Advanced Machine Learning with Python: Master the Algorithms (Udemy.com)
Go beyond the basics. Master Feature Engineering, SVMs, Random Forests, and Model Tuning with Scikit-Learn.
Created by: Eduero Academy, Inc.
Last updated January 2026
What you will learn
- Extract features from categorical variables, text, and images
- Solve real-world problems using machine learning techniques
- Exploit the power of Python to handle data extraction, manipulation, and exploration techniques
- Implement machine learning classification and regression algorithms from scratch in Python
- Dive deep into the world of analytics to predict situations correctly
- Predict the values of continuous variables
- Classify documents and images using logistic regression and support vector machines
- Create ensembles of estimators using bagging and boosting techniques
- Evaluate the performance of machine learning systems in common tasks
How it compares
Against the other 388 rated Udemy courses in Python on CourseDuck:
- Rating3.8 out of 5higher than 3% of them
- Reviews41#382 of 389 by number of reviews
- Length3.7 hoursshorter than 82% of them
- Last updatedJanuary 2026more recently than 76% of them
Quality Score
Overall Score : 76 / 100
Course Description
You know the basics of Data Science. Now, it’s time to master the craft.
Many courses teach you how to run a simple linear regression. But real-world data is messy, complex, and requires advanced strategies. If you are ready to move beyond "Hello World" tutorials and start building robust, deployment-ready models, this course is for you.
Welcome to Advanced Machine Learning. This course is your bridge from "Junior Analyst" to "Senior Data Scientist." We strip away the fluff and dive deep into the mathematical intuition and practical implementation of the industry's most powerful algorithms using Python and Scikit-learn.
What will you build? We believe in learning by doing. You won't just watch code; you will code along with us to build sophisticated projects, including:
Medical Prognosis: Predict insurance risk based on patient data using Random Forests.
Computer Vision: Build a letter recognition system using Support Vector Machines (SVMs).
Natural Language Processing: Create a document classification system that can read and sort text.
What skills will you master?
Advanced Algorithms: Go deep into Support Vector Machines (SVMs) and Random Forests. Understand how they work under the hood, not just how to import them.
Feature Engineering: This is the secret sauce of Data Science. Learn to extract meaningful features from categorical variables, raw text, and images to drastically improve model accuracy.
Model Evaluation: Move beyond simple accuracy scores. Learn to use Confusion Matrices, Precision, Recall, and F1-Scores to truly understand your model's performance.
Parameter Tuning: Stop guessing. Learn the scientific approach to fine-tuning your hyperparameters for peak performance.
Why take this course? In the competitive world of AI, knowing how to use a library isn't enough. You need to know which algorithm to use, why to use it, and how to optimize it. This course gives you that strategic advantage.
Whether you are a professional looking to automate complex tasks or a student aiming for a top-tier Data Science role, this curriculum is designed to get you there fast.
Enroll today, and let's start building the future of AI.
Instructor Details
- 3.8 Rating
41 Reviews
Eduero Academy, Inc.
Eduero is a leading provider of technical training through on-demand streaming, dedicated to empowering independent instructors with comprehensive expertise that extends beyond technical skills. Our courses are meticulously designed, undergoing rigorous planning, thorough reviews, and stringent quality assurance processes to ensure the highest standards of online education. Each course incorporates hands-on exercises at the end of every section, enabling learners to demonstrate mastery and apply their knowledge effectively.
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Reviews
By Johannes Schneider on 1/31/2024
only scratches the surface without ever explaining any of the underlying concepts of the algorithms used. Also in the examples it's never explained why a a specific algorithm is used.
By Purnima Pandit on 3/17/2022
Nice, although addition of few introductory sildes on the concepts implemented, would aid in better understanding and enhance the course.
By David Bierbrauer on 2/16/2022
The topics are decent, but some of the presentations could have been more backed up by additional graphics.
By Jwalit Bhavinkumar Miniwala on 12/8/2020
Fabulous Teaching
By Ziqun Ye on 5/7/2018
not enough deep explanation. Only shallow introduction which can be found everywhere online. Kinda disappointing since I am expecting to learn more deeply
By N S on 11/17/2017
I went with manifold chapter first and the author didn't think that it is necessary to explain how manifold works, what is manifold etc etc. The author directly jumped to code. Who will understand such lectures. The course is not worth it. Waste of money. Please ask the author to explain first and then go for the code
By David Gerner on 10/15/2017
Great in-depth course. I really like the to the point explanation for each topic, it makes me understand the brief concepts but still leave some space for me to explore it myself.
By Samon Mathews on 9/20/2017
Great comprehensive course! I was able to learn all these different and very interesting machine learning techniques in Python! This was a very deep and involved class covering all sorts of algorithms and leaving you with an extremely versatile set of tools to conduct your own data sciences.
By Thomas R. Ohlin on 8/29/2017
This was a new area of learning for me, but I found the speaker to be hard to understand at times. I have some hearing problems, but the speaker brought out the worst in them! I have listened to Bruce Myron in many different courses and did NOT have this problem. You can have the course back, I'm through with it.
By Edgar Furtado
Excellent
By Kent Furtado on 9/13/2017




