Machine Learning courses

1736 Courses

Operationalizing ML Models: MLOps for Scalable AI

In this course you’ll explore how to turn promising ML prototypes into robust, scalable, and maintainable systems that deliver real value. Through hands-on demos, practical tools, and real-world case studies from companies like Netflix, Uber, and Google, you’ll gain a comprehensive understanding of what it takes to run ML systems effectively in pro.
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GenAI for Risk Managers: Advanced Risk Analysis Techniques

In this course, you’ll discover how Generative AI can enhance risk detection, automate monitoring, and improve decision-making. Through hands-on projects and real-world case studies, you’ll gain practical expertise to apply AI-driven strategies in complex risk environments. Whether you’re a risk professional or business leader, this course will equ.
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GenAI for Financial Analysts: Essential Predictive Analytics

In this course, you will take on a practical journey into how GenAI transforms financial forecasting, portfolio optimization, risk management, and reporting automation. You’ll explore how top institutions like investment banks, hedge funds, and fintech innovators are already integrating GenAI into their workflows—and you’ll gain the hands-on skills.
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Responsible AI for Mental Health

Unlock the future of AI-driven mental health care while tackling the critical ethical challenges shaping the field today. From bias and misinformation to privacy and patient safety, this course dives into the complexities of AI’s role in mental health. Explore cutting-edge advancements in computing and social robotics, and compare basic and advance.
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Advancing Dairy Management with Artificial Intelligence

By completing this course, you will gain a solid understanding of the basics of AI and its role in dairy systems. You will learn to identify key data types used in dairy analytics, such as production, health, and nutrition data. Additionally, you will explore AI applications in various aspects of dairy systems and discuss current AI applications in.
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Data Science and Machine Learning

Have you thought about a career in data science and machine learning but didn’t know where to start? Demand for professionals in the machine learning (ML) and artificial intelligence (AI) space is growing exponentially, with no signs of slowing thanks to the ever changing data science landscape. In fact, as the availability of machine learning too.
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Python for Data Science and Machine Learning

Have you thought about a career in data science and machine learning but didn’t know where to start? Demand for professionals in the machine learning (ML) and artificial intelligence (AI) space is growing exponentially, with no signs of slowing thanks to the ever changing data science landscape. In fact, as the availability of machine learning too.
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Machine Learning on Google Cloud

What is machine learning, and what kinds of problems can it solve? How can you build, train, and deploy machine learning models at scale without writing a single line of code? When should you use automated machine learning or custom training? This course teaches you how to build Vertex AI AutoML models without writing a single line of code; build B.
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Artificial Intelligence & Machine Learning in Healthcare

In this two-course MicroMasters program, you will learn how Artificial Intelligence (AI) and Machine Learning (ML) can be used to improve healthcare. In the first self-paced course, you’ll build a solid foundation in AI and ML fundamentals, learning how these technologies can enhance both clinical and operational decision-making. You’ll also learn.
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Automating with AI/ML for Small Business Owners

This course was developed by members of AWS Technical Field Communities (TFC), an AWS community of technical experts. The content is intended to complement our standard training curriculum and augment your AWS learning journey.This course provides small business owners with a high-level overview of generative artificial intelligence (AI). Learners.
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More and more products are now being developed using artificial intelligence. To avoid being left on the sidelines of progress, managers must understand how the robot’s “brains” work

Artificial intelligence (AI) and machine learning technologies have been used for many years, but now the intensity of their use has increased significantly. For example, machine learning is being actively implemented in telecommunications, retail, marketing and e-commerce. But many still do not fully understand what it is.

Machine learning involves the system processing a large number of examples, during which it identifies patterns and uses them to predict the characteristics of new data. In other words, this is the process of giving AI ml courses “consciousness”, the ability to remember and analyze.

Machine learning use cases

The use of machine learning has touched many areas in our lives. Let's look at the most striking examples of the use of computer intelligence:

Facial recognition in the subway will help identify violators or criminals in a huge mass of people. Ordinary observers cannot cope with this task. But a fast-learning machine will do this job without any problems.

What do you need for machine learning (ML)?

For those interested in training, there are several requirements to be met in order to be successful in this field. So, there are the main points you need to know about the machine learning course. These requirements include:

  1. Basic knowledge of programming languages such as Python, R, Java, JavaScript, etc.

  2. Average knowledge of statistics and probability.

  3. Basic knowledge of linear algebra in the ml course. In a linear regression model, a line is drawn through all the data points, and that line is used to calculate new values.

  4. Understanding Calculus.

  5. Knowledge of how to clean and structure raw data into the desired format to reduce the time required for decision making.

Machine learning courses from AI Eeducation are the best choice!