This is the first of eight 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.


您将学到什么
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
您将获得的技能
要了解的详细信息
了解顶级公司的员工如何掌握热门技能

积累 Data Analysis 领域的专业知识
- 向行业专家学习新概念
- 获得对主题或工具的基础理解
- 通过实践项目培养工作相关技能
- 通过 Google 获得可共享的职业证书

该课程共有5个模块
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.
涵盖的内容
8个视频9篇阅读材料3个作业1个插件
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.
涵盖的内容
8个视频9篇阅读材料5个作业2个插件
You’ll identify the skills data professionals use to analyze data. You'll also explore how data professionals collaborate with teammates.
涵盖的内容
4个视频4篇阅读材料3个作业
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.
涵盖的内容
7个视频9篇阅读材料6个作业2个插件
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.
涵盖的内容
4个视频11篇阅读材料4个作业
获得职业证书
将此证书添加到您的 LinkedIn 个人资料、简历或履历中。在社交媒体和绩效考核中分享。
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提供方
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University of London
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Google
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学生评论
3,529 条评论
- 5 stars
79.12%
- 4 stars
14.27%
- 3 stars
3.87%
- 2 stars
1.27%
- 1 star
1.44%
显示 3/3529 个
已于 Jun 4, 2023审阅
It was very useful to understand how is the data science carrers, how to communicate properly with others and how developt a good project proporsal and Pace workflow
已于 Feb 6, 2025审阅
Best course to kick start your career as a data analyst or other job role related to data, AI and ML. Well taught and best suited for startees and beginners.
已于 Sep 21, 2024审阅
Good intro. Was able to move through quickly to suit my level of comfort with material. Was more about filling in some practical details for me, rather than introducing me to a 'whole new world'.
常见问题
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.
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