What You'll Learn
- Set up a free Databricks account and launch a Spark cluster for analytics projects.
- Navigate and use Apache Spark notebooks effectively for data analysis.
- Load, structure, and explore datasets using Spark DataFrames.
- Perform real-world analytics on Olympic Games data, including:
- Age, height, and weight distribution of medal-winning athletes.
- Women’s medal trends over the years.
- Top medal-winning countries and sports.
- Gold, Silver, and Bronze medal distribution analysis.
- Athlete demographics and performance patterns over time.
- Create data visualizations to present insights from Spark outputs.
- Publish Spark notebooks to the web to share project results.
- Build a portfolio-ready Spark project demonstrating end-to-end data analytics skills.
Requirements
- A computer with internet access.
- Basic familiarity with Microsoft Excel or CSV files is helpful but not required.
- No prior experience in Apache Spark is necessary — this course is beginner-friendly.
- Curiosity and willingness to learn data analytics with real-world datasets.
Who This Course is For
- Beginners looking to learn Apache Spark through a practical project.
- Students or professionals interested in data analytics and data science.
- Aspiring Data Engineers or Data Analysts who want to build portfolio-ready projects.
- Anyone interested in sports analytics or analyzing Olympic Games data.
- Learners who prefer hands-on, project-based learning over theory-only courses.
Your Instructor
Bigdata Engineer
Bigdata Engineer
3.9 Instructor Rating
1,579 Reviews
136,020 Students
22 Courses
Never Miss a Coupon!
Subscribe to our newsletter to get daily updates on the latest free courses.