logistic regression online course

Last Updated on August 8, 2022 by Team College Learners

Logistic regression is a popular method to predict a categorical response. It is a special case of linear regression where the target variable is categorical in nature. Logistic Regression finds its use in various fields like finance, economics, medicine, and social sciences. If you are confused with the math behind logistic regression, then this logistic regression course is for you.

Logistic regression is a fundamental tool of statistical learning, and this course will teach you how to use it with Python. You’ll learn how to build models to analyze your data, discover patterns in your data, and predict future outcomes. This course is completely self-paced, so you can study when and where you want — no commute necessary!

Logistic Regression Questions | Questions On Logistic Regression

Top 4 logistic regression course

The best logistic regression course is the one that will teach you the most, in a self-paced and highly personalizable way. The four courses we recommend are based on your background, experience, and goals.

1. Deep Learning Prerequisites: Logistic Regression in Python (Udemy)

If you want to build a career in deep learning but have no idea about where to begin, then this course seems a good starting point. To take the classes, you are expected to have a basic knowledge of Python programming along with Numpy Stack and mathematical areas like probability, matrices, and derivatives. Throughout the lessons, you will be introduced to various scenarios to help you understand the applications of this field and experiment with them. Also, check out our compilation of Best Numpy Courses.

2. Logistic Regression using SAS – In depth Predictive Modeling (Udemy)

In these lessons, you will learn all about developing predictive models using SAS and the obstacles encountered by the analysts during the various steps. Commence by exploring the techniques of data and multicollinearity treatment, and types, selection of variables. Following this, the instructor will guide you through evaluating the robustness of your model and validating it. By the end of the journey, you will have the confidence to crack relevant interviews and go for more advanced certifications.

3.  Multiple and Logistic Regression in R (DataCamp)

If you have prior knowledge of linear regression and are looking forward to leveraging upon that, then you are where you need to be. The introductory classes discuss parallel slopes models, as well as evaluation and comparison of models. Apart from this, the lessons also cover multiple and logistic regression that can be used to predict outcomes and perform classification of observations. End the course by working on a case study based on a real-world situation.

4. Logistic Regression Courses (Coursera)

Coursera brings you over 60 courses and certifications regarding various aspects of this concept. The content on this platform is categorized based on the difficulty level, ensuring that there is something for every interested individual. Some of the important topics covered include logistic regression in R, ML classification, ML in finance, regression modeling, AI engineering, and neural networks. Don’t forget to check out the Best Machine Learning Engineering Courses curated by us.