Vital Skills for Data Science | Coursera For Individuals For Businesses For Universities For Governments Explore Degrees ​ Log In Join for Free Join for Free Vital Skills for Data Science Specialization About Outcomes Courses Testimonials Previous Next Browse Data Science Data Analysis Vital Skills for Data Science Specialization Gain Exposure to Key Data Science Areas. Gain professional knowledge in the field of Data Science and learn applicable skills in Cybersecurity and Ethics. Instructors: Al Pisano +3 more Enroll for free Starts Jul 19 5,701 already enrolled Included with Coursera Plus •Learn more Ask Coursera Is this right for me? 4 course series Get in-depth knowledge of a subject 4.3 from 132 reviews of courses in this program Intermediate level Recommended experience Flexible schedule 2 months at 10 hours a week Learn at your own pace Build toward a degree Learn more 4 course series Get in-depth knowledge of a subject 4.3 from 132 reviews of courses in this program Intermediate level Recommended experience Flexible schedule 2 months at 10 hours a week Learn at your own pace Build toward a degree Learn more About Outcomes Courses Testimonials Previous Next What you'll learn Identify applications of Data Science. Identify the steps of the Data Science process and apply them with real world data. Discuss privacy concerns. Skills you'll gain Visualization (Computer Graphics) Information Privacy Data Presentation Interactive Data Visualization Usability Data Visualization Healthcare Ethics Medical Science and Research User Centered Design Analysis Statistical Reporting Computer Security Cybersecurity Cyber Attacks Data Visualization Software Data Security Ethical Standards And Conduct Data Ethics Data Storytelling Technical Communication Show all Details to know Shareable certificate Add to your LinkedIn profile Taught in English 21 languages available See how employees at top companies are mastering in-demand skills Learn more about Coursera for Business Advance your subject-matter expertise Learn in-demand skills from university and industry experts Master a subject or tool with hands-on projects Develop a deep understanding of key concepts Earn a career certificate from University of Colorado Boulder Specialization - 4 course series Vital Skills for Data Science introduces students to several areas that every data scientist should be familiar with. Each of the topics is a field in itself. This specialization provides a "taste" of each of these areas which will allow the student to determine if any of these areas is something they want to explore further. In this specialization, students will learn about different applications of data science and how to apply the steps in a data science process to real life data. They will be introduced to the ethical questions every data scientist should be aware of when doing an analysis. The field of cybersecurity makes the data scientist aware of how to protect their data from loss. This specialization can be taken for academic credit as part of CU Boulder’s Master of Science in Data Science (MS-DS) degree offered on the Coursera platform. The MS-DS is an interdisciplinary degree that brings together faculty from CU Boulder’s departments of Applied Mathematics, Computer Science, Information Science, and others. With performance-based admissions and no application process, the MS-DS is ideal for individuals with a broad range of undergraduate education and/or professional experience in computer science, information science, mathematics, and statistics. Learn more about the MS-DS program at https://www.coursera.org/degrees/master-of-science-data-science-boulder.Opens in a new tab https://www.coursera.org/degrees/master-of-science-data-science-boulder.Opens in a new tab Logo image by JJ YingOpens in a new tab on UnsplashOpens in a new tab Applied Learning Project Projects will encourage students to engage in ethical discussions, hone networking skills, address cybersecurity threats, and explore the professional world of Data Science. These projects will help students develop an understanding of the field and gain skills that will help them be successful. Data Science as a Field Course 1, 11 hoursCourse 1•11 hoursCourse details What you'll learn By taking this course, you will be able explain what data science is and identify the key disciplines involved. You will be able to use the steps of the data science process to create a reproducible data analysis and identify personal biases. You will be able to identify interesting data science applications, locate jobs in Data Science, and begin developing a professional network. Skills you'll gain Category: Data AnalysisData Analysis Category: Data ScienceData Science Category: Data StorytellingData Storytelling Category: Applied MathematicsApplied Mathematics Category: AnalysisAnalysis Category: Technical CommunicationTechnical Communication Category: Computer