Master machine learning fundamentals with Andrew Ng and Factored. Learn supervised, unsupervised learning, and real-world applications using Python and TensorFlow.
Supervised and unsupervised learning.
Advanced techniques like ensemble methods and recommender systems.
Hands-on projects using TensorFlow and scikit-learn.
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Linear Regression
Logistic Regression
Neural Networks
Decision Trees
Recommender Systems
Supervised Learning
Gradient Descent
Unsupervised Learning
Reinforcement Learning

Factored’s Role in Redefining Machine Learning Education

The Machine Learning Specialization, a collaboration between DeepLearning.AI and Stanford University, offers a comprehensive introduction to modern machine learning. Led by Dr. Andrew Ng and supported by esteemed instructors, this beginner-friendly program equips learners with the practical and theoretical foundations needed to build real-world AI applications. With over 550,000 enrollments and a stellar 4.9-star rating, this specialization has empowered countless learners to embark on their AI journeys.

Factored’s Key Contributions

Factored engineers, David Valencia and Santiago Hernández, were instrumental in ensuring the technical excellence of this course. Their contributions focused on optimizing hands-on projects, refining workflows for building machine learning models and enhancing the practical learning experience for students. The team collaborated with instructors to integrate cutting-edge tools like TensorFlow, NumPy, and scikit-learn, ensuring learners gain the most demanded skills in today’s AI-driven industries.

What Learners Will Master

This three-course series offers in-depth knowledge across key areas of machine learning:

  • Supervised Learning: Build regression and classification models, including logistic and linear regression, neural networks, and decision trees.
  • Unsupervised Learning: Explore clustering, anomaly detection, and dimensionality reduction.
  • Advanced Techniques: Master ensemble methods (random forests, boosting), recommendation systems, and reinforcement learning.

Practical, Industry-Relevant Projects

Learners tackle real-world challenges, such as:

  • Building robust machine learning models that generalize across diverse datasets.
  • Applying collaborative filtering and deep learning to design recommendation systems.
  • Training neural networks for multi-class classification tasks.

Impact and Global Reach

Factored’s involvement highlights its role in advancing education and helping address the global skills gap in data science. By empowering learners with practical expertise, this program shapes the next generation of AI innovators.

Enroll in the Machine Learning Specialization today.

“The Machine Learning course became a guiding light. Andrew Ng explains concepts with simple visualizations and plots. I learned how to evaluate my training results and explain the outcomes to my colleagues, boss, and even the vice president of our company.”
Hsin-Wen Chang
Sr. C++ Developer, Zealogics

About the instructor

Dr. Andrew Ng
Co-Founding Advisor, Factored; Managing General Partner, AI Fund; Founder, DeepLearning.AI; Co-founder, Coursera