What you'll get
- 17+ Hours
- 2 Courses
- Course Completion Certificates
- Self-paced Courses
- Technical Support
- Case Studies
Synopsis
- Provides training in data analysis, manipulation, visualization, statistics, and hypothesis testing.
- Teaches predictive analytics techniques for effectively interpreting model outputs.
- Guides learners on using predictive analytics tools to solve real-time business problems.
- Covers various predictive models, including regression, clustering, and other key techniques.
Content
| Courses | No. of Hours | Certificates | Details |
|---|---|---|---|
| Predictive Modeling using Minitab | 15h 32m | ✔ | View Curriculum |
| Minitab:01 - Application to Predictive Modeling (Descriptive Statistics) | 2h 43m | ✔ | View Curriculum |
Description
This course provides a comprehensive introduction to predictive analytics and modeling using Minitab, guiding participants through all the essential steps. Learners will gain practical skills to create statistical models that forecast future outcomes and support data-driven decision-making across business sectors.
Key topics covered include:
- Defining Objectives: Learn to align predictive models with business goals and objectives.
- Data Collection: Explore methods for gathering data from multiple sources, with practical examples for different data types.
- Data Preparation: Understand how to segregate and organize data to optimize its use in predictive modeling.
- Variable Selection & Transformation: Learn techniques to transform independent variables for the best fit with dependent variables.
- Model Processing & Evaluation: Explore methods for building, processing, and evaluating predictive models effectively.
- Model Validation: Apply powerful techniques to ensure model accuracy and performance.
- Implementation & Maintenance: Gain insight into deploying models successfully, auditing them, and maintaining performance over time.
By the end of this course, participants will develop the expertise to leverage predictive analytics and modeling to enhance business performance, make informed decisions, and anticipate future trends effectively.
Requirements
- Basic knowledge of statistics
- Familiarity with software such as SPSS, SAS, or STATA.
Target Audience
- Students interested in predictive analytics
- Researchers looking to apply predictive modeling in their work
