Data. Every time you make a purchase online or share a photo with friends, you are contributing to the pile of data being amassed every single second from every corner of the earth. We’re producing tons of data, yet the demand for qualified data analysts is outpacing the amount of data being created every day. So the question becomes – what does it take to become a data analyst?
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To be truly successful in this new and exciting field, you’ll need to understand essential skills as well as where your strengths lie and what skills you still need to develop. Yes, you need to know R and Python, but which packages are the most useful to a data analyst? Are there specific mathematical concepts that are more important than others? And what skills can set you apart from the competition when it comes to interviewing for a job?
We’ve put together a comprehensive 18 page checklist that explains the essential skills and tools you’ll need for a career in data science. Download our Ultimate Skills Checklist for Your First Data Analyst Job to see how we’ve built upon concepts mentioned in previous articles to explain exactly what you need to know in each subject.
Topics covered include:
- Python and R packages, both essential and good-to-know
- Descriptive and Inferential Statistics
- Mathematics
- Experimental Design
- Supervised and Reinforcement Learning
- Database Systems
and others. In addition, there are over 3 pages of tips and external resources for extra learning.
Interested in more? We also offer a Data Analyst Nanodegree program that will build up your data science portfolio through industry-approved projects and open up new opportunities to advance your career.
