MLOps Specialization

Diabetic Retinopathy Detection with AI

Learn to understand and implement Deep Neural Networks, Residual Nets, and Convolutional Neural Networks (CNNs) using Keras with TensorFlow 2.0, and evaluate their performance and generalization.

Data Science Methodology

Master the CRISP-DM methodology, identify optimal data sources, and select appropriate analytic models with our comprehensive AI course on data science methodology.

Cervical Cancer Risk Prediction Using ML

The course outlines the learning objectives for understanding XGBoost algorithm theory, performing exploratory data analysis, and implementing XGBoost classifier models using Scikit-Learn.

Intro to ML with Python

A comprehensive course on machine learning using Python, covering deep learning, GANs, image processing, various algorithms, and industrial applications, accessible to all skill levels.

ML: Concepts & Applications

Learn to use Python and libraries for data tasks, understand key machine learning techniques, and apply them to real-world datasets for a strong research foundation.