Foundations of Data Science

External: Coursera Courses ↗ · Coursera

Open Course on External: Coursera

Free to audit · Opens on External: Coursera

Foundations of Data Science

Coursera · Beginner ·📊 Data Analytics & Business Intelligence ·3mo ago

Key Takeaways

Foundations of data science using data storytelling, statistics, and machine learning

Original Description

This is the first course 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 eight 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
Watch on External: Coursera ↗ (saves to browser)
Sign in to unlock AI tutor explanation · ⚡30

Related Reads

📰
Why Synthetic Healthcare Data Isn’t Enough for Commercial Analytics
Synthetic healthcare data has limitations for commercial analytics, and finding suitable synthetic commercial data is challenging
Medium · Data Science
📰
Why Synthetic Healthcare Data Isn’t Enough for Commercial Analytics
Synthetic healthcare data has limitations for commercial analytics, and finding suitable synthetic commercial data is challenging
Medium · Python
📰
Scraping Indian government open data in 2026: what actually works
Learn to scrape Indian government open data for projects like Village Finder, a mapping project tracking 78,000 Indian villages
Dev.to · Manideep Chittineni
📰
2026 Enterprise Data Recovery: What IT Teams Should Look For
Learn what IT teams should look for in 2026 enterprise data recovery to minimize losses and ensure business continuity
Medium · AI
Up next
6-Phase SQL Roadmap 2026 | Data Analytics & Engineering | #shorts
SCALER
Watch →