ScienceComputer Science Category: Statistical ReportingStatistical Reporting Category: Data PresentationData Presentation Category: StatisticsStatistics Category: Data LiteracyData Literacy Ethical Issues in Data Science Course 2, 24 hoursCourse 2•24 hoursCourse details What you'll learn Learners will be able to Identify and manage ethical situations that may arise in their careers. Learnerrs will be able to apply ethical frameworks to help them analyze ethical challenges. Learners will be familiar with key applications of data science that are commonly  linked to ethical issues. Skills you'll gain Category: Data EthicsData Ethics Category: Ethical Standards And ConductEthical Standards And Conduct Category: Responsible AIResponsible AI Category: Diversity AwarenessDiversity Awareness Category: Data SecurityData Security Category: Information PrivacyInformation Privacy Category: Case StudiesCase Studies Category: Medical PrivacyMedical Privacy Category: Artificial IntelligenceArtificial Intelligence Category: Medical Science and ResearchMedical Science and Research Category: Data ScienceData Science Category: Law, Regulation, and ComplianceLaw, Regulation, and Compliance Category: CybersecurityCybersecurity Category: AutomationAutomation Category: Machine Learning AlgorithmsMachine Learning Algorithms Category: AlgorithmsAlgorithms Category: Clinical Research EthicsClinical Research Ethics Category: Healthcare EthicsHealthcare Ethics Cybersecurity for Data Science Course 3, 19 hoursCourse 3•19 hoursCourse details What you'll learn Characterize the CIA principles and use them to classify a variety of cyber scenarios. Identify and disseminate vulnerabilities in the data security space- social (human) and technical (digital). Distinguish ethical boundaries of hacking and its applications. Explore professional cybersecurity networks and connect with experts from the field. Skills you'll gain Category: Data EthicsData Ethics Category: CryptographyCryptography Category: CybersecurityCybersecurity Category: Data SecurityData Security Category: Risk AnalysisRisk Analysis Category: Security AwarenessSecurity Awareness Category: Information AssuranceInformation Assurance Category: Cyber Security AssessmentCyber Security Assessment Category: Information PrivacyInformation Privacy Category: Authorization (Computing)Authorization (Computing) Category: Problem SolvingProblem Solving Category: AuthenticationsAuthentications Category: Cyber Security PoliciesCyber Security Policies Category: Security SoftwareSecurity Software Category: Security ControlsSecurity Controls Category: Computer SecurityComputer Security Category: CommunicationCommunication Category: Data AccessData Access Category: EncryptionEncryption Category: Cyber AttacksCyber Attacks Fundamentals of Data Visualization Course 4, 15 hoursCourse 4•15 hoursCourse details What you'll learn Develop a toolkit for exploring and communicating complex data using visualization Produce basic data visualizations using a chosen dataset Compare methods for visualizing data and understand how these methods may guide users towards different conclusions Evaluate how effectively a visualization conveys target data Skills you'll gain Category: Interactive Data VisualizationInteractive Data Visualization Category: Data Visualization SoftwareData Visualization Software Category: Data VisualizationData Visualization Category: Quantitative ResearchQuantitative Research Category: Design Elements And PrinciplesDesign Elements And Principles Category: Design ResearchDesign Research Category: Graphic and Visual DesignGraphic and Visual Design Category: User Centered DesignUser Centered Design Category: Human Centered DesignHuman Centered Design Category: User ResearchUser Research Category: Visualization (Computer Graphics)Visualization (Computer Graphics) Category: Data PresentationData Presentation Category: UsabilityUsability Category: Usability TestingUsability Testing Earn a career certificate Add this credential to your LinkedIn profile, resume, or CV. Share it on social media and in your performance review. Build toward a degree This Specialization is part of the following degree program(s) offered by University of Colorado Boulder. If you are admitted and enroll, your completed coursework may count toward your degree learning and your progress can transfer with you.