Machine Learning in Python

Sharpening your predictive modelling skills to set you apart as a data scientist instead of data analyst covers regressions, classifications, and clustering.

with Iliya Valchanov

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Course Overview

Machine Learning in Python builds upon the statistical knowledge you gained earlier in the program. This course focuses on predictive modelling and enters multidimensional spaces which require an understanding of mathematical methods, transformations, and distributions. We will introduce these concepts, as well as complex means of analysis such as clustering, factoring, Bayesian inference, and decision theory, while also allowing you to exercise your Python programming skills.

72 High Quality Lessons
20 Practical Tasks
5 Hours of Video
Certificate of Achievement

Skills you will gain

data analysismachine learningprogrammingpythontheory

What You'll Learn

This course is focused on predictive modelling via an array of approaches such as linear regression, logistic regression, and cluster analysis. It combines comprehensive theory with lots of practice to allow you to exercise your Python skills.

Learn the fundamentals of predictive modelling 
Understand the theory behind linear regression 
Perform linear regression with sklearn 
Grasp logistic regression 
Approach cluster analysis 
Implement K-means clustering 


“This is the place where you will learn the advanced statistical techniques that are used by successful data scientists. I will teach you regression analysis, clustering, and factor analysis. After this course, you’ll be able to fill your resume with skills and have plenty left over to show off at the interview.”

Iliya Valchanov
Co-founder at 365 Data Science
Machine Learning in Python

with Iliya Valchanov

Start Course