Data Processing and Feature Engineering with MATLAB faq

star-rating
4.5
learnersLearners: 2,236
instructor Instructor: / instructor-icon
duration Duration: duration-icon

This intermediate-level course combines data from multiple sources and times to lay the foundation for predictive modeling. MATLAB is used to process and engineer features, providing a useful tool for anyone interested in data analysis.

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Course Feature Course Overview Pros & Cons Course Provider Discussion and Reviews
Go to class

Course Feature

costCost:

Free

providerProvider:

Coursera

certificateCertificate:

Paid Certification

languageLanguage:

English

start dateStart Date:

15th May, 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 [March 06th, 2023]

Data Processing and Feature Engineering with MATLAB is an intermediate-level course designed to help those with domain knowledge and some exposure to computational tools, but no programming background, build on the skills learned in Exploratory Data Analysis with MATLAB. Through this course, participants will learn how to merge data from different data sets, handle common scenarios such as missing data, and explore special techniques for handling textual, audio, and image data. By the end of the course, participants will be able to visualize their data, clean it up and arrange it for analysis, and identify the qualities necessary to answer their questions.

[Applications]
Upon completion of this course, participants will be able to apply the skills learned to combine data from multiple sources, handle missing data, and explore special techniques for handling textual, audio, and image data. They will be able to visualize their data, clean it up and arrange it for analysis, and identify the qualities necessary to answer their questions. Participants will also be able to visualize the distribution of their data and use visual inspection to address artifacts that affect accurate modeling.

[Career Paths]
1. Data Scientist: Data Scientists are responsible for analyzing large amounts of data and developing predictive models to help organizations make better decisions. They use a variety of tools and techniques, including MATLAB, to explore and analyze data, identify patterns, and develop models. Data Scientists are in high demand as organizations increasingly rely on data-driven decision making.

2. Data Analyst: Data Analysts are responsible for collecting, organizing, and analyzing data to help organizations make informed decisions. They use MATLAB to explore and analyze data, identify patterns, and develop insights. Data Analysts are in high demand as organizations increasingly rely on data-driven decision making.

3. Machine Learning Engineer: Machine Learning Engineers are responsible for developing and deploying machine learning models to solve real-world problems. They use MATLAB to explore and analyze data, identify patterns, and develop models. Machine Learning Engineers are in high demand as organizations increasingly rely on data-driven decision making.

4. Data Engineer: Data Engineers are responsible for designing, building, and maintaining data pipelines and data warehouses. They use MATLAB to explore and analyze data, identify patterns, and develop models. Data Engineers are in high demand as organizations increasingly rely on data-driven decision making.

[Education Paths]
1. Bachelor of Science in Data Science: This degree program provides students with the skills and knowledge to analyze and interpret data, develop predictive models, and create data-driven solutions. Students will learn the fundamentals of data science, including data mining, machine learning, and artificial intelligence. They will also gain experience in programming languages such as Python, R, and MATLAB. This degree is becoming increasingly popular as businesses and organizations rely more heavily on data-driven decision making.

2. Master of Science in Data Science: This degree program builds on the skills and knowledge acquired in a Bachelor of Science in Data Science. Students will learn more advanced techniques for data analysis, such as natural language processing, deep learning, and big data analytics. They will also gain experience in more advanced programming languages such as Java and Scala. This degree is ideal for those who want to pursue a career in data science or research.

3. Doctor of Philosophy in Data Science: This degree program is designed for those who want to pursue a career in research or academia. Students will learn advanced techniques for data analysis, such as Bayesian inference, statistical modeling, and machine learning. They will also gain experience in programming languages such as Python, R, and MATLAB. This degree is ideal for those who want to pursue a career in data science research or teaching.

4. Certificate in Data Science: This certificate program provides students with the skills and knowledge to analyze and interpret data, develop predictive models, and create data-driven solutions. Students will learn the fundamentals of data science, including data mining, machine learning, and artificial intelligence. They will also gain experience in programming languages such as Python, R, and MATLAB. This certificate is ideal for those who want to gain a basic understanding of data science and its applications.

Pros & Cons

Pros Cons
  • pros

    Topnotch content and delivery

  • pros

    Practicals, quizzes and exams

  • pros

    Variety of data type

  • pros

    Unique programming mindset and skills

  • pros

    Advanced uses of Live Editor & Machine Learning apps

  • pros

    Clear and concise manner

  • pros

    Hands on experience

  • cons

    Week 5 was too rushed

  • cons

    Fast pace

  • cons

    Not enough interactive assignments

  • cons

    Difficult to follow

  • cons

    Video lectures not in depth

Course Provider

Provider Coursera's Stats at AZClass

This intermediate course combines data from multiple sources and time to provide a foundation for predictive modeling. MATLAB is used to process and design features, providing a useful tool for anyone interested in data analysis. In this course, you'll build on the skills you learn in MATLAB Exploratory Data Analysis to build on the foundation for predictive modeling. This intermediate course is useful for anyone who needs to combine data from multiple sources or time and is interested in modeling. These skills are valuable for those who have domain knowledge and exposure to some computing tools but no programming background.

Discussion and Reviews

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faq FAQ for Matlab Courses

Q1: What topics are covered in the Data Processing and Feature Engineering with MATLAB course?

This course covers a range of topics related to data processing, feature engineering, data analysis, data visualization, machine learning, programming, and algorithms using MATLAB. You will learn how to use MATLAB to process data, extract features, visualize data, and develop algorithms for machine learning applications. You will also gain an understanding of the fundamentals of programming and algorithms.

Q2: What skills will I gain from taking the Data Processing and Feature Engineering with MATLAB course?

By taking this course, you will gain a range of skills related to data processing, feature engineering, data analysis, data visualization, machine learning, programming, and algorithms. You will learn how to use MATLAB to process data, extract features, visualize data, and develop algorithms for machine learning applications. You will also gain an understanding of the fundamentals of programming and algorithms.

Q3: 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.

Q4: 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.

Q5: 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.

Q6: How many people have enrolled in this course?

So far, a total of 2236 people have participated in this course. The duration of this course is hour(s). Please arrange it according to your own time.

Q7: How Do I Enroll in This Course?

Click the"Go to class" button, then you will arrive at the course detail page.
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(Please note that the following steps should be performed on Coursera's official site.)
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Add your desired course to your cart.
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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 Matlab courses and certifications, our extensive collection at azclass.net will help you.

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