By the end of this course, learners will be able to build, evaluate, and optimize machine learning models using Python. They will develop the ability to preprocess data with NumPy and Pandas, visualize insights using Matplotlib, and implement workflows with scikit-learn pipelines. Learners will apply regression, classification, clustering, and dimensionality reduction techniques to real-world datasets, while mastering hyperparameter tuning for improved model performance.
Machine Learning with Python: Build & Optimize
Machine Learning with Python: Build & Optimize
This course is part of AI Driven Machine Learning with Python Specialization
Instructor: EDUCBA
Included with 
Gain insight into a topic and learn the fundamentals.
8 hours to complete
Flexible schedule
Learn at your own pace
What you'll learn
Build and optimize ML models using scikit-learn.
Preprocess and visualize data with NumPy, Pandas, and Matplotlib.
Apply regression, classification, and clustering techniques.
Skills you'll gain
- Predictive Modeling
- Feature Engineering
- Statistical Modeling
- Unsupervised Learning
- Data Science
- NumPy
- Matplotlib
- Statistical Machine Learning
- Applied Machine Learning
- Regression Analysis
- Pandas (Python Package)
- Performance Tuning
- Data Visualization
- Python Programming
- Machine Learning Algorithms
- Data Manipulation
- Machine Learning
- Scikit Learn (Machine Learning Library)
- Dimensionality Reduction
- Data Processing
Details to know
Shareable certificate
Add to your LinkedIn profile
Recently updated!
October 2025
Assessments
11 assignments
Taught in English
See how employees at top companies are mastering in-demand skills
Build your subject-matter expertise
This course is part of the AI Driven Machine Learning with Python Specialization
When you enroll in this course, you'll also be enrolled in this Specialization.
- Learn new concepts from industry experts
- Gain a foundational understanding of a subject or tool
- Develop job-relevant skills with hands-on projects
- Earn a shareable career certificate
There are 3 modules in this course
This module introduces learners to the fundamentals of machine learning, including its lifecycle, prerequisites, and essential data handling techniques. Learners will gain practical skills in numerical computing with NumPy and data analysis using Pandas, setting a solid foundation for advanced machine learning tasks.
What's included
15 videos4 assignments
This module focuses on preparing and transforming data for machine learning models. Learners will master visualization using Matplotlib and Pandas, understand the importance of scaling and encoding, and implement preprocessing pipelines for streamlined workflows.
What's included
7 videos3 assignments
This module provides hands-on experience with building, evaluating, and optimizing machine learning models. Learners will explore regression, classification, clustering, dimensionality reduction, and hyperparameter tuning to achieve robust and scalable solutions.
What's included
15 videos4 assignments
Earn a career certificate
Add this credential to your LinkedIn profile, resume, or CV. Share it on social media and in your performance review.
Explore more from Machine Learning
Why people choose Coursera for their career
Felipe M.
Learner since 2018
"To be able to take courses at my own pace and rhythm has been an amazing experience. I can learn whenever it fits my schedule and mood."
Jennifer J.
Learner since 2020
"I directly applied the concepts and skills I learned from my courses to an exciting new project at work."
Larry W.
Learner since 2021
"When I need courses on topics that my university doesn't offer, Coursera is one of the best places to go."
Chaitanya A.
"Learning isn't just about being better at your job: it's so much more than that. Coursera allows me to learn without limits."
Open new doors with Coursera Plus
Unlimited access to 10,000+ world-class courses, hands-on projects, and job-ready certificate programs - all included in your subscription
Advance your career with an online degree
Earn a degree from world-class universities - 100% online
Join over 3,400 global companies that choose Coursera for Business
Upskill your employees to excel in the digital economy
Frequently asked questions
To access the course materials, assignments and to earn a Certificate, you will need to purchase the Certificate experience when you enroll in a course. You can try a Free Trial instead, or apply for Financial Aid. The course may offer 'Full Course, No Certificate' instead. This option lets you see all course materials, submit required assessments, and get a final grade. This also means that you will not be able to purchase a Certificate experience.
When you enroll in the course, you get access to all of the courses in the Specialization, and you earn a certificate when you complete the work. Your electronic Certificate will be added to your Accomplishments page - from there, you can print your Certificate or add it to your LinkedIn profile.
Yes. In select learning programs, you can apply for financial aid or a scholarship if you can’t afford the enrollment fee. If fin aid or scholarship is available for your learning program selection, you’ll find a link to apply on the description page.
More questions
Financial aid available,