Excel-Basic to Advanced
Curso

Excel-Basic to Advanced

Master Excel end-to-end, from core basics to advanced functions. This intensive course is designed for professionals who want to streamline daily tasks, boost productivity, and make smarter data-driven decisions. Through hands-on exercises and real-world case studies, you’ll level up your Excel skills for workplace success.

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+6
Years of experience
MSc
Applied Statistics
Official
Statistical methodology
R · Python
Power BI
USAC
University teaching
Audit
Data that withstands scrutiny
What you will learn
  • Understand the fundamentals of the subject.
  • Build practical skills with guided exercises.
  • Apply your knowledge in a final project.
Quick facts
  • Level: Beginner–Intermediate & Advanced
  • Certificate: Yes
Technologies
Excel Power BI Python SQL RStudio

Master Excel end-to-end, from core basics to advanced functions. This intensive course is designed for professionals who want to streamline daily tasks, boost productivity, and make smarter data-driven decisions. Through hands-on exercises and real-world case studies, you’ll level up your Excel skills for workplace success.

Master Excel end-to-end, from core basics to advanced functions. This intensive course is designed for professionals who want to streamline daily tasks, boost productivity, and make smarter data-driven decisions. Through hands-on exercises and real-world case studies, you’ll level up your Excel skills for workplace success.

Contact us for details about this service.

Sample · Illustrative data

This is what your data could look like

We transform the complexity of your data into rigorous analysis that reveals the key insights for your thesis, market research, project, or business. We provide the clarity you need to interpret results, predict trends, and prepare to make decisions or support findings with solid evidence. We have the perfect solution for you.

Monthly trend
Distribution by segment
0%
Model accuracy
0
Customer segments
Q0M
Projected revenue
0%
Explained variance (R²)
Customer segmentation (k-means)

Grouping by spend and frequency

Prediction (regression)

Fitted model over observed data

Variable importance (random forest)

Which factors drive the outcome