Neelesh Tiruviluamala

Neel Tiruviluamala is a math professor who has been consulting in the machine learning space for over ten years. He enjoys working on problems related to the supply chain because the data sets involved are rich and are amenable to a host of interesting quantitative tools.

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Advanced AI Techniques for the Supply Chain (Coursera) Coursera
LearnQuest

Advanced AI Techniques for the Supply Chain (Coursera)

Dive into the world of advanced AI with our specialized course on 'Advanced AI Techniques for the Supply Chain'. Learn how to leverage sophisticated machine learning models to enhance decision-making processes, streamline logistics, and optimize resource allocation within your supply chain. This comprehensive course is designed for professionals looking to harness the full potential of AI in supply chain management.

Jun 1st 2026
3 Weeks
Capstone Project: Predicting Safety Stock (Coursera) Coursera
LearnQuest

Capstone Project: Predicting Safety Stock (Coursera)

Dive into the world of predictive analytics with our Capstone Project: Predicting Safety Stock course. Gain insights into optimizing inventory management by accurately forecasting product demand and determining appropriate safety stock levels. This course is ideal for professionals looking to refine their skills in data analysis and improve supply chain performance.

Jun 1st 2026
3 Weeks
Fundamentals of Machine Learning for Supply Chain (Coursera) Coursera
LearnQuest

Fundamentals of Machine Learning for Supply Chain (Coursera)

Dive into the world of machine learning and its application to supply chain management with our Fundamentals of Machine Learning for Supply Chain course. Whether you're a seasoned professional or new to the field, this course will equip you with Python skills needed to analyze intricate data sets and optimize supply chain processes.

Jun 1st 2026
4 Weeks
Capstone Project: Advanced AI for Drug Discovery (Coursera) Coursera
LearnQuest

Capstone Project: Advanced AI for Drug Discovery (Coursera)

Embark on a transformative journey into the heart of drug development with 'Capstone Project: Advanced AI for Drug Discovery'. This course delves deep into leveraging cutting-edge AI to identify and target specific areas within COVID-19 virus mutations that could be potential therapeutic targets. By comparing genome sequences, performing dimensionality reduction through PCA, and identifying common features, learners will gain a comprehensive understanding of how AI can revolutionize the drug discovery process.

Jun 1st 2026
3 Weeks
Introduction to Data Science and scikit-learn in Python (Coursera) Coursera
LearnQuest

Introduction to Data Science and scikit-learn in Python (Coursera)

Dive into the world of data science and artificial intelligence with our beginner-friendly course. Learn how to use Python effectively for hypothesis creation and testing, explore key concepts in EDA, and master powerful tools such as Numpy, Pandas, and scikit-learn. This course is perfect for those new to data science who want to build a strong foundation.

Jun 1st 2026
4 Weeks
Machine Learning Models in Science (Coursera) Coursera
LearnQuest

Machine Learning Models in Science (Coursera)

Embark on a journey into the world of applying machine learning techniques to solve complex scientific challenges. This course will guide you through every step of the machine learning pipeline, from data cleaning and transformation to running advanced algorithms. Perfect for scientists, researchers, and anyone interested in leveraging AI for problem-solving.

Jun 1st 2026
4 Weeks
Neural Networks and Random Forests (Coursera) Coursera
LearnQuest

Neural Networks and Random Forests (Coursera)

Dive deep into the world of advanced artificial intelligence with our 'Neural Networks and Random Forests' course. Learn to construct sophisticated neural network models and random forest algorithms from scratch, understanding their structures and properties thoroughly. This course will equip you with essential skills in avoiding overfitting, regularization techniques, and optimizing hyper-parameters for effective model performance.

Jun 1st 2026
3 Weeks
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