You’re almost there! This is the seventh and final course of the Google Advanced Data Analytics Certificate. In this course, you have the opportunity to complete an optional capstone project that includes key concepts from each of the six preceding courses. During this capstone project, you'll use your new skills and knowledge to develop data-driven insights for a specific business problem.
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Google Advanced Data Analytics Capstone
Dieser Kurs ist Teil von Google Advanced Data Analytics (berufsbezogenes Zertifikat)
Dozent: Google Career Certificates
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Was Sie lernen werden
Examine data to identify patterns and trends
Build models using machine learning techniques
Create data visualizations
Explore career resources
Kompetenzen, die Sie erwerben
- Kategorie: Data Analysis
- Kategorie: Python Programming
- Kategorie: Machine Learning
- Kategorie: Technical Interview Preparation
- Kategorie: Executive Summaries
Wichtige Details
Zu Ihrem LinkedIn-Profil hinzufügen
8 Quizzes
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 3 Module
To start, you’ll be provided with an overview of the optional capstone project and how it differs from the end-of-course projects. You’ll also receive helpful suggestions for successfully completing the capstone project. Finally, you'll learn how to incorporate your completed capstone project into your professional portfolio.
Das ist alles enthalten
3 Videos5 Lektüren3 Quizzes2 Unbewertete Labore
You’ll review data-focused career resources designed to help you effectively navigate the job market. You'll also get useful tips for polishing your resume and preparing for interviews.
Das ist alles enthalten
10 Videos7 Lektüren4 Quizzes
You’ll complete the final tasks necessary to earn your Google Advanced Data Analytics Certificate badge. Congratulations!
Das ist alles enthalten
2 Videos3 Lektüren1 Quiz1 Plug-in
Dozent
von
Empfohlen, wenn Sie sich für Data Analysis interessieren
University of Illinois Urbana-Champaign
- Status: [object Object]
Johns Hopkins University
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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.