A highly interactive training course on

Data Mining and Big Data Analytics Using SPSS

Data Mining and Big Data Analytics Using SPSS
5
Days

Course Schedules

 Dubai
 04-08 Dec 2023
 $5,950
 Dubai
 26 Feb-01 Mar 2024
 $5,950
 London
 22-26 Apr 2024
 $5,950
 Dubai
 24-28 Jun 2024
 $5,950
 London
 08-12 Jul 2024
 $5,950
 Dubai
 14-18 Oct 2024
 $5,950
 London
 09-13 Dec 2024
 $5,950

Training course overview

The amount of data collected in recent years has risen exponentially, and this has created the collection of datasets on customer interactions, sales, logistics, and production processes. Large retailer companies handle up to ten million transactions and five thousand items per second. This also enabled companies to introduce analysis of this data and achieve reduction in their lead times, reduce overheads, optimize workflows and increase customer satisfaction, while at the same time increasing their profits. There are many software packages for Big Data mining and Big Data Analytics, however many of these tools are mainly programming languages, and although free, they require a knowledge of computer programming.

As the data rises, the number of people who can perform the Data Mining and Big Data analytics should also rise, to handle the tide, and by using one of easiest to handle, big data analytics software is SPSS.

This training course will feature:

  • Use of SPSS software packages
  • Data mining and visualization with SPSS
  • Data analytics of Big Data with the use of SPSS packages
  • Advanced uses of SPSS and its interoperability with other software
  • Using the Big Data analytics for the benefits of the companies

What are the goals?

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

  • Understand the power of Big Data and Big Data Analytics
  • Harness the benefits of graphical interface of SPSS for Big Data Analytics
  • Learn the concepts of data analysis and visualization
  • Apply the drag and drop functionality for data visualization
  • Acquire the knowledge of advanced analysis of big data, like sentiment analysis in SPSS

Who is this training course for?

This training course is designed for all people involved in data mining and data analysis, as well as planning and forecasting, and especially the ones who are inclined to the use of graphical software interface, and their busy schedules are not allowing them to learn or apply programming languages like JAVA, R or Python.  This course is for those who do want to harness the power of Big Data but are not programmers themselves.

This training course is suitable to a wide range of professionals but will greatly benefit:

  • CTOs, CIOs and Engineers
  • Data Scientists, Data Analysts
  • Statisticians and technology personnel
  • Marketing and research specialists

How will this training course be presented?

This training course will utilise a variety of proven adult learning techniques to ensure maximum understanding, comprehension and retention of the information presented. This includes theoretical presentation of the concepts, but the emphasis will be on the exercises performed by the delegates with the guidance of the instructor. The delegates will be “learning by doing” as the training course is designed for them to use the software on the real problems and real data applying each of the techniques themselves. Delivery will be by presentation, group syndicate investigations, training e-manual and interactive seminars, as well as group discussion on the results of the exercises.

Course Outline

Day One: Introduction to SPSS
  • Getting to know SPSS
  • Starting SPSS and Working with data files
  • Descriptive Statistics
  • Frequencies (categorical variables)
  • Central tendency, standard deviations, and range (continuous variables)
  • Getting help and running tutorials
Day Two: Manipulating the Data and Initial Data Visualization
  • Using graphs to describe and explore the data
    • Histograms
    • Bar graphs
    • Boxplots
    • Line graphs
  • Calculating total scale scores
  • Transforming variables
    • Recode procedure
    • Compute procedure
    • Select cases procedure
    • Split file procedure
  • Reliability analysis using coefficient alpha (also known as Cronbach’s alpha)
Day Three: Inferential Statistics
  • T-test, one sample t-test, independent and dependent sample t-test
  • Analysis of variance (ANOVA)
  • Correlation and Pearson r correlation coefficient
  • Linear regression-simple and multiple linear regression
  • The chi-square goodness of fit and test of independence procedures
  • Autocorrelation and time series analysis
Day Four: Advanced Statistics with SPSS Modeller
  • SPSS Modeler and its main elements
  • Clustering analysis, using k-means
  • Association rules and apriori algorithm
  • Logistics regression
  • Forecasting using the Autoregressive Integrated Moving Average (ARIMA) model
  • Building a decision tree model
  • Sensitivity analysis of texts in SPSS
Day Five: The Integration of SPSS with Python and R
  • Big Data Analytics programs
  • Brief introduction to R
  • SPSS Modeler-R integration
  • Introduction to Python
  • SPSS Modeler Python Integration
  • Putting it all together

The certificate

*Coventry Academy Certificate of Attendance will be provided to delegates who attend and complete the course

Coventry Academy
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