Enroll Course: https://www.coursera.org/learn/sas-predictive-modeling-using-logistic-regression
In today’s data-driven world, the ability to predict outcomes based on historical data is invaluable. One of the most significant tools for achieving this is logistic regression, particularly in the context of SAS/STAT software. Coursera’s course, **Predictive Modeling with Logistic Regression using SAS**, presents an excellent opportunity for professionals looking to bolster their predictive analytics skills.
### Course Overview
The course is designed to give learners a solid understanding of predictive modeling and focuses heavily on the LOGISTIC procedure within SAS. It’s not just about fitting a model; participants will dive deeply into selecting relevant variables, handling categorical data, and overcoming common problems like missing values – all critical when working with large datasets.
### Syllabus Breakdown
1. **Course Overview and Logistics**: This introductory module sets the stage for what you’ll encounter throughout the course. You’ll familiarize yourself with the course structure and the data used in practical examples.
2. **Understanding Predictive Modeling**: Here, you’ll explore the essentials of predictive modeling, getting acquainted with potential analytical challenges. This module is crucial for grounding your understanding in real-world business scenarios.
3. **Fitting the Model**: This is where things get exciting. You will learn how to utilize the LOGISTIC procedure to fit your logistic regression model. You will also gain insights into scoring new cases, making this module particularly hands-on.
4. **Preparing the Input Variables, Part 1**: Every data model faces issues with predictor variables. This module tackles challenges like missing values and overly complex categorical predictors, ensuring you’re well-prepared for any data set.
5. **Preparing the Input Variables, Part 2**: Here, the focus is on variable selection. You will learn how to identify the most predictive variables to optimize your model’s performance.
6. **Measuring Model Performance**: The final major module teaches you how to assess your model’s output. You will learn to determine allocation rules that can maximize profits, and how to iteratively create more advanced predictive models.
7. **SAS Certification Practice Exam**: To top it all off, there’s a practice exam available for those pursuing SAS certification in Statistical Business Analysis using SAS®9.
### Conclusion
This course is a gem for anyone serious about predictive analytics, especially those aiming to use SAS in professional settings. The emphasis on practical skills and real-world applications makes it highly recommendable. Whether you’re just getting started or looking to refine your existing skills, you will find great value in this course.
### Recommendation
Enroll in the **Predictive Modeling with Logistic Regression using SAS** course on Coursera to elevate your data analysis skills to the next level! Your journey into the world of predictive modeling awaits.
Enroll Course: https://www.coursera.org/learn/sas-predictive-modeling-using-logistic-regression