Support Vector Machines in Python: SVM Concepts & Code (Udemy.com)
Learn Support Vector Machines in Python. Covers basic SVM models to Kernel-based advanced SVM models of Machine Learning
Created by: Start-Tech Academy
Last updated April 2026
What you will learn
- Get a solid understanding of Support Vector Machines (SVM)
- Understand the business scenarios where Support Vector Machines (SVM) is applicable
- Tune a machine learning model's hyperparameters and evaluate its performance.
- Use Support Vector Machines (SVM) to make predictions
- Implementation of SVM models in Python
How it compares
Against the other 155 rated Udemy courses in Machine Learning on CourseDuck:
- Rating4.1 out of 5higher than 20% of them
- Reviews564#75 of 156 by number of reviews
- Length6.3 hoursshorter than 55% of them
- Last updatedApril 2026more recently than 83% of them
Course Description
You're looking for a complete Support Vector Machines course that teaches you everything you need to create a Support Vector Machines model in Python, right?
You've found the right Support Vector Machines techniques course!
How this course will help you?
A Verifiable Certificate of Completion is presented to all students who undertake this Machine learning advanced course.
If you are a business manager or an executive, or a student who wants to learn and apply machine learning in Real world problems of business, this course will give you a solid base for that by teaching you some of the advanced technique of machine learning, which are Support Vector Machines.
Why should you choose this course?
This course covers all the steps that one should take while solving a business problem through Decision tree.
Most courses only focus on teaching how to run the analysis but we believe that what happens before and after running analysis is even more important i.e. before running analysis it is very important that you have the right data and do some pre-processing on it. And after running analysis, you should be able to judge how good your model is and interpret the results to actually be able to help your business.
What makes us qualified to teach you?
The course is taught by Abhishek and Pukhraj. As managers in Global Analytics Consulting firm, we have helped businesses solve their business problem using machine learning techniques and we have used our experience to include the practical aspects of data analysis in this course
We are also the creators of some of the most popular online courses - with over 150,000 enrollments and thousands of 5-star reviews like these ones:
This is very good, i love the fact the all explanation given can be understood by a layman - Joshua
Thank you Author for this wonderful course. You are the best and this course is worth any price. - Daisy
Our Promise
Teaching our students is our job and we are committed to it. If you have any questions about the course content, practice sheet or anything related to any topic, you can always post a question in the course or send us a direct message.
Download Practice files, take Quizzes, and complete Assignments
With each lecture, there are class notes attached for you to follow along. You can also take quizzes to check your understanding of concepts. Each section contains a practice assignment for you to practically implement your learning.
Go ahead and click the enroll button, and I'll see you in lesson 1!
Cheers
Start-Tech Academy
Instructor Details
- 4.1 Rating
564 Reviews
Start-Tech Academy
Start-Tech Academy is a technology-based Analytics Education Company and aims at Bringing Together the analytics companies and interested Learners.
Our top quality training content along with internships and project opportunities helps students in launching their Analytics journey.
Founded by Abhishek Bansal and Pukhraj Parikh.
Working as a Project manager in an Analytics consulting firm, Pukhraj has multiple years of experience working on analytics tools and software. He is competent in MS office suites, Cloud computing, SQL, Tableau, SAS, Google analytics and Python.
Abhishek worked as an Acquisition Process owner in a leading telecom company before moving on to learning and teaching technologies like Machine Learning and Artificial Intelligence.
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Reviews
By Ishaaq MM on 9/2/2025
Youtube videos are better than this vague explanations. Not clear enough at the most important parts and skiping them.
By Joyal Jose T S on 9/19/2023
Excellent class all through and very easy to follow the sessions as it is explained in detail.
By Anirban Sarkar on 1/11/2023
The theoritical part was great. But I think the coding part could be made better by adding more examples of how and what can be done to make kernel coding stronger
By Fahim Muntasir on 8/11/2022
The trainers are both well-mannered and vastly experienced. The course not only talks or shows something, it gives enough description and knowledge over the topics. Especially tuning parameters and talking about both types of problems in SVM was outstanding.
By Maryam Soleimani-Alyar on 4/26/2022
Thank you for this course. It has enough information about SVM method and explains this method step by step.
By Gaurang Awatade on 6/21/2020
This course does not explain theory behind machine learning concepts , rather it applies ML models using functions of pandas and numpy. It is a decent course who wishes to get familiar with data preprocessing on built-in datasets.
By Pragyan prakash on 6/8/2020
Till Now I find the audio and quality of video better. It should contain some theory of SVM at the beginning which made you loose 1 point.
By Menna Omar on 4/15/2020
This course was amazing, I enjoy it and learned a lot. The only comment for the instructors is the English accent wasn't very good, It takes awhile to understand what they say. Thank you
By Mohan Bisunke on 4/1/2020
Awesome courses for Vector Machine Courses. Provided with all lectures notes ,well explanation makes the best environments for learning .
By Juari Ritter Müller on 12/23/2019
Good course on anaconda data pre-processing and calculation but the lessons don't have a logical order (there are pratical tutorials in the beginning and introductions at the end)
Quality Score
No CourseDuck member has rated this course yet. Taken it? Give each part a thumbs up or down.
Overall Score : 82 / 100











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