Deep Learning on Azure with Python: Introduction to Machine Learning

Explore machine learning basics to build more efficient systems

This self-paced course offers you the chance to explore the key skills needed to become a machine learning engineer, in turn developing your understanding of how deep learning works. Machine learning is the process through which artificial intelligence systems use data to become more efficient and effective. No human input is required, beyond the data science skills needed to build machine learning models and set parameters for refinement.

Explore machine learning concepts and applications

The data science insights generated through machine learning are detailed and immediate. The process allows you to build sophisticated and efficient systems, with a huge range of applications. Everything from Netflix recommendations to self-driving cars to medical diagnostic technologies are built around machine learning algorithms.

Unsurprisingly, it is a valuable market: an estimated $7.3 billion in 2020. This is set to rise to $30.6 billion by 2024.

In this introduction to machine learning, you’ll develop the data science skills to build machine learning models using Microsoft Cognitive Services on the Azure cloud platform, and Python programming.

Discover how to become a machine learning engineer

You’ll learn the first steps of how to become a machine learning engineer. You’ll cover practical machine learning skills, with hands-on learning using Python in Microsoft Cognitive Services. With these artificial intelligence skills, you’ll be able to build your own machine learning models, forming the basis of deep learning models, as you develop further data science skills in following courses.

This machine learning and artificial intelligence course is designed for those who would like to learn more about deep learning. Basic knowledge of python programming would be advantageous, as would solid maths and computer science skills.

This machine learning and artificial intelligence course is designed for those who would like to learn more about deep learning. Basic knowledge of python programming would be advantageous, as would solid maths and computer science skills.

• Explored, prepared and cleaned data
• Applied supervised machine learning techniques
• Applied unsupervised machine learning techniques
• Modeled performance improvement