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Machine Learning courses

1795 Courses

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California Institute of Technology

Generative AI For Business Leaders

Ideal for those without an analytics or data background, you’ll get a foundational understanding of how the technology works and how to use it to meet business objectives. By the end of this course you’ll be able to weigh the benefits of AI and gAI, as well as understand the limitations, tradeoffs, and legal and ethical implications.
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California Institute of Technology

Distributed Computing & AI with Spark

You’ll get hands-on experience in building, training, and customizing models using TensorFlow and Keras. Starting from implementing simple networks by hand, this course builds to making use of advanced pre-trained models with transfer learning. You’ll complete a practical mini-project on image classification, with the help of guidance during office.
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California Institute of Technology Coursera

Introduction to AI and Machine Learning

Welcome to the Introduction to AI and Machine Learning Course! This course is the first course of the 3 courses specialization - AWS Certified AI Practitioner. A journey into the world of Artificial Intelligence (AI) and Machine Learning (ML) with AWS begins with this course. This is perfect start whether you are a beginner or want to brush up on y.
provider Coursera
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California Institute of Technology XuetangX

Big data analytics and smart rehabilitation

Course BackgroundBig data analysis and smart rehabilitation have become key trends in modern rehabilitation medicine. By leveraging advanced computing technologies, artificial intelligence (AI) algorithms, and Internet of Things (IoT) devices, healthcare professionals can assess patients’ functional status more accurately, optimize rehabilita.
provider XuetangX
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California Institute of Technology Coursera

Generative AI in Finance

Course Description: This course provides a comprehensive exploration of Generative AI and its transformative impact on the financial sector. Learners will delve into foundational concepts, key AI models, and their applications across financial analysis, decision-making, forecasting, and compliance. With a focus on real-world case studies and hands-.
provider Coursera
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California Institute of Technology edX

Azure AI Services: Core applications

"Core Applications of Azure AI Services" is an introductory course designed to familiarize users with the practical application of Microsoft's Azure AI services in various real-world scenarios. It aims to bridge the gap between theoretical AI concepts and their actual implementation. You will learn how Azure AI services are utilized to solve real-.
provider edX
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California Institute of Technology CodeSignal

Q-Learning Unleashed: Building Intelligent Agents

In this course, we focus on building a Q-learning agent step by step. We start with the Bellman equation and the Q-table update, then implement a basic Q-learning function. Next, we incorporate an exploration policy (ε-greedy), and finally we demonstrate how to use the learned Q-table for decision making.
provider CodeSignal
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California Institute of Technology Coursera

AWS AI Practitioner

The AWS Certified AI Practitioner Specialization is meant for those who desire to establish a solid base in Artificial Intelligence (AI) and Machine Learning (ML) and have the ability to utilize AWS cloud services. This specialization is aligned with the AWS AI Practitioner Certification exam and offers a broad understanding of AI concepts, generat.
provider Coursera
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California Institute of Technology Pluralsight

AIOps: CI/CD for AI Systems

DevOps is a concept that has been around a long time and has been applied to ML and, recently, LLMs. In this course, AIOps: CI/CD for AI Systems, you’ll learn to apply CI/CD, a fundamental concept of DevOps, to ML, AI, and LLMs. First, you’ll explore how CI/CD pipelines work with ML models. Next, you’ll discover how to deploy to cloud environments.
provider Pluralsight
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California Institute of Technology Pluralsight

AWS Certified Machine Learning Engineer - Associate (MLA-C01): ML Model Development

AWS has a broad range of machine learning services to help businesses approach complex problems. In this course, AWS Certified Machine Learning Engineer - Associate (MLA-C01): ML Model Development, you’ll learn to navigate these services and select the approach that is most appropriate for your machine learning (ML) solutions. First, you’ll explore.
provider Pluralsight

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!