Demystifying Machine Learning- An Overview for Non-Technical

Demystifying Machine Learning: An Overview for Non-Technical, available at $54.99, has an average rating of 4.67, with 9 lectures, based on 3 reviews, and has 6 subscribers.

You will learn about A clear understanding of what machine learning is and how it differs from other forms of artificial intelligence Practical examples of how machine learning is used in real-world applications, including business and industry An overview of the different types of machine learning algorithms, and how they are used to solve different problems Insight into the benefits and limitations of machine learning, and how it can be used to inform decision-making in a range of fields The ability to confidently communicate about machine learning concepts with technical professionals and stakeholders. This course is ideal for individuals who are Non-technical professionals interested in learning about machine learning and its potential applications in their field or Managers, executives, and decision-makers looking to gain a basic understanding of machine learning to inform strategic decisions or Entrepreneurs and business owners seeking to leverage machine learning for their products or services or Marketing, sales, and customer service professionals looking to understand how machine learning can be used to improve customer experiences or Anyone who wants to demystify machine learning and learn how it can be applied in their industry or field of interest. It is particularly useful for Non-technical professionals interested in learning about machine learning and its potential applications in their field or Managers, executives, and decision-makers looking to gain a basic understanding of machine learning to inform strategic decisions or Entrepreneurs and business owners seeking to leverage machine learning for their products or services or Marketing, sales, and customer service professionals looking to understand how machine learning can be used to improve customer experiences or Anyone who wants to demystify machine learning and learn how it can be applied in their industry or field of interest.

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Summary

Title: Demystifying Machine Learning: An Overview for Non-Technical

Price: $54.99

Average Rating: 4.67

Number of Lectures: 9

Number of Published Lectures: 9

Number of Curriculum Items: 9

Number of Published Curriculum Objects: 9

Original Price: $19.99

Quality Status: approved

Status: Live

What You Will Learn

A clear understanding of what machine learning is and how it differs from other forms of artificial intelligence

Practical examples of how machine learning is used in real-world applications, including business and industry

An overview of the different types of machine learning algorithms, and how they are used to solve different problems

Insight into the benefits and limitations of machine learning, and how it can be used to inform decision-making in a range of fields

The ability to confidently communicate about machine learning concepts with technical professionals and stakeholders.

Who Should Attend

Non-technical professionals interested in learning about machine learning and its potential applications in their field

Managers, executives, and decision-makers looking to gain a basic understanding of machine learning to inform strategic decisions

Entrepreneurs and business owners seeking to leverage machine learning for their products or services

Marketing, sales, and customer service professionals looking to understand how machine learning can be used to improve customer experiences

Anyone who wants to demystify machine learning and learn how it can be applied in their industry or field of interest.

Target Audiences

Non-technical professionals interested in learning about machine learning and its potential applications in their field

Managers, executives, and decision-makers looking to gain a basic understanding of machine learning to inform strategic decisions

Entrepreneurs and business owners seeking to leverage machine learning for their products or services

Marketing, sales, and customer service professionals looking to understand how machine learning can be used to improve customer experiences

Anyone who wants to demystify machine learning and learn how it can be applied in their industry or field of interest.

Machine learning is a powerful technology that is driving innovation across a wide range of industries, from finance and healthcare to retail and manufacturing. However, for non-technical professionals, the concept of machine learning can seem daunting and difficult to understand. This course is designed to provide a clear and concise overview of machine learning for non-technical professionals, allowing you to gain a solid understanding of this complex topic.

Throughout the course, you will learn about the different types of machine learning algorithms, how they work, and what they can be used for. You will explore common applications of machine learning, such as image recognition, natural language processing, and predictive analytics.

The course is structured in a way that is easy to follow and engaging, with a mix of video lectures and real-world examples.

Upon completion of the course, you will have a solid understanding of machine learning and its applications, and you will be better equipped to work with technical professionals on machine learning projects. You will also have a better understanding of the ethical considerations surrounding machine learning, and how to navigate these issues in your work. Whether you are a business professional, a marketer, or a manager, this course will provide you with the knowledge and skills you need to succeed in the era of machine learning.

Course Curriculum

Chapter 1: Introduction & Agenda

Lecture 1: Introduction & Agenda

Chapter 2: I. Introduction to Machine Learning

Lecture 1: I. Introduction to Machine Learning

Chapter 3: II. Data Preparation

Lecture 1: II. Data Preparation

Chapter 4: III. Supervised Learning

Lecture 1: III. Supervised Learning

Chapter 5: IV. Unsupervised Learning

Lecture 1: IV. Unsupervised Learning

Chapter 6: V. Decision Systems

Lecture 1: V. Decision Systems

Chapter 7: VI. Evaluation and Model Selection

Lecture 1: VI. Evaluation and Model Selection

Chapter 8: VII. Deployment and Maintenance

Lecture 1: VII. Deployment and Maintenance

Chapter 9: VIII. Conclusion

Lecture 1: VIII. Conclusion

Instructors

David Landaeta
Technogical Savvy

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4 stars: 1 votes

5 stars: 2 votes

Frequently Asked Questions

How long do I have access to the course materials?

You can view and review the lecture materials indefinitely, like an on-demand channel.

Can I take my courses with me wherever I go?

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