Practical Machine Learning faq

star-rating
3.5
learnersLearners: 1,229
instructor Instructor: Jeff Leek instructor-icon
duration Duration: duration-icon

Data scientists and data analysts can benefit from this course on Practical Machine Learning. It covers the basics of building and applying prediction functions, with an emphasis on practical applications. Topics include training and test sets, overfitting, error rates, and a range of model-based and algorithmic machine learning methods. Learn how to collect data, create features, apply algorithms, and evaluate results. Get the skills you need to make accurate predictions.

ADVERTISEMENT

Course Feature Course Overview Course Provider Discussion and Reviews
Go to class

Course Feature

costCost:

Free

providerProvider:

Coursera

certificateCertificate:

Paid Certification

languageLanguage:

English

start dateStart Date:

21st Aug, 2023

Course Overview

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

Updated in [June 30th, 2023]

This course provides an overview of practical machine learning. Students will learn the basics of building and applying prediction functions, with an emphasis on practical applications. Topics covered include training and test sets, overfitting, error rates, model-based and algorithmic machine learning methods such as regression, classification trees, Naive Bayes, and random forests. The course will also cover the complete process of building prediction functions, from data collection and feature creation to algorithms and evaluation. By the end of the course, students will have a better understanding of the fundamentals of machine learning and be able to apply them to real-world problems.

[Applications]
The application of this course can be seen in a variety of fields. It can be used to create predictive models for marketing, finance, healthcare, and other industries. It can also be used to create models for predicting customer behavior, predicting stock prices, and predicting disease outbreaks. Additionally, the course can be used to create models for natural language processing, image recognition, and other machine learning tasks. Finally, the course can be used to create models for autonomous vehicles, robotics, and other applications.

[Career Path]
The career path recommended to learners of this course is that of a Machine Learning Engineer. A Machine Learning Engineer is responsible for developing and deploying machine learning models and algorithms to solve real-world problems. They are responsible for designing, building, and maintaining machine learning systems, as well as for developing and testing new algorithms. They must be able to work with large datasets and have a strong understanding of the underlying mathematics and statistics.

The development trend for Machine Learning Engineers is very positive. As the demand for data-driven decision making increases, so does the need for Machine Learning Engineers. Companies are increasingly looking for Machine Learning Engineers to help them make better decisions and to automate processes. Additionally, the development of new technologies such as artificial intelligence and deep learning are creating new opportunities for Machine Learning Engineers.

[Education Path]
The recommended educational path for learners interested in Practical Machine Learning is a Bachelor's degree in Computer Science or a related field. This degree will provide a strong foundation in the fundamentals of computer science, including programming, data structures, algorithms, and software engineering. Additionally, the degree will provide a comprehensive overview of machine learning, including supervised and unsupervised learning, deep learning, and reinforcement learning.

The development trend for this degree is to focus on the practical application of machine learning. This includes the use of machine learning to solve real-world problems, such as predicting customer behavior, analyzing medical data, and forecasting stock prices. Additionally, the degree will focus on the development of new algorithms and techniques to improve the accuracy and efficiency of machine learning models. Finally, the degree will emphasize the use of big data and cloud computing to enable the development of more powerful machine learning models.

Course Provider

Provider Coursera's Stats at AZClass

Discussion and Reviews

0.0   (Based on 0 reviews)

Start your review of Practical Machine Learning

faq FAQ for Machine Learning Courses

Q1: Does the course offer certificates upon completion?

Yes, this course offers a free certificate. AZ Class have already checked the course certification options for you. Access the class for more details.

Q2: How do I contact your customer support team for more information?

If you have questions about the course content or need help, you can contact us through "Contact Us" at the bottom of the page.

Q3: Can I take this course for free?

Yes, this is a free course offered by Coursera, please click the "go to class" button to access more details.

Q4: How many people have enrolled in this course?

So far, a total of 1229 people have participated in this course. The duration of this course is hour(s). Please arrange it according to your own time.

Q5: How Do I Enroll in This Course?

Click the"Go to class" button, then you will arrive at the course detail page.
Watch the video preview to understand the course content.
(Please note that the following steps should be performed on Coursera's official site.)
Find the course description and syllabus for detailed information.
Explore teacher profiles and student reviews.
Add your desired course to your cart.
If you don't have an account yet, sign up while in the cart, and you can start the course immediately.
Once in the cart, select the course you want and click "Enroll."
Coursera may offer a Personal Plan subscription option as well. If the course is part of a subscription, you'll find the option to enroll in the subscription on the course landing page.
If you're looking for additional Machine Learning courses and certifications, our extensive collection at azclass.net will help you.

close

To provide you with the best possible user experience, we use cookies. By clicking 'accept', you consent to the use of cookies in accordance with our Privacy Policy.