Description
Advanced Data Science Techniques in SPSS course. Within days you can master some of the most complex data analysis techniques available in SPSS software. Even if you are not a professional mathematician or statistician, you will understand these techniques well and be able to apply them in practical and real situations. Let’s see what you will learn:
- Stepwise regression
- Non-linear regression
- K nearest neighbor
- Decision trees
- Neural networks
- Two-stage cluster analysis
- Survival analysis
What you will learn in this course
- Perform advanced linear regression using predictive selection techniques
- Perform any type of non-linear regression analysis
- Prediction using the k nearest neighbor (KNN) technique.
- Using binary trees (CART) for prediction (both regression and classification trees)
- Using non-binary (CHAID) trees for prediction (both regression and classification trees)
- Construction and training of a multilayer perceptron (MLP)
- Construction and training of a radial basis neural network (RBF)
- Perform two-way clustering analysis
- Carrying out survival analysis using the Kaplan-Meier method
- Performing survival analysis using Cox regression
- Validation of prediction techniques (KNN, trees, neural networks) using validation set and cross-validation approach
- Save a predictive analytics model and use it to predict future new data
This course is suitable for people who
- Students
- Doctoral students
- Academic researchers
- Business researchers
- University professors
- Anyone interested in data analytics and data science
Advanced Data Science Techniques in SPSS course specifications
- Publisher: Udemy
- Lecturer: Bogdan Anastasiei
- Training level: beginner to advanced
- Training duration: 6 hours and 41 minutes
- Number of courses: 87
Course headings
Advanced Data Science Techniques in SPSS course prerequisites
- SPSS program installed (version 21+)
- Basic SPSS knowledge
- Basic or intermediate statistics knowledge
Course images
Sample video of the course
Installation guide
After Extract, view with your favorite Player.
Subtitle: English
Quality: 720p
download link
File(s) password: www.downloadly.ir
File size
831 MB