Aarti Bagul

Aarti Bagul is a machine learning engineer at Snorkel AI. Before Snorkel, she worked closely with Andrew Ng in various capacities: She helped build and invest in machine learning companies at the AI Fund. Previously, she was a machine learning engineer at Landing AI and was the head teacher’s assistant for Dr. Ng’s deep learning class at Stanford University. She graduated with a Master's in Computer Science from Stanford and a Bachelor's in Computer Science and Computer Engineering from NYU with the highest honors.

Coursera

Stanford University,DeepLearning.AI

Advanced Learning Algorithms (Coursera)

Data Science

Expand your knowledge in machine learning by diving into 'Advanced Learning Algorithms'. This course will guide you through building and training complex neural networks using TensorFlow for effective multi-class classification tasks. You'll also learn best practices for developing machine learning models that generalize well to real-world data and scenarios, as well as explore decision trees and ensemble methods like random forests and boosted trees.

Jun 15th 2026

4 Weeks

Algorithms Machine Learning Neural Networks

Coursera

Stanford University,DeepLearning.AI

Supervised Machine Learning: Regression and Classification (Coursera)

Data Science

Dive into the world of Supervised Machine Learning with our introductory course designed to equip you with essential skills in model building and training. This course will guide you through constructing and refining regression and classification models using Python's powerful libraries such as NumPy and scikit-learn, enabling you to tackle prediction and binary classification tasks effectively.

Jun 15th 2026

3 Weeks

Python Machine Learning Regression

Coursera

Stanford University,DeepLearning.AI

Unsupervised Learning, Recommenders, Reinforcement Learning (Coursera)

Data Science

Dive into the world of advanced machine learning with our 'Unsupervised Learning, Recommenders, Reinforcement Learning' course. This comprehensive program will equip you with essential skills in unsupervised learning techniques like clustering and anomaly detection, as well as cutting-edge approaches to building effective recommender systems and implementing deep reinforcement learning models.

Jun 15th 2026

3 Weeks

Machine Learning Clustering Recommender Systems

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