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Maria Gavilan-Alfonso,
Heather Gorr,
Michael Reardon,
Erin Byrne,
Brandon Armstrong,
Nikola Trica,
Cris LaPierre,
and
Adam Filion
In this course, you will learn to think like a data scientist and ask questions of your data. You will use interactive features in MATLAB to extract subsets of data and to compute statistics on groups of related data. You will learn to use MATLAB to automatically generate code so you can learn syntax as you explore. You will also use interactive documents, called live scripts, to capture the steps of your analysis, communicate the results, and provide interactive controls allowing others to experiment by selecting groups of data.
Read more
In this course, you will learn to think like a data scientist and ask questions of your data. You will use interactive features in MATLAB to extract subsets of data and to compute statistics on groups of related data. You will learn to use MATLAB to automatically generate code so you can learn syntax as you explore. You will also use interactive documents, called live scripts, to capture the steps of your analysis, communicate the results, and provide interactive controls allowing others to experiment by selecting groups of data.
Read more
In this course, you will learn to think like a data scientist and ask questions of your data. You will use interactive features in MATLAB to extract subsets of data and to compute statistics on groups of related data. You will learn to use MATLAB to automatically generate code so you can learn syntax as you explore. You will also use interactive documents, called live scripts, to capture the steps of your analysis, communicate the results, and provide interactive controls allowing others to experiment by selecting groups of data.
These skills are valuable for those who have domain knowledge and some exposure to computational tools, but no programming background is required. To be successful in this course, you should have some knowledge of basic statistics (e.g., histograms, averages, standard deviation, curve fitting, interpolation).
By the end of this course, you will be able to load data into MATLAB, prepare it for analysis, visualize it, perform basic computations, and communicate your results to others. In your last assignment, you will combine these skills to assess damages following a severe weather event and communicate a polished recommendation based on your analysis of the data. You will be able to visualize the location of these events on a geographic map and create sliding controls allowing you to quickly visualize how a phenomenon changes over time.
Register for this course and see more details by visiting:
OpenCourser.com/course/d0zjkl/exploratory
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What's inside
Syllabus
Introduction to the Data Science Workflow
In this module you’ll learn about the key steps in a data science workflow and begin exploring a data set using a script provided for you. As you work with the file, take note of the different elements in the script. As you progress through the course, you’ll create a similar script yourself.
Read more
Syllabus
Introduction to the Data Science Workflow
In this module you’ll learn about the key steps in a data science workflow and begin exploring a data set using a script provided for you. As you work with the file, take note of the different elements in the script. As you progress through the course, you’ll create a similar script yourself.
Read more
Importing Data
In this module you’ll import data into MATLAB, customize the import options, and generate code to automate the process. You’ll also work with different types of data, such as numeric, dates, and text.
Visualizing and Filtering Data
In this module you’ll create visualizations and learn how to customize figures. You’ll also filter your data to select only what is needed for your analysis. You’ll create new tables and save them to use in the future or share with others outside of MATLAB.
Performing Calculations
In this module you’ll write small pieces of code to extend your analysis. You’ll calculate summary statistics on groups of data and determine if variables are correlated. You’ll extend your ability to filter data to defining conditions across multiple variables. You’ll also modify categorical data to remove, combine, or create new categories to use for defining groups.
Documenting Your Work
In this module you’ll create live scripts with interactive controls. Then you’ll create your own analysis of a weather event to submit as a peer-reviewed assignment.
Good to know
Good to know
Know what's good ,
what to watch for , and
possible dealbreakers
Reinforces foundational knowledge and skills in statistics for learners who are new to data science
Provides exposure to MATLAB, a widely used tool in data science and industry
Teaches learners to automate code, making data analysis more efficient and reproducible
Instructs learners to document their work using live scripts, enhancing communication and collaboration
Capstone project allows learners to apply their skills to a real-world data analysis task, fostering practical application
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Save Exploratory Data Analysis with MATLAB to your list so you can find it easily later:
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Reviews summary
Matlab skills for data analysis
Learners say this course largely positive is a helpful introduction to exploratory data analysis with MATLAB. Engaging assignments and detailed explanations are praised, though some students wish there were more graded assignments and more comprehensive information on programming in MATLAB. According to students, this course is useful for beginners with no prior MATLAB experience. They also say that students may want to do the free MathWorks MATLAB Onramp course beforehand to gain a little bit of background knowledge.
Course is moderately challenging
"It is clear,concise and highly polished content.For a beginner, the quizzes and assignments are moderately challenging so by the time you reach the solution you have re-watched the videos,gone through the discussion forum ,read some MATLAB documentation and tried a couple of ways of doing things."
