This is the first of seven courses in the Google Advanced Data Analytics Certificate, which will help develop the skills needed to apply for more advanced data professional roles, such as an entry-level data scientist or advanced-level data analyst. Data professionals analyze data to help businesses make better decisions. To do this, they use powerful techniques like data storytelling, statistics, and machine learning. In this course, you’ll begin your learning journey by exploring the role of data professionals in the workplace. You’ll also learn about the project workflow PACE (Plan, Analyze, Construct, Execute) and how it can help you organize data projects.
Foundations of Data Science
Dieser Kurs ist Teil von Google Advanced Data Analytics (berufsbezogenes Zertifikat)
Dozent: Google Career Certificates
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Was Sie lernen werden
Understand common careers and industries that use advanced data analytics
Investigate the impact data analysis can have on decision-making
Explain how data professionals preserve data privacy and ethics
Develop a project plan considering roles and responsibilities of team members
Kompetenzen, die Sie erwerben
- Kategorie: Project Management
- Kategorie: Sharing Insights With Stakeholders
- Kategorie: Cross-Functional Team Dynamics
- Kategorie: Asking Effective Questions
- Kategorie: Effective Written Communication
Wichtige Details
Zu Ihrem LinkedIn-Profil hinzufügen
19 Quizzes, 1 Aufgabe
Erfahren Sie, wie Mitarbeiter führender Unternehmen gefragte Kompetenzen erwerben.
Erweitern Sie Ihr Fachwissen im Bereich Data Analysis
- Lernen Sie neue Konzepte von Branchenexperten
- Gewinnen Sie ein Grundverständnis bestimmter Themen oder Tools
- Erwerben Sie berufsrelevante Kompetenzen durch praktische Projekte
- Erwerben Sie ein Berufszertifikat von Google zur Vorlage
Erwerben Sie ein Karrierezertifikat.
Fügen Sie diese Qualifikation zur Ihrem LinkedIn-Profil oder Ihrem Lebenslauf hinzu.
Teilen Sie es in den sozialen Medien und in Ihrer Leistungsbeurteilung.
In diesem Kurs gibt es 5 Module
You’ll begin with an introduction to the Google Advanced Data Analytics Certificate. Then, you'll explore the history of data science and ways that data science helps solve problems today.
Das ist alles enthalten
7 Videos10 Lektüren2 Quizzes3 Diskussionsthemen3 Plug-ins
Now that you’re more familiar with the history of data science, you’re ready to explore today’s data career space. You’ll learn more about how data professionals manage and analyze their data, as well as how data-driven insights can help organizations.
Das ist alles enthalten
8 Videos9 Lektüren5 Quizzes3 Diskussionsthemen1 Plug-in
You’ll identify the skills data professionals use to analyze data. You'll also explore how data professionals collaborate with teammates.
Das ist alles enthalten
9 Videos6 Lektüren2 Quizzes1 Aufgabe
You’ll learn about the PACE (Plan, Analyze, Construct, Execute) project workflow and how to organize a data project. You’ll also learn how to communicate effectively with teammates and stakeholders.
Das ist alles enthalten
7 Videos9 Lektüren6 Quizzes1 Diskussionsthema1 Plug-in
You’ll complete an end-of-course project, gaining an opportunity to apply your new data skills and knowledge from Course 1 to a workplace scenario, and practice solving a business problem.
Das ist alles enthalten
4 Videos10 Lektüren4 Quizzes2 Diskussionsthemen
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Geprüft am 16. Dez. 2023
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Geprüft am 21. Apr. 2023
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Häufig gestellte Fragen
Organizations of all types and sizes have business processes that generate massive volumes of data. Every moment, all sorts of information gets created by computers, the internet, phones, texts, streaming video, photographs, sensors, and much more. In the global digital landscape, data is increasingly imprecise, chaotic, and unstructured. As the speed and variety of data increases exponentially, organizations are struggling to keep pace.
Data science and advanced data analytics are part of a field of study that uses raw data to create new ways of modeling and understanding the unknown. To gain insights, businesses rely on data professionals to acquire, organize, and interpret data, which helps inform internal projects and processes. Data scientists and advanced data analysts rely on a combination of critical skills, including statistics, scientific methods, data analysis, and artificial intelligence.
A data professional is a term used to describe any individual who works with data and/or has data skills. At a minimum, a data professional is capable of exploring, cleaning, selecting, analyzing, and visualizing data. They may also be comfortable with writing code and have some familiarity with the techniques used by statisticians and machine learning engineers, including building models, developing algorithmic thinking, and building machine learning models.
Data professionals are responsible for collecting, analyzing, and interpreting large amounts of data within a variety of different organizations. The role of a data professional is defined differently across companies. Generally speaking, data professionals possess technical and strategic capabilities that require more advanced analytical skills such as data manipulation, experimental design, predictive modeling, and machine learning. They perform a variety of tasks related to gathering, structuring, interpreting, monitoring, and reporting data in accessible formats, enabling stakeholders to understand and use data effectively. Ultimately, the work of data professionals helps organizations make informed, ethical decisions.
Large volumes of data — and the technology needed to manage and analyze it — are becoming increasingly accessible. Because of this, there has been a surge in career opportunities for people who can tell stories using data, such as senior data analysts and data scientists. These professionals collect, analyze, and interpret large amounts of data within a variety of different organizations. Their responsibilities require advanced analytical skills such as data manipulation, experimental design, predictive modeling, and machine learning.