Foundations of Data Science
- Offered byCoursera
Foundations of Data Science at Coursera Overview
Duration | 21 hours |
Start from | Start Now |
Total fee | Free |
Mode of learning | Online |
Difficulty level | Advanced |
Official Website | Explore Free Course  |
Credential | Certificate |
Foundations of Data Science at Coursera Highlights
- Flexible deadlines Reset deadlines in accordance to your schedule.
- Shareable Certificate Earn a Certificate upon completion
- 100% online Start instantly and learn at your own schedule.
- Coursera Labs Includes hands on learning projects. Learn more about Coursera Labs External Link
- Advanced Level
- Approx. 21 hours to complete
- English Subtitles: English
Foundations of Data Science at Coursera Course details
- 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.
- Google employees who currently work in the field will guide you through this course by providing hands-on activities that simulate relevant tasks, sharing examples from their day-to-day work, and helping you enhance your data analytics skills to prepare for your career.
- Learners who complete the seven courses in this program will have the skills needed to apply for data science and advanced data analytics jobs. This certificate assumes prior knowledge of foundational analytical principles, skills, and tools covered in the Google Data Analytics Certificate.
- By the end of this course, you will:
- -Describe the functions of data analytics and data science within an organization
- -Identify tools used by data professionals
- -Explore the value of data-based roles in organizations
- -Investigate career opportunities for a data professional
- -Explain a data project workflow
- -Develop effective communication skills
Foundations of Data Science at Coursera Curriculum
Introduction to data science concepts
Welcome to the Google Advanced Data Analytics Certificate
Introduction to Course 1
Cassie: A lifelong love of data
Welcome to week 1
What data professionals do
Explore your data toolbox
Wrap-up
Lois-An: Navigate your data career with curiosity
Prepare for your first assessment
Google Advanced Data Analytics Certificate overview
Course 1 overview
Helpful resources and tips
Data discourse
A brief history of data
Prepare to assess your readiness for the Google Advanced Data Analytics Certificate
Understand your readiness score
Participate in program surveys
Engage with other learners
Connect with other learners
Glossary terms from week 1
Assess your readiness for the Advanced Analytics Data Certificate
Weekly challenge 1
The impact of data today
Welcome to week 2
Adrian: Create a data-driven business solution
Data-driven careers
How data drives modern business
Leverage data analysis in nonprofits
Important ethical considerations for data professionals
The future of data careers
Wrap-up
Profiles of data professionals
Data trends for the future
Where data analytics makes an impact
Volunteer data skills to make a positive impact
Critical data security and privacy principles
Data stewardship and ethics conversations
The practices and principles of good data stewardship
Glossary terms from week 2
Test your knowledge: Data-driven careers
Test your knowledge: Doing good with data analytics
Test your knowledge: Trajectory of the field
Weekly challenge 2
Your career as a data professional
Welcome to week 3
The top skills needed for a data career
Cliff: Value everyone's contributions
What data professionals do
The data career space
Build a professional online presence
Tiffany: Advice for job seekers
Strengthen professional relationships
Prepare for your job search
Wrap-up
Ideal qualities for data analytics professionals
Build the perfect data team
Organize data teams with a RACI matrix, Part 1
Organize data teams with a RACI matrix, Part 2
Make the most out of mentorships
Glossary terms from week 3
Test your knowledge: Data career skills
Test your knowledge: Work in the field
Weekly challenge 3
Data applications and workflow
Welcome to week 4
Introduction to PACE
Key elements of communication
Molly: Communication is key in the workplace
Successful communication
Communication drives PACE
Connect PACE with upcoming course themes
Wrap-up
The PACE Stages
Top data professional communication practices
Activity Exemplar: Communicate with stakeholders in different roles
Communication skills for data professionals
Consider assumptions, data limitations and presentations
The value of the PACE strategy document
Communicate objectives with a project proposal
Connect PACE with executive summaries
Glossary terms from week 4
Test your knowledge: The data project workflow
Activity: Communicate with stakeholders in different roles
Test your knowledge: Elements of communication
Activity: Analyze a project proposal
Test your knowledge: Communicate like a data professional
Weekly challenge 4
Course 1 end-of-course project
The value of a portfolio
Introduction to your Course 1 end-of-course portfolio project
End-of-course project wrap-up and tips for ongoing career success
Course wrap-up
End-of-course portfolio project introduction
Course 1 end-of-course portfolio project overview: Automatidata
Activity Exemplar: Create your Course 1 Automatidata project
Course 1 glossary
Get started on the next course
Activity: Create your Course 1 Automatidata project
Assess your Course 1 end-of-course project
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