What you'll get
- 13+ Hours
- 6 Courses
- Course Completion Certificates
- Self-paced Courses
- Technical Support
- Case Studies
Synopsis
- Gain a solid understanding of essential statistical principles while learning to leverage SAS Enterprise Miner for predictive analytics and data-driven insights.
- One-year access to all course materials for flexible, self-paced learning.
- Suitable for anyone committed to building expertise in predictive analytics using SAS Enterprise Miner.
- Prior familiarity with SAS is recommended but not mandatory.
- Participants receive a Certificate of Completion for each of the six courses and associated projects.
- Certificates are verifiable via a unique online link, making them ideal for resumes and LinkedIn profiles.
- Delivered as a self-paced video course for convenient learning.
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
This course offers comprehensive training in predictive modeling using SAS Enterprise Miner, focusing on statistical methods and their practical application for forecasting and analyzing data. Participants gain hands-on experience in handling real-world datasets, applying statistical techniques, and building predictive models.
The program blends theoretical understanding with practical exercises, ensuring learners can confidently interpret data and generate actionable insights. By the end of the course, participants will be equipped with the knowledge to use SAS Enterprise Miner effectively for predictive analytics across industries, including finance, IT, and research.
Sample Certificate
Goals
- To provide a solid understanding of statistical concepts relevant to predictive modeling
- To teach participants how to use SAS Enterprise Miner to analyze and predict data trends
- To develop practical skills applicable to real-world predictive analytics projects
- To prepare learners for professional roles in data science and analytics
Objectives
- Understand fundamental and advanced statistical concepts used in predictive analytics
- Gain hands-on experience with SAS Enterprise Miner for building predictive models
- Learn to work with Excel data and integrate it into SAS for analysis
- Apply coding and programming skills to enhance predictive modeling tasks
- Develop the ability to interpret results and generate actionable business insights
Requirements
- Basic understanding of statistics; a refresher may be beneficial before starting
- Familiarity with Microsoft Excel for handling data inputs
- Introductory knowledge of a programming language to facilitate working with SAS
- Motivation to learn and willingness to complete exercises and projects
Optional: A bridge course for learners who want to strengthen their prerequisites
Target Audience
- Students from mathematics, statistics, computer science, or engineering backgrounds
- Working professionals in software, banking, insurance, IT, or finance looking to shift into data analysis
- Managers and experienced professionals seeking to advance as data scientists
- Individuals from various fields aiming to leverage predictive analytics in their domain
- Graduate, postgraduate, and professional learners aiming to enhance analytical skills
FAQ
Q1. Do I need prior experience with SAS to join the course?
Familiarity with SAS is suggested, though the course is designed to take learners from fundamental concepts to advanced predictive modeling techniques.
Q2.Will participants be awarded a certificate upon completing the course?
Yes, participants earn verifiable Certificates of Completion for each course and project, which can be added to resumes and LinkedIn profiles.
Q3. Is this course suitable for beginners?
Yes, beginners with some statistical and Excel knowledge can benefit from this course, though prior SAS familiarity helps accelerate learning.
Q4. How much time should I dedicate to the course?
Learners are encouraged to dedicate consistent weekly hours to complete the self-paced modules and projects efficiently.
Career Benefits
- Develop expertise in predictive modeling and data analysis using SAS Enterprise Miner
- Gain practical experience applicable to real-world projects across industries
- Boost career opportunities in roles such as Data Analyst, Data Scientist, or Business Analyst.
- Build confidence in interpreting and visualizing data for decision-making
- Earn verifiable certificates to showcase skills and improve career prospects
