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Machine Learning courses

1795 Courses

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California Institute of Technology Harvard University

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.
provider edX
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California Institute of Technology ESSEC Business School

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.
provider Coursera
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California Institute of Technology Northeastern University

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.
provider Coursera
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California Institute of Technology Coursera

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.
provider Coursera
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California Institute of Technology Coursera

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.
provider Coursera
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California Institute of Technology Coursera

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.
provider Coursera
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California Institute of Technology Coursera

Building AI Agents: Automation and NLP Foundations

Hey there, AI enthusiasts, tech trailblazers, and future-focused pros! Are you ready to explore the world of AI Agents and unleash the power of artificial intelligence? Buckle up for a deep dive into the cutting-edge tools and techniques transforming industries – and yes, your projects and workflows too! Why AI Agents? Did you know that by 2026, AI.
provider Coursera
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California Institute of Technology Coursera

AI ML with Deep Learning and Supervised Models

This comprehensive AI ML with Deep Learning and Supervised Models specialization equips you with the skills to excel in roles across AI, machine learning, and deep learning. Through in-depth modules, you'll master regression, classification, clustering, neural networks, and advanced AI frameworks to solve real-world challenges. By the end of this c.
provider Coursera
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California Institute of Technology Coursera

Preparing for Google Cloud Certification: Machine Learning Engineer

87% of Google Cloud certified users feel more confident in their cloud skills. This program provides the skills you need to advance your career and provides training to support your preparation for the industry-recognized Google Cloud Professional Machine Learning Engineer certification. Here's what you have to do: 1) Complete the Preparing for Goo.
provider Coursera
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California Institute of Technology AWS Skill Builder

Amazon QuickSight Advanced Business Intelligence Authoring (Part 2) (Español LATAM)

Después del 28 de marzo, los títulos de los cursos solo estarán disponibles en inglés. Sin embargo, las descripciones de los cursos permanecerán disponibles en su idioma preferido para que pueda consultarlas.
provider AWS Skill Builder

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!