
Machine Learning Specialization
Master Machine Learning, From Basics to Advanced Models
Why Choose This Course?
Join thousands of learners and master new skills with our comprehensive learning platform
Students Enrolled
3,552
Join thousands of learners worldwide
Course Rating
4.89/5
Highly rated by our community
Course Content
15 Lessons
Comprehensive curriculum with assessments
Total Duration
1h 20m
Self-paced learning experience
Get Your Certificate
Complete this machine learning specialization course and earn an official certificate of completion. Perfect for showcasing your skills to employers and adding credibility to your professional profile.
Certificate Price
Limited time offer - Pay after completion
Premium Quality
Certificate of Achievement
This certifies that
[Your Name Here]
has successfully completed
Machine Learning Specialization
DevsCall
Learning Platform
[Completion Date]
1h 20m Course
Course Content
3 sections • 15 lessons • 0 quizzes
1Foundations of Machine Learning
5 lessons
Foundations of Machine Learning
2Advanced Supervised and Unsupervised Learning
5 lessons
Advanced Supervised and Unsupervised Learning
3ML Applications and Best Practices
5 lessons
ML Applications and Best Practices
Got Questions? We've Got Answers
Everything you need to know about this course and learning experience
Frequently Asked Questions
Basic familiarity with Python is recommended, but we provide introductory lessons to get you comfortable with the essentials before diving into machine learning concepts.
You’ll work hands-on with popular Python libraries such as NumPy, Pandas, Scikit-learn, TensorFlow, and PyTorch, along with practical projects to strengthen your skills.
Yes! After successfully completing all lessons and projects, you’ll earn a professional certificate that you can showcase on LinkedIn, résumés, and portfolios.
On average, learners complete the course in 3–6 months with part-time study (5–7 hours per week). However, you can learn at your own pace.
You’ll complete real-world projects such as building predictive models, image classifiers, recommendation engines, and clustering systems perfect for showcasing in a data science portfolio.
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