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Foundations of Machine Learning

This course is part of Fractal Data Science Professional Certificate.

This course cannot be purchased separately - to access the complete learning experience, graded assignments, and earn certificates, you'll need to enroll in the full Fractal Data Science Professional Certificate program. You can audit this specific course for free to explore the content, which includes access to course materials and lectures. This allows you to learn at your own pace without any financial commitment.

Instructors:

English

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Foundations of Machine Learning

This course includes

25 Hours

Of Self-paced video lessons

Beginner Level

Completion Certificate

awarded on course completion

Free course

What you'll learn

  • Build and evaluate machine learning models

  • Apply appropriate metrics for model assessment

  • Develop regression and tree-based models

  • Implement unsupervised learning techniques

  • Solve real-world business problems using ML

Skills you'll gain

Machine Learning
Linear Regression
Logistic Regression
Decision Trees
Unsupervised Learning
Data Preprocessing
Model Evaluation

This course includes:

6 Hours PreRecorded video

12 assignments

Access on Mobile, Tablet, Desktop

FullTime access

Shareable certificate

Get a Completion Certificate

Share your certificate with prospective employers and your professional network on LinkedIn.

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There are 6 modules in this course

This comprehensive course covers fundamental machine learning concepts and techniques. Students learn supervised and unsupervised learning approaches, model evaluation methods, and practical applications through real-world business cases. The curriculum includes hands-on implementation of various algorithms including KNN, regression, decision trees, and clustering.

Introduction to Machine Learning

Module 1 · 2 Hours to complete

Building Your First Machine Learning (ML) Model for Synergix Solutions

Module 2 · 4 Hours to complete

Evaluating Prediction Models

Module 3 · 3 Hours to complete

Linear and Logistic Regression

Module 4 · 5 Hours to complete

Decision Trees for Synergix Solution

Module 5 · 4 Hours to complete

Introduction to Unsupervised Learning

Module 6 · 4 Hours to complete

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: Fractal Data Science Professional Certificate

Instructor

Fractal Analytics
Fractal Analytics

4.4 rating

16 Reviews

83,137 Students

19 Courses

Diverse, Industry-Focused AI and Data Science Courses

Fractal Analytics, as a leading Coursera partner, provides a comprehensive suite of online courses and professional certificates in English, covering topics such as Generative AI, data science, human behavior, coding, data storytelling, responsible AI, and quantum computing. Their offerings include foundational and advanced programs like "GenAI for Everyone," "Coding with Generative AI," "Data Frameworks for Generative AI," and "Python for Data Science," catering to learners from various backgrounds and industries. These courses are designed for continuous learning, blending instructor-led, eLearning, and blended formats, and aim to equip professionals and organizations with in-demand skills for the evolving digital economy, while also supporting career advancement through recognized certifications and practical, hands-on projects

Foundations of Machine Learning

This course includes

25 Hours

Of Self-paced video lessons

Beginner Level

Completion Certificate

awarded on course completion

Free course

Testimonials

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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.