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@markusspiske/PexelsAs companies amass more data than ever, the employees best able to interpret it and apply key insights to important decision-making processes become increasingly valuable.
But while the skillset grows more desirable, the supply of workers with the correct skills isn't sufficient — making data science skills among the most in-demand hard skills in 2020, according to LinkedIn's research.
Thankfully, there are plenty of online learning opportunities to help you prepare for a career in data science, whether it's a course that helps you master a specific skill or an intensive year-long program that helps you jump up the ladder in your current role. Many classes are offered by top schools such as Harvard and MIT, and many programs were designed by major companies like IBM and Google specifically for educating a useful future workforce. Some of them offer students the opportunity to join their talent network after completing a specific course level.
Below are a few of the most popular data science options online, including MicroMasters, professional certificates, and individual courses.
Professional certificates are bundles of related courses that help you master a specific skill, and they tend to be most useful for breaking into a new industry or getting you to the next level of your career. They can take anywhere from a few months to more than a year to complete. At Coursera, professional certificate programs typically have a 7-day free trial and a monthly fee afterward. So, the faster you complete it, the more money you'll save. At edX, professional certificates typically have a flat one-time fee.
MicroMasters are a bundle of graduate-level courses that are designed to help you advance your career. Students have the option of applying to the university that's offering credit for the MicroMasters program certificate and, if accepted, can pursue an accelerated and less expensive Master's Degree. You can learn more here.
If you end up taking a Coursera course, and you think you'll realistically spend more than $399 in monthly fees or on individual classes throughout the year, you may want to consider Coursera Plus if all the courses and programs you plan to take are included in the annual membership (90% of the site is). And, if your employer offers to cover educational costs that include online-learning programs, you may even be able to get reimbursed for the following courses.
Browse all data science classes on edXBrowse all data science classes on Coursera10 of the most popular data science programs and courses online:Read the original article on Business Insider
IBM's course is an introduction to Python for Data Science. It aims to take students from the beginning to programming in Python within a week and includes lab exercises for practice. Upon completion, students will be able to write their own Python scripts and perform basic hands-on data analysis using a Jupyter-based lab environment.
You can audit the course for free, or pay for a certificate of completion for $39.
UC SanDiego's MicroMasters Program in Data Science integrates the mathematical and applied aspects of data science learning. It's designed to lend a well-rounded foundation of the mathematical and computational tools that form the basis of data science, and how to use them to make data-driven business recommendations. It includes four graduate-level courses and, according to the school, should take about 10 months to complete.
Harvard's professional certificate in data science includes eight courses and a final project. Students learn fundamental R programming skills, statistical concepts, and gain experience with the tidyverse, including data visualization with ggplot2 and data wrangling with dplyr, among other things.
This self-paced program should take approximately one year and five months to complete.
MIT's MicroMasters focuses on the foundations of data science, statistics, and machine learning in four graduate-level courses and a virtually proctored exam. The course is built to prepare its students for job titles like Data Scientist, Data Analyst, Business Intelligence Analyst, Systems Analyst, and Data Engineer. According to the school, it should take about one year and three months to complete.
LearnQuest is an Apple Authorized Global Training Provider, and this course introduces the concepts of Artificial Intelligence and Machine Learning to students who already have a general knowledge of Azure.
Students will go through an introduction to AI, Standardized AI Processes and Azure Resources, Azure Cognitive APIs, and Azure Machine Learning Service: Model Training.
It'll take you approximately 16 hours to complete.
This Google Cloud course is designed as an introduction to machine learning for non-technical business professionals. By the end, students will have learned how to formulate machine learning solutions to real-world problems, identify whether the data you have is sufficient for ML, carry a project through various ML phases, and perform AI responsibly without reinforcing existing bias.
According to the company, it takes approximately 12 hours to complete.
Amazon Web Services' Machine Learning course teaches students the basics of AWS Machine Learning, including key problems that ML can address, how to build intelligent applications using Amazon AI services, and how to build, train, and deploy a model using Amazon SageMaker with built-in algorithms and Jupyter Notebook instance among other things.
It should take students about eight hours to complete.
Google's IT Automation with Python is a beginner-level program that includes six courses designed to build on IT foundations and provide IT professionals with in-demand skills like Python, Git, and IT automation.
It's estimated to take about six months to complete. And, upon completion, you'll have the option to share your information with potential employers, like Walmart, Sprint, Hulu, Bank of America, Google, and more.
Google's IT Support professional certificate includes five courses designed to prepare beginners for an entry-level role in IT support.
Students are introduced to troubleshooting, customer service, networking, operating systems, system administration, and security through video lectures, quizzes, and hands-on labs and widgets.
According to the company, you can complete it in under six months if you're able to dedicate about five hours per week to it.
You can also earn a CompTIA and Google dual credential when you complete the Google certificate and pass the CompTIA A+ certification exams.
IBM's professional certificate includes nine courses that will give beginners job-ready skills and techniques.
The program covers a range of data science topics, including open source tools and libraries, methodologies, Python, databases, SQL, data visualization, data analysis, and machine learning. Students practice in the IBM Cloud using real data science tools and data sets.
Upon completion, you will have a portfolio of projects and have completed several hands-on assignments. In addition to a professional certificate from Coursera that you can add to your resume and LinkedIn, you'll also receive a digital badge from IBM recognizing proficiency in Data Science.
According to Coursera, it should take approximately three months to complete as a full-time student.
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