¹ View eligible degrees Instructors Al Pisano University of Colorado Boulder 1 Course•5,063 learnersView all 4 instructors Offered by University of Colorado BoulderLearn more Why people choose Coursera for their career Felipe M. Learner since 2018 "To be able to take courses at my own pace and rhythm has been an amazing experience. I can learn whenever it fits my schedule and mood." Jennifer J. Learner since 2020 "I directly applied the concepts and skills I learned from my courses to an exciting new project at work." Larry W. Learner since 2021 "When I need courses on topics that my university doesn't offer, Coursera is one of the best places to go." Chaitanya A. "Learning isn't just about being better at your job: it's so much more than that. Coursera allows me to learn without limits." Unlock access to 10,000+ courses with a subscription Start trial Advance your career with an online degree Earn a degree from world-class universities - 100% online Explore degrees Join over 4,700 global companies that choose Coursera for Business Learn more Frequently asked questions How long does it take to complete the Specialization? Vital Skills for Data Science takes approximately sixteen weeks of study to complete. What background knowledge is necessary? In order to successfully complete this specialization, learners should have some R programming. Do I need to take the courses in a specific order? Courses do not have to be taken a specific order, though it's recommended that learners follow the sequence of courses if they have no previous experience with data structures or algorithm analysis and design. Will I earn university credit for completing the Specialization? Vital Skills for Data Science is part of CU Boulder's Master of Science in Data Science (MS-DS) program. Learners enrolled in the degree program will earn three credits for successful completion of the specialization. What will I be able to do upon completing the Specialization? Upon completing the specialization, learners will have and broad understanding of the world of Data Science and ethical and cybersecurity concerns in the field. They will also be able to exercise networking skills to expand their professional connections. What is a cross-listed course? A cross-listed course is offered under two or more CU Boulder degree programs on Coursera. For example, Dynamic Programming, Greedy Algorithms is offered as both CSCA 5414 for the MS-CS and DTSA 5503 for the MS-DS. · You may not earn credit for more than one version of a cross-listed course. · You can identify cross-listed courses by checking your program’s student handbook. · Your transcript will be affected. Cross-listed courses are considered equivalent when evaluating graduation requirements. However, we encourage you to take your program's versions of cross-listed courses (when available) to ensure your CU transcript reflects the substantial amount of coursework you are completing directly in your home department. Any courses you complete from another program will appear on your CU transcript with that program’s course prefix (e.g., DTSA vs. CSCA). · Programs may have different minimum grade requirements for admission and graduation. For example, the MS-DS requires a C or better on all courses for graduation (and a 3.0 pathway GPA for admission), whereas the MS-CS requires a B or better on all breadth courses and a C or better on all elective courses for graduation (and a B or better on each pathway course for admission). All programs require students to maintain a 3.0 cumulative GPA for admission and graduation. Can I take cross-listed courses to fulfill my degree requirements? Yes. Cross-listed courses are considered equivalent when evaluating graduation requirements. You can identify cross-listed courses by checking your program’s student handbook. How do I upgrade and earn credit from CU Boulder? You may upgrade and pay tuition during any open enrollment period to earn graduate-level CU Boulder credit for << this course/ courses in this specialization>>. Because << this course is / these courses are >> cross listed in both the MS in Computer Science and the MS in Data Science programs, you will need to determine which program you would like to earn the credit from before you upgrade. MS in Data Science (MS-DS) Credit: To upgrade to the for-credit data science (DTSA) version of << this course / these courses >>, use the MS-DS enrollment form. See How It WorksOpens in a new tab . MS in Computer Science (MS-CS) Credit: To upgrade to the for-credit computer science (CSCA) version of << this course / these courses >>, use the MS-CS enrollment form. See How It WorksOpens in a new tab . If you are unsure of which program is the best fit for you, review the MS-CSOpens in a new tab and MS-DSOpens in a new tab program websites, and then contact datascience@colorado.eduOpens in a new tab or mscscoursera-info@colorado.eduOpens in a new tab if you still have questions. Is this course really 100% online? Do I need to attend any classes in person? 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. Can I just enroll in a single course? 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. 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. Is financial aid available? 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. Can I take the course for free? No, you cannot take this course for free. 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. 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