Machine learning (ML) is one of the fastest growing areas in technology and a highly sought after skillset in today’s job market. The World Economic Forum states the growth of artificial intelligence (AI) could create 58 million net new jobs in the next few years, yet it’s estimated that currently there are 300,000 AI engineers worldwide, but millions are needed. This means … [Read more...] about Getting Started with AWS Machine Learning
Machine Learning
Introduction to Artificial Intelligence (AI)
In this course you will learn what Artificial Intelligence (AI) is, explore use cases and applications of AI, understand AI concepts and terms like machine learning, deep learning and neural networks. You will be exposed to various issues and concerns surrounding AI such as ethics and bias, & jobs, and get advice from experts about learning and starting a career in AI. … [Read more...] about Introduction to Artificial Intelligence (AI)
Foundations of Data Science: K-Means Clustering in Python
Organisations all around the world are using data to predict behaviours and extract valuable real-world insights to inform decisions. Managing and analysing big data has become an essential part of modern finance, retail, marketing, social science, development and research, medicine and government. This MOOC, designed by an academic team from Goldsmiths, University of London, … [Read more...] about Foundations of Data Science: K-Means Clustering in Python
Data Wrangling, Analysis and AB Testing with SQL
This course allows you to apply the SQL skills taught in “SQL for Data Science†to four increasingly complex and authentic data science inquiry case studies. We'll learn how to convert timestamps of all types to common formats and perform date/time calculations. We'll select and perform the optimal JOIN for a data science inquiry and clean data within an analysis dataset by … [Read more...] about Data Wrangling, Analysis and AB Testing with SQL
Advanced Computer Vision with TensorFlow
In this course, you will: a) Explore image classification, image segmentation, object localization, and object detection. Apply transfer learning to object localization and detection. b) Apply object detection models such as regional-CNN and ResNet-50, customize existing models, and build your own models to detect, localize, and label your own rubber duck images. c) Implement … [Read more...] about Advanced Computer Vision with TensorFlow