By the end of this course, learners will be able to explain core machine learning concepts, prepare and analyze data using Python libraries, visualize insights effectively, and build and evaluate basic machine learning models using industry-standard tools.
Learn & Build Machine Learning Models with Python
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Gain insight into a topic and learn the fundamentals.
Intermediate level
Recommended experience
9 hours to complete
Flexible schedule
Learn at your own pace
What you'll learn
Explain core machine learning concepts and prepare data using Python libraries.
Visualize and analyze datasets using NumPy, Pandas, and Matplotlib.
Build and evaluate basic machine learning models using Scikit-learn.
Skills you'll gain
Details to know
Shareable certificate
Add to your LinkedIn profile
Recently updated!
January 2026
Assessments
16 assignments
Taught in English
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There are 4 modules in this course
This module introduces learners to the core concepts of machine learning and establishes a strong foundation in numerical computing using Python. Learners gain an understanding of how machine learning works, its life cycle, and how NumPy is used to create and manipulate numerical data essential for ML workflows.
What's included
6 videos4 assignments
This module focuses on efficient data manipulation using NumPy and introduces Pandas for structured data handling. Learners develop skills in array operations, vectorized computations, and DataFrame-based data exploration, which are critical for data preprocessing in machine learning.
What's included
6 videos4 assignments
This module equips learners with practical data analysis and visualization skills using Pandas and Matplotlib. Learners explore datasets, generate statistical insights, handle missing values, and create meaningful visualizations to communicate data-driven findings effectively.
What's included
6 videos4 assignments
This module introduces practical machine learning implementation using Scikit-learn. Learners focus on data preprocessing, pipeline construction, model evaluation, and linear regression, enabling them to build, evaluate, and interpret machine learning models with confidence.
What's included
6 videos4 assignments
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Frequently asked questions
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