Free SOA Exam PA (Predictive Analytics) Lessons
All 22 SOA Exam PA (Predictive Analytics) lessons are free to read, each with worked examples and audio narration. Just a free account, no card.
Predictive Analytics Problem Definition
- Assess whether descriptive, predictive, and prescriptive analytics applies to a business problem. (8 min)
- Describe the characteristics of predictive modeling problems. (7 min)
- Explain the concepts of bias, variance, model complexity, and the bias-variance trade-off. (8 min)
- Translate a vague question into one that can be analyzed with statistics and predictive analytics to solve a business problem. (8 min)
- Consider factors such as available data and technology, significance of business impact, and implementation challenges to define the problem. (9 min)
- Assess what additional information or next steps would improve the ability to apply predictive analytics to a business problem. (8 min)
Data Exploration and Visualization
- Identify structured and unstructured data types. (11 min)
- Identify the types of variables and terminology used in predictive modeling. (11 min)
- Evaluate effective data design with respect to time frame, sampling, and granularity. (12 min)
- Apply the key principles of constructing graphs. (10 min)
- Apply univariate data exploration techniques. (11 min)
- Apply bivariate data exploration techniques. (12 min)
Data Transformations and Unsupervised Learning Techniques
- Create features from existing data that may add value. (13 min)
- Apply principal components analysis to transform data. (12 min)
- Apply K-means and hierarchical clustering to transform data. (12 min)
Generalized Linear Models
- Select and validate a GLM as appropriate for a business problem. (15 min)
- Apply offsets and weights as appropriate. (16 min)
- Interpret model coefficients, including interaction terms. (14 min)
- Select appropriate hyperparameters for regularized regression. (15 min)