be PC literate, have a sound working knowledge of SPSS and be familiar with the topics covered on the Introduction to SPSS course. You must also be familiar with variable definition, use of the data dictionary, setting up dates, generating basic exploratory statistics, using the compute and recode procedures and editing and saving output. These techniques must have been used in SPSS v.23 or above.

The course provides detailed training in the use of a wide range of file and data management techniques. The knowledge and competence gained will enable you to suitably manage your data files to achieve the desired data structures. Advice on optimizing efficiency in everyday operations is provided and you will gain an understanding of the various options available when operating SPSS. Through an understanding of the command syntax, you will be able to efficiently manage and modify your data.

By the end of this course, you will be able to:

  • Manage and manipulate numeric data, including multiple response data.
  • Manage and manipulate dates and non-numeric data.
  • Manipulate files so as to achieve the desired data structure.
  • Merging, and Appending data files
  • Prepare Data for Analysis
  • Check the Data correctness and know how to handle Missing values
  • Data Transformations
  • Recoding & Binning Data
  • Deriving and Computing variables
  • Summarizing & graphing data using chart builder
  • Creating tables using custom tables
  • Basic Statistical Analysis
  • Automating the procedures using SPSS Syntax file

Advanced SPSS Statistics Courses

Advanced Statistical Techniques

Duration: 5 days

This course will consider in depth some of the more advanced statistical procedures that are available in SPSS. You'll take a look at several advanced statistical techniques and discuss situations when each may be used, the assumptions made by each method, how to set up the analysis using SPSS and how to interpret the results.

You must be PC literate, have a good working knowledge of SPSS, and be familiar with the topics covered on the Introduction, and Data Management and Manipulation of SPSS course. You must also be familiar with basic Statistics

The course provides detailed training in the use of a wide range of following an introduction to essential terminology; you will proceed logically through the following topics as per the predefined trainees need

  • In depth introduction to Sampling techniques
  • Advanced techniques to Research Methodology
  • Introduction to Inferential statistics.
  • In depth assessment to Regression Modeling.
  • Simple Linear, Multivariate, Logistic, & Ordinal Regression
  • Assess the goodness of fits of the models.
  • Correlation Coefficients and Significance
  • One-way ANOVA
  • Two-way analysis, comparing more than two groups ANOVA.
  • Independent Sample T-Test

SV Analytica Modeler Data Collection Course

Duration: 4 days

Designing and publishing Questionnaire

The course introduces the entire survey life cycle and assists in demonstrating how to build and design questionnaires and surveys.

And guides you in detail in how to deal with multiple types of questions (Single response, Multiple responses, Grids, Open ended ones, etc.). Then how to control and administer the entire project and getting into the details of deploying the different questionnaires through the different channels (ex. Web, Telephone, and email).

This course provides a solid knowledge on how to differentiate between various deployment channels and how to deal with the collected data in terms of exporting the data into different sources and creating reports and tabulation.

Also, it provides in-depth knowledge of monitoring the agents and uploading the list of respondents for all the different channels.

By the end of the course you will have learned to:

  • Building and Designing Questionnaires.
  • Managing different types of questions
  • Launching the questionnaires
  • Choose the appropriate publishing techniques
  • Dealing with Web Interviews
  • Dealing with CATI Interviews
  • Exploring the results and collected data
  • Creating reports and charts

SV Analytica Collaboration & Deployment Services Courses

Duration: 2 days

Introduction to Collaboration & Deployment Services

This 2-day course is designed for current analyst users of Modeler, and IT users in order to be able to deploy the anti-corruption and other fraud detection models built with the Modeler into the CADS.

So that it can be shared among the whole enterprise. business data. 

SV Analytica Decision Management Courses

Introduction to Analytical Decision Management

Duration: 2 days

These 2-days course, designed for business users and decision makers in order to be able to apply the what-if scenarios and simulate the results in real-time. It will help them in applying the business rules easily and interactively.