Machine Learning courses

1736 Courses

Text Analytics with Python

Learn the core techniques of text analytics and natural language processing (NLP) while discovering the cognitive science that makes it possible in this certificate Text Analytics with Python. On the practical side, you’ll learn how to actually do an analysis in Python: creating pipelines for text classification and text similarity using machine l.
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Tiny Machine Learning (TinyML)

In this exciting Professional Certificate program offered by Harvard University and Google TensorFlow, you will learn about the emerging field of Tiny Machine Learning (TinyML), its real-world applications, and the future possibilities of this transformative technology. TinyML is a cutting-edge field that brings the transformative power of machine.
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Fintech: The Future of Finance

The trend in the financial industry is clear: Technology powered financial services is the way of the future, and it is critical that finance professionals have the technology acumen to ensure your firm is not left behind. It is becoming increasingly important for organizations to understand not only the application of expansive technological adva.
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Foundations of AI

The world of Artificial Intelligence (AI) is no longer science fiction. Instead, it is rapidly permeating across all industries and impacting every aspect of our daily-life. Whether you are an industry professional, an executive, an entrepreneur or a student – developing a foundational understanding of AI and its impact on your organization and ou.
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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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AI in Practice

Start by recognizing AI’s multiple benefits and implications and end by making a plan for its application. Artificial Intelligence (AI) is like electricity must have been 140 years ago. We may not yet be able to properly imagine how it will affect our lives, but organizations need to start thinking about how AI can be applied to and improve everyd.
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AI Innovation in Healthcare

AI is transforming the landscape of healthcare by offering innovative solutions to improve diagnostics, personalize treatment plans, and streamline clinical workflows. This course from Northeastern University, available through Coursera, delves into the crucial role of AI in modern healthcare. Participants will learn how various data forms, f.
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(KK) Generative AI with Large Language Models

Coursera Dive into the fundamentals of generative AI with our comprehensive course on Large Language Models (LLMs). This program is designed to equip learners with essential knowledge to deploy generative AI in practical scenarios. Understand the lifecycle of LLM-based generative AI and the key steps involved, including data gathering, model.
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Exam Prep (NCA-GENL): NVIDIA-Certified Generative AI LLMs

The NVIDIA-Certified Generative AI LLMs - Associate Specialization is crafted for professionals in AI, machine learning, and deep learning who are eager to sharpen their skills in generative AI and large language models (LLMs). This program is designed to prepare participants to effectively design, build, optimize, and deploy generative AI sol.
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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!