Beginner
57 Lessons
72h 30min
Certificate of Completion
The goal is to introduce the audience to some fundamental machineĀ learning algorithms with implementation.
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This course includes
This course includes
Course Overview
This course teaches you how to code basic machine learning models. The content is designed for beginners with general knowledge of machine learning, including common algorithms such as linear regression, logistic regression, SVM, KNN, decision trees, and more. If you need a refresher, we have summarized key concepts from machine learning, and there are overviews of specific algorithms dispersed throughout the course.
What You'll Learn
Learn fundamental principles and techniques of machine learning.
Understand the benefits and drawbacks of a variety of common machine learning methods.
The key premise of the course is to teach you how to code basic machine learning models.
Develop skills with using machine learning tools to solve real-world issues.
Learn the fundamentals of different learning paradigms (supervised, unsupervised, etc.).
Course Content
Introduction to Course
Introduction to Machine Learning
Exploratory Data Analysis
Data Scrubbing
Pre-Model Algorithms
Split Validation
2 Lessons
Model Design
4 Lessons
Linear Regression
5 Lessons
Logistic Regression
5 Lessons
Support Vector Machines
4 Lessons
K-Nearest Neighbors
4 Lessons
Tree-Based Methods
10 Lessons
Conclusion
1 Lesson
Appendix
2 Lessons
How You'll Learn
You donāt get better at swimming by watching others. Coding is no different. Practice as you learn with live code environments inside your browser.
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Learn faster and smarter with adaptive AI tools embedded in every Educative course.
Built-in assessments let you test your skills. Completion certificates let you show them off.