What you'll get
- 22+ Hours
- 6 Courses
- Course Completion Certificates
- Self-paced Courses
- Technical Support
- Case Studies
Synopsis
- Designed to build practical expertise in using Minitab for real-world time series analysis and forecasting.
- Provides one year of full access to self-paced, video-based learning.
- Suitable for individuals committed to developing skills in forecasting with Minitab.
- Assumes a foundational understanding of basic statistical concepts.
- Includes hands-on projects and completion certificates for all six courses.
- Offers verifiable certificates with unique links for easy sharing on resumes and professional profiles.
Content
| Courses | No. of Hours | Certificates | Details |
|---|---|---|---|
| Minitab:01 - Application to Predictive Modeling (Descriptive Statistics) | 2h 43m | ✔ | View Curriculum |
| Minitab | 4h 27m | ✔ | View Curriculum |
| Courses | No. of Hours | Certificates | Details |
|---|---|---|---|
| Data Analytics using Minitab | 4h 38m | ✔ | View Curriculum |
| Minitab:03 - Correlation Techniques | 2h 18m | ✔ | View Curriculum |
| Minitab:04 - Regression Modeling | 9h 36m | ✔ | View Curriculum |
| Minitab:05 - Predictive Modeling using Microsoft Excel | 55m | ✔ | View Curriculum |
Description
This course clearly defines its purpose by explaining core concepts and setting clear expectations for learners. It presents Minitab as a robust statistical tool for data analysis, automated computations, and visual reporting, enabling analysts to identify patterns and generate insights efficiently. The program uses Minitab for time-series analysis and forecasting, allowing learners to examine data collected over time and identify structures such as trends, seasonality, and autocorrelation. Through practical examples, the course shows how historical data reveals meaningful patterns and how learners can use those insights to build reliable forecasts and make informed predictions about future outcomes.
Sample Certificate
Requirements
The course is designed for learners of all levels, starting from the basics, so no prior experience is required. All essential concepts are covered in the course, providing a comprehensive learning experience without the need for additional resources.
Some knowledge is beneficial for faster understanding:
- Familiarity with statistical concepts such as mean, standard deviation, and other fundamental measures.
- Basic coding experience, as certain tasks in Minitab may involve programming.
- A creative mindset is required, as data analytics often demands innovative, out-of-the-box thinking.
- Strong motivation to independently complete assignments and projects, which is crucial for practical learning.
Target Audience
- The course is open to all learners, with no specific target audience, starting from the basics and gradually building up.
- It emphasizes perseverance and full dedication as key ingredients for successful learning.
- University students studying data analysis, mathematics, or statistics can use the course as a comprehensive resource to address queries encountered in their studies.
- Professionals looking to advance to the next role can leverage the course to bridge knowledge gaps and strengthen their expertise.
- Experienced individuals in time series analysis can use the course for a quick refresher, revisiting essential terms and concepts applicable to their daily work.
