ML & Human Learning

MLOps1 (Azure): Deploying AI & ML Models in Production using Microsoft Azure ML

The material equips data engineers to incorporate machine learning models into pipelines while adhering to best practices in collaboration, version control, and artifact management.

Data Science and ML Capstone Project

A program that emphasizes the practical implementation of data science and machine learning to overcome obstacles through the use of Python.

AI in Architectural Design: Introduction

In-depth study of the applications of machine learning and computer vision, as well as practical experience in data analysis and Python programming.

AI Skills Tailored to Engineers: Data Engineering and Data Pipelines

Acquire the fundamental skills of data management, extraction, querying, and visualization to power your AI initiatives.

Bias and Discrimination in AI

This course delves deeply into AI bias, equipping students with the knowledge they need to design responsible and ethical AI systems.

Teach Teens Computing: Understanding AI for Educators

Explores the ethical consequences, practical applications, and varieties of AI systems in education and the workplace.

Machine Learning

Offers a wider understanding and practical skills for excelling at machine learning and pursuing research opportunities.

AI in Practice: Applying AI

Acquire actionable insights to effectively formulate and execute AI strategies within your organization.

Machine Learning Implementation and Operations in AWS

In order to facilitate effective learning, this course provides learners with the necessary skills to develop scalable and resilient ML solutions on AWS, combining theory and practical experience.

Machine Learning Models

Learn the ability to employ machine learning techniques to resolve classification, regression, forecasting, and clustering issues in business settings.