Course is suitable for beginners with little to no MATLAB experience
"This course has an amazing accompaniment, all the weeks have the correct and enough information to learn a lot of data treatment in MATLAB"
"This course is amazing with very learned and professional teachers and some useful course contents."
Covers basics of data analysis using MATLAB
"Clear and to the point. Polished presentation that packs alot of info into each lesson."
"This course describes in detail how data should be analyzed and interpreted in such a way, so that you can gain useful insights about various types of phenomena."
Assignments help reinforce concepts learned in the videos
"Quizzes are well planned to test the leanings."
"This course is amazing with very learned and professional teachers and some useful course contents."
Instructors are helpful and knowledgeable
"The course provided a lot of insight into data and data science. The instructors were explicit and straight to the point."
"This is the best course that I've taken not only in Coursera, but also in my whole life!! This course is very interactive. You'll never get bored."
Peer-review assignment is subjective
"It is rather unfair to anyone who is eager to learn to have to wait endlessly till more people enroll and submit their assessment. I suggest that this be looked into."
Activities
Be better prepared
before
your course. Deepen your understanding
during
and
after
it. Supplement your coursework and achieve mastery of the topics covered
in Exploratory Data Analysis with MATLAB with these
activities:
Review Data Science Concepts
Show steps
Sharpen your data science skills by reviewing core concepts such as histograms, averages, and curve fitting.
Browse courses on
Data Science Concepts
Show steps
-
Go through your existing notes or textbooks.
-
Take practice quizzes or solve sample problems.
Organize Course Materials
Show steps
Keep your course materials organized and easily accessible for future reference.
Show steps
-
Create a dedicated study space or folder for the course.
-
Organize your notes, assignments, and other materials.
-
Review and update your materials regularly.
Form a Study Group
Show steps
Collaborate with classmates to discuss course material, share insights, and work on problems together.
Show steps
-
Identify classmates with similar interests or backgrounds.
-
Set up regular meeting times and locations.
-
Establish group norms and expectations.
Four other activities
Expand to see all activities and additional details
Show all seven activities
Practice MATLAB Coding
Show steps
Reinforce your understanding of MATLAB syntax and programming concepts through regular practice exercises.
Show steps
-
Solve coding challenges or practice problems.
-
Follow along with online tutorials or guided exercises.
Contribute to the MATLAB Community
Show steps
Gain practical experience and give back to the MATLAB community by reporting bugs or contributing code.
Show steps
-
Identify areas in MATLAB where you can make a contribution.
-
Follow community guidelines and best practices.
-
Submit your contributions through the appropriate channels.
Develop a MATLAB Project
Show steps
Apply your MATLAB skills to solve a real-world problem or create a visualization tool.
Show steps
-
Identify a problem or opportunity to address.
-
Design and develop your project.
-
Present your findings or share your project with others.
Participate in MATLAB Challenges
Show steps
Challenge yourself and showcase your skills by participating in MATLAB competitions and hackathons.
Show steps
-
Find relevant competitions or hackathons.
-
Register and form a team (if necessary).
-
Develop and submit your solution.
Review Data Science Concepts
Show steps
Sharpen your data science skills by reviewing core concepts such as histograms, averages, and curve fitting.
Browse courses on
Data Science Concepts
Show steps
Show steps
Show steps
- Go through your existing notes or textbooks.
- Take practice quizzes or solve sample problems.
Organize Course Materials
Show steps
Keep your course materials organized and easily accessible for future reference.
Show steps
Show steps
Show steps
- Create a dedicated study space or folder for the course.
- Organize your notes, assignments, and other materials.
- Review and update your materials regularly.
Form a Study Group
Show steps
Collaborate with classmates to discuss course material, share insights, and work on problems together.
Show steps
Show steps
Show steps
- Identify classmates with similar interests or backgrounds.
- Set up regular meeting times and locations.
- Establish group norms and expectations.
Four other activities
Expand to see all activities and additional details
Show all seven activities
Practice MATLAB Coding
Show steps
Reinforce your understanding of MATLAB syntax and programming concepts through regular practice exercises.
Show steps
Show steps
Show steps
- Solve coding challenges or practice problems.
- Follow along with online tutorials or guided exercises.
Contribute to the MATLAB Community
Show steps
Gain practical experience and give back to the MATLAB community by reporting bugs or contributing code.
Show steps
Show steps
Show steps
- Identify areas in MATLAB where you can make a contribution.
- Follow community guidelines and best practices.
- Submit your contributions through the appropriate channels.
Develop a MATLAB Project
Show steps
Apply your MATLAB skills to solve a real-world problem or create a visualization tool.
Show steps
Show steps
Show steps
- Identify a problem or opportunity to address.
- Design and develop your project.
- Present your findings or share your project with others.
Participate in MATLAB Challenges
Show steps
Challenge yourself and showcase your skills by participating in MATLAB competitions and hackathons.
