What you'll get
- 13+ Hours
- 6 Courses
- Course Completion Certificates
- Self-paced Courses
- Technical Support
- Case Studies
Synopsis
- Gain a comprehensive understanding of key statistical concepts and learn to use SAS Enterprise Miner for predictive data analysis.
- Access the course for one year.
- Suitable for anyone eager to learn Predictive Modeling with SAS Enterprise Miner.
- Requires basic knowledge of SAS.
- Receive a Certificate of Completion for each of the six courses, along with project certifications.
- Certificates are verifiable with unique links, ideal for resumes or LinkedIn profiles.
- Learners complete the training through self-paced video lessons.
Content
| Courses | No. of Hours | Certificates | Details |
|---|---|---|---|
| SAS Predictive Modeling:01 - Introduction | 1h 51m | ✔ | View Curriculum |
| SAS Predictive Modeling:02 - Variables | 1h 8m | ✔ | View Curriculum |
| SAS Predictive Modeling:03 - Combination | 2h 43m | ✔ | View Curriculum |
| Courses | No. of Hours | Certificates | Details |
|---|---|---|---|
| SAS Predictive Modeling:04 - Neural Networks | 2h 01m | ✔ | View Curriculum |
| SAS Predictive Modeling:05 - Regression | 40m | ✔ | View Curriculum |
| Logistic Regression Project using SAS Stat | 4h 26m | ✔ | View Curriculum |
Description
Boost your data analytics expertise with the SAS Predictive Modeling course. This program equips learners with advanced skills to analyze data, build accurate predictive models, and generate actionable insights using SAS tools. Ideal for professionals and students seeking to advance their careers in data analytics, business intelligence, or statistical modeling, the course offers hands-on experience with real-world datasets and industry-relevant techniques.
Sample Certificate

Requirements
- Trainees should meet certain prerequisites to grasp the concepts in this predictive modeling course fully.
- The requirements are straightforward, focusing on foundational knowledge rather than advanced skills.
- Learners should have a basic understanding of statistics; those who need a refresher should review the concepts.
- Familiarity with MS Excel is necessary, as the course involves working with Excel data in SAS Enterprise Miner.
- Introductory knowledge of any programming language helps navigate coding-related tasks with ease.
- Individuals who do not meet these prerequisites are encouraged to complete a bridge course before enrolling in the predictive modeling program.
Target Audience
- This course caters to a wide range of learners and helps them determine if Predictive Modeling with SAS Enterprise Miner aligns with their goals.
- Ideal candidates include students with backgrounds in mechanical, computer science, mathematics, or statistics.
- Working professionals in software, banking, insurance, stock markets, and IT who wish to transition into data analysis form a significant portion of the participants.
- Managers and experienced industry professionals aiming to advance their careers as data scientists also benefit from this training.
- Individuals from diverse fields can apply the course to perform data analysis in their specific domains.
- Graduates, postgraduates, and those with master’s degrees are particularly well-suited to enroll in this program.