General AI Mastery Toolbox: Master AI & Drive Success

Applied ML An Introduction

It provides professionals with the necessary skills to define machine learning problems, prepare data, and identify applications across a variety of domains.

Launching into ML

Master the process of exploratory data analysis, train AutoML models with Vertex AI and BigQuery ML, optimize models using performance metrics and loss functions, and generate scalable datasets for training and evaluation.

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.

Intel AI Fundamentals Specialization

This course prepares you to effectively promote and sell AI solutions by providing a deep understanding of AI fundamentals, relevance, and practical applications.

ML Algorithms: Supervised Learning Tip to Tail

This course concentrates on the fundamentals of machine learning, including decision trees, k-nearest neighbors, and support vector machines. It addresses data preparation and production challenges and requires a rudimentary understanding of Python, linear algebra, and statistics.