Show steps
Show steps
Show steps
- Find relevant competitions or hackathons.
- Register and form a team (if necessary).
- Develop and submit your solution.
Career center
Learners who complete Exploratory Data Analysis with MATLAB will develop knowledge and skills
that may be useful to these careers:
Data Journalist
Data Journalist
Data Journalists use data to tell stories and inform the public. They work with data scientists and other stakeholders to identify data-driven insights and to develop stories that are both engaging and informative. The Exploratory Data Analysis with MATLAB course will provide you with the skills and knowledge you need to succeed in this role. You will learn how to import, visualize, and analyze data, and how to write code to automate your tasks. You will also learn how to communicate your findings to others in a clear and concise way.
Machine Learning Engineer
Machine Learning Engineer
Machine Learning Engineers design, build, and deploy machine learning models. They work with data scientists and other stakeholders to identify opportunities for machine learning and to develop models that meet business needs. The Exploratory Data Analysis with MATLAB course will provide you with the skills and knowledge you need to succeed in this role. You will learn how to import, visualize, and analyze data, and how to write code to automate your tasks. You will also learn how to communicate your findings to others in a clear and concise way.
Business Analyst
Business Analyst
Business Analysts use data to identify and solve business problems. They work with stakeholders to gather requirements, analyze data, and develop recommendations. The Exploratory Data Analysis with MATLAB course will provide you with the skills and knowledge you need to succeed in this role. You will learn how to import, visualize, and analyze data, and how to write code to automate your tasks. You will also learn how to communicate your findings to others in a clear and concise way.
Operations Research Analyst
Operations Research Analyst
Operations Research Analysts use mathematical and statistical methods to improve the efficiency and effectiveness of organizations. They work in a variety of industries, including manufacturing, healthcare, and transportation. The Exploratory Data Analysis with MATLAB course will provide you with the skills and knowledge you need to succeed in this role. You will learn how to import, visualize, and analyze data, and how to write code to automate your tasks. You will also learn how to communicate your findings to others in a clear and concise way.
Statistician
Statistician
Statisticians use mathematical and statistical methods to collect, analyze, interpret, and present data. They work in a variety of fields, including finance, healthcare, and marketing. The Exploratory Data Analysis with MATLAB course will provide you with the skills and knowledge you need to succeed in this role. You will learn how to import, visualize, and analyze data, and how to write code to automate your tasks. You will also learn how to communicate your findings to others in a clear and concise way.
Financial Analyst
Financial Analyst
Financial Analysts use data to make investment recommendations. They analyze financial statements, economic data, and market trends to identify opportunities and risks. The Exploratory Data Analysis with MATLAB course will provide you with the skills and knowledge you need to succeed in this role. You will learn how to import, visualize, and analyze data, and how to write code to automate your tasks. You will also learn how to communicate your findings to others in a clear and concise way.
Marketing Analyst
Marketing Analyst
Marketing Analysts use data to understand consumer behavior and develop marketing campaigns. They analyze sales data, customer surveys, and web traffic to identify trends and opportunities. The Exploratory Data Analysis with MATLAB course will provide you with the skills and knowledge you need to succeed in this role. You will learn how to import, visualize, and analyze data, and how to write code to automate your tasks. You will also learn how to communicate your findings to others in a clear and concise way.
Risk Analyst
Risk Analyst
Risk Analysts identify and assess risks to organizations. They develop strategies to mitigate risks and ensure that organizations are prepared for unexpected events. The Exploratory Data Analysis with MATLAB course will provide you with the skills and knowledge you need to succeed in this role. You will learn how to import, visualize, and analyze data, and how to write code to automate your tasks. You will also learn how to communicate your findings to others in a clear and concise way.
Data Engineer
Data Engineer
Data Engineers design, build, and maintain data systems. They work with data scientists and other stakeholders to ensure that data is available, reliable, and secure. The Exploratory Data Analysis with MATLAB course will provide you with the skills and knowledge you need to succeed in this role. You will learn how to import, visualize, and analyze data, and how to write code to automate your tasks. You will also learn how to communicate your findings to others in a clear and concise way.
Data Visualization Specialist
Data Visualization Specialist
Data Visualization Specialists create visual representations of data. They use charts, graphs, and other visual elements to communicate data insights to stakeholders. The Exploratory Data Analysis with MATLAB course will provide you with the skills and knowledge you need to succeed in this role. You will learn how to import, visualize, and analyze data, and how to write code to automate your tasks. You will also learn how to communicate your findings to others in a clear and concise way.
