WHAT’S INCLUDED
Course description
Python is a core skill in machine learning, and this course equips you with the tools to apply it effectively. You’ll learn key ML concepts, build models with scikit-learn, and gain hands-on experience using Jupyter Notebooks.
Start with regression techniques like linear, multiple linear, polynomial, and logistic regression. Then move into supervised models such as decision trees, K-Nearest Neighbors, and support vector machines. You’ll also explore unsupervised learning, including clustering methods and dimensionality reduction with PCA, t-SNE, and UMAP.
Through real-world labs, you’ll practice model evaluation, cross-validation, regularization, and pipeline optimization. A final project on rainfall prediction and a course-wide exam will help you apply and reinforce your skills.
Enroll now to start building machine learning models with confidence using Python.
When you enroll in this course, you'll also be asked to select a specific program.
- Learn new concepts from industry experts
- Gain a foundational understanding of a subject or tool
- Develop job-relevant skills with hands-on projects
- Earn a shareable career certificate from IBM
Skills covered in this course
Instructor
IBM
American multinational technology company headquartered in Armonk, New York, and present in over 175 countries.
Student Feedback
Recent Reviews
good course , some part is typical more statistical part shown, even i have good understanding of ML , so new learner will find little typical. rest tutor voice and language is understandable.
This is a very good start for Machine leaning with Python. I didnt have much idea about ML concepts but this course gave me great understanding on each topic and lot of learning. Awesome Course !!
Great course, they teach the very basic steps for data analysis world, which is awesome so we can get a solid basics understanding, the tests are in a great level (neither too easy nor too hard).