Practice, practice, and then.... practice again.
Books and theory are very important, but I prefer to spend the most part of the time with exercises, and then recommend the student lectures written by me or from a book.
Data Science is a very complex world, with a lot of maths and programmig. I usually teach the theory in the 20% of the class, and the rest is for practise and questions.
But all of this depends on each student :)
I'm an engineer with 4 years of experience in Data Science world. My universitary titles are:
- Degree in Telecommunication Engineer
- Master in Telecomunication, specialiced in Computer Science
- Master in Data Science
I work in one of the biggest finance companies in the world.
I have wide experience teaching Data Science technologies in my work and also teaching private classes.
I'm from Spain so you can learn in English or Spanish! :)
Programming Languages I use: Python (pandas, numpy, sklearn, seaborn, matplotlib), R (tidyverse, dplyr, ggpot2), SQL
Programs I use: Anaconda, Spyder, Jupyter, RStudio, QlikView, QlikSense, Power BI, Cloudera environment
Fields I manage: Machine learning, Big Data, Business Intelligence, Data Base Querying, statistics
You have my completed resume in LinkedIn:
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