This three-module course introduces machine learning and data science for everyone with a foundational understanding of machine learning models. You’ll learn about the history of machine learning, applications of machine learning, the machine learning model lifecycle, and tools for machine learning. You’ll also learn about supervised versus unsupervised learning, classification, regression, evaluating machine learning models, and more. Our labs give you hands-on experience with these machine learning and data science concepts. You will develop concrete machine learning skills as well as create a final project demonstrating your proficiency.

Machine Learning Introduction for Everyone

Machine Learning Introduction for Everyone


Instructors: Aije Egwaikhide
31,905 already enrolled
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311 reviews
What you'll learn
Compare and contrast artificial intelligence, machine learning, and deep learning
Explain the machine learning models development lifecycle
Differentiate between supervised and unsupervised machine learning
Evaluate classification models using metrics such as accuracy, confusion matrices, precision, and recall
Skills you'll gain
- Model Training
- Machine Learning
- Artificial Intelligence
- Reinforcement Learning
- Machine Learning Methods
- Deep Learning
- Predictive Modeling
- Regression Analysis
- Applied Machine Learning
- Artificial Intelligence and Machine Learning (AI/ML)
- Unsupervised Learning
- Model Evaluation
- Machine Learning Algorithms
- Supervised Learning
Tools you'll learn
Details to know

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There are 3 modules in this course
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Reviewed on Sep 23, 2024
Excellent. Teaching techniques are unique. Keep it UP....
Reviewed on Oct 31, 2022
Suitable for a beginner course. The course taught is >90% accurate to the quiz given, making learners not confused about the fundamentals of machine learning science.
Reviewed on Jun 4, 2025
It's a great time and experience to learn machine learning
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