Supervised Machine Learning – Supervised Machine Learning is a foundational approach to teaching machines how to make predictions based on labeled data. In this course, you’ll explore key concepts such as regression, classification, and how algorithms like Decision Trees, Support Vector Machines, and Neural Networks operate. Learn to train models, evaluate their performance, and fine-tune them for better accuracy. With practical examples and coding exercises, you’ll gain hands-on experience in building models that can predict outcomes from real-world data. Whether you’re stepping into data science or enhancing your AI skills, this course will help you master the art of supervised learning.
What You Will Learn?
| Build machine learning models in Python using popular machine learning libraries NumPy & scikit-learn |
| Build & train supervised machine learning models for prediction & binary classification tasks, including linear regression & logistic regression |
Skills You Will Gain
- Linear Regression
- Regularization to Avoid Overfitting
- Logistic Regression for Classification
- Gradient Descent
- Supervised Learning
Also Check : Vocol: Elevating Team Collaboration with AI-Powered Transcriptions
Coursera Course Enrollment Process
Step 1 – Visit the Course Page
Click on the Orange Button below – GET THE FREE ONLINE COURSE to access the Course Page.
Step 2 – Sign Up or Log In
Click on the “Sign Up” or “Log In” button located at the top-right corner of the page. You can register using your email address, Google account, or Facebook account.
Step 3 – Enroll for FREE
Once you’re logged in, select the “Enroll Now” option to gain access to the course materials.
Step 4 – Begin Your Learning Journey: After clicking “Start Learning,” you will be seamlessly redirected to your personalized dashboard, where you can embark on your course at your own pace !
Also Check : Virtual Charity Drive Work From Home Part Time Internship by Pawzz
