Why take a course in Machine Learning and how it is structured

Machine Learning (or machine learning) is a subfield of Artificial Intelligence, defined as the ability of a machine to mimic intelligent human behavior. Artificial intelligence systems are therefore being used to perform complex tasks in a way similar to how humans solve problems.

Currently, ML is used in numerous areas of daily life: from social media to online banking to e-commerce.

The Machine Learning Engineer, the programmer who specializes in managing Machine Learning projects, is thus an increasingly sought-after figure who is responsible for:

• Support the team in finding and analyzing the data needed to develop a Machine Learning model;
• Develop the Machine Learning model, based on the analysis performed;
• Monitor the flow of data;
• intervene if drops in performance occur.

How to become a Machine Learning Engineer

Typically, the Machine Learning Engineer is a graduate student in Computer Science, Mathematics, or Computer Engineering, who has then advanced to a course in Machine Learning.

Machine Learning courses are intended both for programmers and Web developers, intent on becoming Machine Learning Engineers, and for professionals from different fields who want to deepen and broaden their knowledge.

The course enables you to learn the basic principles of Artificial Intelligence and Machine Learning, and thus the set of techniques, models and algorithms by which machines learn to perform a task autonomously.

Typically, a Machine Learning course is structured into different chapters:

• data acquisition;
• descriptive analysis to filter, group, and transform data;
• processing, to pre-process the data in order to run the Machine Learning model;
• Execution of supervised and unsupervised classification algorithms.

Phyd provides its users with numerous
courses
in Machine Learning. By attending them, the user will learn about the different types of problems that Machine Learning can solve, through examples of concrete applications. Not only that, he will also understand the difference between regression and classification problems, and learn the techniques of constructing the main algorithms.

Why choose an online Machine Learning course

Machine learning is critical for companies because it enables them to predict how consumers will behave. Many of today’s leading brands, such as Facebook, Google and Uber, make machine learning a central part of their operations, and a differentiator.

There are numerous areas in which Machine Learning finds application:

• production: predictive maintenance;
• Retail: upselling and cross-channel marketing;
• healthcare: precision medicine;
• Travel and hospitality: price dynamism;
• Financial services: risk analysis and regulation;
• Energy: optimization of energy supply and demand.

With every field seeking to apply Artificial Intelligence to its advantage, the study of machine learning opens up numerous job outlets. There are more and more Machine Learning companies looking for engineers, and the need for specialized figures is growing. Every customer-oriented company is looking to adopt machine learning technology, and this, especially for IT professionals, translates into additional opportunities for specialization.

In addition, Machine Learning is closely related to Data Science. Pursuing a career in machine learning therefore allows one to work as a Machine Learning Engineer or as a Data Science Specialist. Becoming competent in both fields makes candidates coveted by companies, even the largest ones.