Understanding Machine Learning with Python faq

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This course provides an introduction to machine learning using Python, the scikit-learn library, and the Jupyter Notebook environment. Participants will learn how to create a machine learning prediction solution.

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Free Trial

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Pluralsight

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languageLanguage:

English

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Self Paced

Course Overview

❗The content presented here is sourced directly from Pluralsight platform. For comprehensive course details, including enrollment information, simply click on the 'Go to class' link on our website.

Updated in [March 06th, 2023]

This course, Understanding Machine Learning with Python, provides an overview of the fundamentals of Machine Learning and how to use Python and the scikit-learn library to create Machine Learning solutions. Participants will learn how to format their problem to be solvable, prepare data for use in a prediction, and combine data with algorithms to create models that can predict the future. By the end of the course, participants will be able to use Python and the scikit-learn library to create Machine Learning solutions and understand how to evaluate and improve the performance of the solutions they create. Prerequisites for this course include familiarity with software development and basic statistics.

[Applications]
After completing this course, students should be able to apply their knowledge of Machine Learning with Python to create models that can predict the future. They should also be able to evaluate and improve the performance of the models they create. Additionally, they should be able to use the scikit-learn library to create Machine Learning solutions.

[Career Paths]
1. Data Scientist: Data Scientists use Machine Learning algorithms to analyze large datasets and uncover patterns and insights. They use these insights to develop predictive models and create data-driven solutions. Data Scientists are in high demand and the field is expected to continue to grow in the coming years.

2. Machine Learning Engineer: Machine Learning Engineers are responsible for designing, developing, and deploying Machine Learning models. They use a variety of programming languages and frameworks to create models that can be used in production. This is a rapidly growing field and Machine Learning Engineers are in high demand.

3. Artificial Intelligence Engineer: Artificial Intelligence Engineers are responsible for developing AI-based solutions. They use Machine Learning algorithms to create models that can be used to automate tasks and make decisions. This is a rapidly growing field and AI Engineers are in high demand.

4. Research Scientist: Research Scientists use Machine Learning algorithms to conduct research and develop new algorithms. They use their knowledge of Machine Learning to create new models and algorithms that can be used to solve complex problems. This is a highly specialized field and Research Scientists are in high demand.

[Education Paths]
1. Bachelor's Degree in Computer Science: A Bachelor's Degree in Computer Science is a great way to gain a comprehensive understanding of the fundamentals of computer science and machine learning. This degree will provide you with the skills and knowledge necessary to develop and implement machine learning algorithms. Additionally, you will learn about the latest trends in the field, such as artificial intelligence and deep learning.

2. Master's Degree in Artificial Intelligence: A Master's Degree in Artificial Intelligence is a great way to gain a deeper understanding of the principles of machine learning and artificial intelligence. This degree will provide you with the skills and knowledge necessary to develop and implement advanced machine learning algorithms. Additionally, you will learn about the latest trends in the field, such as natural language processing and computer vision.

3. Doctorate in Machine Learning: A Doctorate in Machine Learning is a great way to gain a comprehensive understanding of the principles of machine learning and artificial intelligence. This degree will provide you with the skills and knowledge necessary to develop and implement advanced machine learning algorithms. Additionally, you will learn about the latest trends in the field, such as reinforcement learning and generative adversarial networks.

4. Certificate in Data Science: A Certificate in Data Science is a great way to gain a comprehensive understanding of the fundamentals of data science and machine learning. This certificate will provide you with the skills and knowledge necessary to develop and implement machine learning algorithms. Additionally, you will learn about the latest trends in the field, such as big data and predictive analytics.

Course Provider

Provider Pluralsight's Stats at AZClass

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Pluralsight ranked 20th on the Forbes Cloud 100 list of the top 100 private cloud companies in the world.
Pluralsight Ranked on the Best Workplaces for Women List for the second consecutive year.
AZ Class hope that this free trial Pluralsight course can help your Machine Learning skills no matter in career or in further education. Even if you are only slightly interested, you can take Understanding Machine Learning with Python course with confidence!

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