What Is a Social Media Influencer? And How to Become One
December 10, 2024
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Instructors: Sam Jones
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Analyze large datasets & calculate statistics on specific groups in the data
Use interactive tools to investigate your data & remove noise and outliers
Create & evaluate machine learning models
Create reports & interactive documents to share your work
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Do you find yourself in an industry or field that increasingly uses data to answer questions? Are you working with an overwhelming amount of data and need to make sense of it? Do you want to avoid becoming a full-time software developer or statistician to do meaningful tasks with your data?
Completing this specialization will give you the skills and confidence you need to achieve practical results in Data Science quickly. Being able to visualize, analyze, and model data are some of the most in-demand career skills from fields ranging from healthcare, to the auto industry, to tech startups.
This specialization assumes you have domain expertise in a technical field and some exposure to computational tools, such as spreadsheets. To be successful in completing the courses, you should have some background in basic statistics (histograms, averages, standard deviation, curve fitting, interpolation).
Throughout this specialization, you will be using MATLAB. MATLAB is the go-to choice for millions of people working in engineering and science, and provides the capabilities you need to accomplish your data science tasks. You will be provided with free access to MATLAB for the duration of the specialization to complete your work.
Applied Learning Project
You'll apply your new skills on several real-world examples including: analyzing costs associated with severe weather events, predicting flight delays, and building machine learning models. The final capstone project will provide you the opportunity to apply concepts from all the courses to gain insight from raw data and to build predictive models.
Import large tabular datasets & customize the import options for your application
Extract subsets of data & compute statistics on groups of related data
Create customized visualizations to highlight the most relevant results from your analysis
Use interactive tools to explore, analyze, & visual data with automated code generation for reproducing results
Prepare data for further analysis by removing noise, identifying outliers, & merging data from multiple sources
Create and evaluate features for machine learning applications
Explore special techniques for handling textual, audio, & image data
Perform unsupervised machine learning
Apply a full machine learning workflow, from cleaning data to training & evaluating models using a real-world dataset
Use apps to quickly train many machine learning models to find the best approach for your application
Customize training using cost matrices to emphasize important classes
Apply a full data science workflow, including importing & cleaning data, creating features, training machine learning models, & evaluating results
Effectively communicate results by identifying your target audience & creating meaningful visualizations
Create a final report that includes text, code, & visualizations to share with colleagues
Unlimited access to 10,000+ world-class courses, hands-on projects, and job-ready certificate programs - all included in your subscription
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Basic math, statistics and some experience working with spreadsheets will be helpful. No prior experience with MATLAB or programming is necessary.
Yes. A free license is available to learners enrolled in the course. You must have a computer capable of running MATLAB. You can view the system requirements here.
You will be able to:
Import data from a variety of sources into MATLAB
Create compelling visualizations
Analyze and calculate statistics on groups of data
Perform common data cleaning techniques
Identify and create new features for machine learning models
Apply common machine learning methods and evaluate their performance
It is recommended that you take the courses in order. The skills gained in course one is considered pre-requisite knowledge for course two.
This course is completely online, so there’s no need to show up to a classroom in person. You can access your lectures, readings and assignments anytime and anywhere via the web or your mobile device.
If you subscribed, you get a 7-day free trial during which you can cancel at no penalty. After that, we don’t give refunds, but you can cancel your subscription at any time. See our full refund policy.
Yes! To get started, click the course card that interests you and enroll. You can enroll and complete the course to earn a shareable certificate, or you can audit it to view the course materials for free. When you subscribe to a course that is part of a Specialization, you’re automatically subscribed to the full Specialization. Visit your learner dashboard to track your progress.
Yes. In select learning programs, you can apply for financial aid or a scholarship if you can’t afford the enrollment fee. If fin aid or scholarship is available for your learning program selection, you’ll find a link to apply on the description page.
When you enroll in the course, you get access to all of the courses in the Specialization, and you earn a certificate when you complete the work. If you only want to read and view the course content, you can audit the course for free. If you cannot afford the fee, you can apply for financial aid.
This Specialization doesn't carry university credit, but some universities may choose to accept Specialization Certificates for credit. Check with your institution to learn more.
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