Quantitative Analyst
Quantitative Analyst
Quantitative Analysts use mathematical and statistical methods to analyze financial data. They develop models to predict risk, return, and other financial outcomes. The Exploratory Data Analysis with MATLAB course will provide you with the skills and knowledge you need to succeed in this role. You will learn how to import, visualize, and analyze data, and how to write code to automate your tasks. You will also learn how to communicate your findings to others in a clear and concise way.
User Experience (UX) Researcher
User Experience (UX) Researcher
UX Researchers study how users interact with products and services. They use data and research methods to identify pain points and improve user experience. The Exploratory Data Analysis with MATLAB course will provide you with the skills and knowledge you need to succeed in this role. You will learn how to import, visualize, and analyze data, and how to write code to automate your tasks. You will also learn how to communicate your findings to others in a clear and concise way.
Data Scientist
Data Scientist
Data Scientists are responsible for extracting knowledge from data and using it to make informed decisions. They use a variety of tools and techniques, including machine learning and statistical analysis, to identify patterns and trends in data. The Exploratory Data Analysis with MATLAB course will provide you with the skills and knowledge you need to succeed in this role. You will learn how to import, visualize, and analyze data, and how to write code to automate your tasks. You will also learn how to communicate your findings to others in a clear and concise way.
Actuary
Actuary
Actuaries use mathematical and statistical methods to assess risk and uncertainty. They work in a variety of fields, including insurance, finance, and healthcare. The Exploratory Data Analysis with MATLAB course may be useful for Actuaries as it will provide them with the skills and knowledge needed to import, visualize, and analyze data, and to write code to automate their tasks. Additionally, the course will teach Actuaries how to communicate their findings to others in a clear and concise way.
Epidemiologist
Epidemiologist
Epidemiologists study the distribution and causes of disease in populations. They use data to identify risk factors, develop prevention strategies, and evaluate the effectiveness of public health interventions. The Exploratory Data Analysis with MATLAB course may be useful for Epidemiologists as it will provide them with the skills and knowledge needed to import, visualize, and analyze data, and to write code to automate their tasks. Additionally, the course will teach Epidemiologists how to communicate their findings to others in a clear and concise way.
For more career information including salaries, visit:
OpenCourser.com/course/d0zjkl/exploratory
Reading list
We've selected nine books
that we think will supplement your
learning. Use these to
develop background knowledge, enrich your coursework, and gain a
deeper understanding of the topics covered in
Exploratory Data Analysis with MATLAB.
This classic text provides a gentle introduction to numerical computing with MATLAB. It covers a wide range of topics, including linear algebra, differential equations, and optimization.
Provides a comprehensive introduction to data science for business. It covers a wide range of topics, including data mining, machine learning, and statistical modeling.
Save
Provides a comprehensive introduction to data mining using R. It covers a wide range of topics, including data cleaning, visualization, and modeling.
Provides a comprehensive introduction to machine learning using R. It covers a wide range of topics, including supervised learning, unsupervised learning, and reinforcement learning.
Provides a comprehensive introduction to statistical learning with sparsity. It covers a wide range of topics, including variable selection, regularization, and high-dimensional data analysis.
Provides a comprehensive introduction to statistical learning. It covers a wide range of topics, including supervised learning, unsupervised learning, and reinforcement learning.
Provides a comprehensive introduction to pattern recognition and machine learning. It covers a wide range of topics, including supervised learning, unsupervised learning, and reinforcement learning.
Save
Provides a comprehensive introduction to deep learning. It covers a wide range of topics, including convolutional neural networks, recurrent neural networks, and generative adversarial networks.
Provides a comprehensive introduction to reinforcement learning. It covers a wide range of topics, including Markov decision processes, value functions, and policy iteration.
For more information about how these books relate to this course, visit:
OpenCourser.com/course/d0zjkl/exploratory
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Effort
5 weeks of study, 4 hours/week
Level
Introductory
Via
Coursera
Institution
MathWorks
Instructors
Maria Gavilan-Alfonso
Heather Gorr
Michael Reardon
Erin Byrne
Brandon Armstrong
Nikola Trica
Cris LaPierre
Adam Filion
Language
English
Transcripts
Español
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آذربایجان دیلی
This course belongs to a
collection
called
Practical Data Science with MATLAB. It's comprised of four courses:
- Predictive Modeling and Machine Learning with MATLAB
- Data Processing and Feature Engineering with MATLAB
- Exploratory Data Analysis with MATLAB (viewing)
- Data Science Project: MATLAB for the Real World
Good to know
Reinforces foundational knowledge and skills in statistics for learners who are new to data science
Provides exposure to MATLAB, a widely used tool in data science and industry
Teaches learners to automate code, making data analysis more efficient and reproducible
Instructs learners to document their work using live scripts, enhancing communication and collaboration
Capstone project allows learners to apply their skills to a real-world data analysis task, fostering practical application
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