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Economic Data Analyst Course
Unlock the power of economic data with our Economic Data Analyst Course (Irish Edition), designed for Economics professionals looking to boost their analytical skills. Delve into key economic indicators such as consumer spending, employment figures, and GDP growth. Master statistical analysis, including descriptive and inferential statistics, and hypothesis testing. Learn data visualisation techniques to effectively interpret trends and communicate findings. Get hands-on experience with R, Python, and Excel, ensuring you're well-equipped to handle and prepare data with accuracy.
- Analyse economic indicators: Master consumer trends, employment, and GDP growth.
- Conduct statistical analysis: Use descriptive and inferential statistics effectively.
- Visualise data insights: Create impactful charts and interpret trends accurately.
- Interpret economic data: Draw meaningful conclusions and communicate findings clearly.
- Use data tools: Become proficient in R, Python, and Excel for data analysis.

from 4 to 360h flexible workload
certificate recognized by the MEC
What will I learn?
Unlock the power of economic data with our Economic Data Analyst Course (Irish Edition), designed for Economics professionals looking to boost their analytical skills. Delve into key economic indicators such as consumer spending, employment figures, and GDP growth. Master statistical analysis, including descriptive and inferential statistics, and hypothesis testing. Learn data visualisation techniques to effectively interpret trends and communicate findings. Get hands-on experience with R, Python, and Excel, ensuring you're well-equipped to handle and prepare data with accuracy.
Elevify advantages
Develop skills
- Analyse economic indicators: Master consumer trends, employment, and GDP growth.
- Conduct statistical analysis: Use descriptive and inferential statistics effectively.
- Visualise data insights: Create impactful charts and interpret trends accurately.
- Interpret economic data: Draw meaningful conclusions and communicate findings clearly.
- Use data tools: Become proficient in R, Python, and Excel for data analysis.
Suggested summary
Before starting, you can change the chapters and the workload. Choose which chapter to start with. Add or remove chapters. Increase or decrease the course workload.What our students say
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