What you'll get
- 13+ Hours
- 1 Courses
- Course Completion Certificates
- Self-paced Courses
- Technical Support
- Case Studies
Synopsis
- The course is designed to develop and strengthen predictive modeling expertise applicable across various business domains.
- It emphasizes the use of quantitative methods and predictive modeling techniques to gain deep insights into customer behavior.
- Both theoretical concepts and real-world datasets are employed to facilitate hands-on predictive analysis.
- Throughout the training, observations, interpretations, predictions, and conclusions are illustrated and explained using practical examples, ensuring learners grasp concepts as they progress.
Content
| Courses | No. of Hours | Certificates | Details |
|---|---|---|---|
| Predictive Modeling using SPSS | 13h 17m | ✔ | View Curriculum |
Description
This course provides a comprehensive introduction to predictive analytics and modeling, equipping learners with the skills to analyze patterns and forecast outcomes across various domains. It emphasizes the practical application of quantitative methods to understand customer behavior, financial trends, and results in medical or pharmaceutical research. Participants work with both theoretical and real-world datasets, applying SPSS software to perform predictive analysis.
Throughout the course, key concepts such as observations, interpretations, predictions, and conclusions are demonstrated in real time through examples, ensuring learners gain hands-on experience. Advanced regression techniques, including quadratic and polynomial regressions, are also covered, offering insights often not included in other online courses. The program further deepens understanding of descriptive statistics, including means, standard deviation, skewness, kurtosis, and t-tests, with practical implementation using SPSS.
Requirements
- Basic knowledge of quantitative methods and data analysis.
- Familiarity with MS Office and tools like Paint for practical exercises.
Target Audience
- Students and early-career professionals seeking hands-on predictive analytics experience.
- Quantitative analysts, CFAs, equity researchers, and pharma or research scientists.
