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Machine Learning with Python Fundamentals
This course is part of multiple programs. Learn more.
Course Cost
₹ 8,650
Beginner
Skill Level
5 Weeks
Self-paced Video lessons
This comprehensive course introduces practical machine learning using Python. Students learn the fundamentals of both supervised and unsupervised learning, exploring key algorithms and statistical modeling techniques. The curriculum covers classification, regression, clustering, and dimensional reduction, with popular models like Random Forests and Support Vector Machines. Through hands-on labs, learners apply theoretical knowledge to real-world scenarios, building practical skills in implementing machine learning solutions.
4.5
1,80,138 Enrolled
English
What you'll learn
Understand the fundamentals of supervised and unsupervised machine learning
Implement classification and regression algorithms using Python
Master clustering and dimensionality reduction techniques
Apply statistical modeling concepts to machine learning problems
Develop practical skills through hands-on programming exercises
Build real-world prediction models using various algorithms
Skills you'll gain
This course includes:
PreRecorded video
Graded assignments, exams
Access on Mobile, Tablet, Desktop
Limited Access access
Shareable certificate
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Top companies offer this course to their employees
Top companies provide this course to enhance their employees' skills, ensuring they excel in handling complex projects and drive organizational success.
There are 5 modules in this course
This comprehensive course provides a practical introduction to machine learning using Python. The curriculum covers fundamental concepts including supervised and unsupervised learning, statistical modeling, and algorithm implementation. Students learn through hands-on practice with real-world applications, exploring various techniques like classification, regression, clustering, and dimensional reduction. The course emphasizes practical skill development through interactive labs and projects.
Introduction to Machine Learning
Module 1
Regression
Module 2
Classification
Module 3
Unsupervised Learning
Module 4
Recommender Systems
Module 5
Fee Structure
Individual course purchase is not available - to enroll in this course with a certificate, you need to purchase the complete Professional Certificate Course. For enrollment and detailed fee structure, visit the following: IBM Data Science Professional Certificate, Python Data Science
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Faculties
These are the expert instructors who will be teaching you throughout the course. With a wealth of knowledge and real-world experience, they're here to guide, inspire, and support you every step of the way. Get to know the people who will help you reach your learning goals and make the most of your journey.
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Courses
Saeed Aghabozorgi, PhD, serves as a Senior Data Scientist at IBM, where he specializes in developing enterprise-level applications that transform complex data into actionable business knowledge. His expertise spans data mining, machine learning, and statistical modeling, with particular emphasis on large-scale datasets. As an accomplished educator, his courses have reached over 100,000 learners worldwide, maintaining an impressive 4.7 instructor rating. His most notable contribution includes the Machine Learning with Python course, which has enrolled more than 482,000 students and covers comprehensive topics from supervised learning to advanced clustering techniques. Through his work at IBM, he continues to advance the field of data science by developing cutting-edge analytical methods and sharing his expertise through educational initiatives that bridge the gap between theoretical knowledge and practical application.
Frequently asked Questions
Below are some of the most commonly asked questions about this course. We aim to provide clear and concise answers to help you better understand the course content, structure, and any other relevant information. If you have any additional questions or if your question is not listed here, please don't hesitate to reach out to our support team for further assistance.