This is the "science" part. You need enough stats to know if your results are a real trend or just a random fluke. 3. The Workflow (The "Data Pipeline")
Making charts and graphs to see what the data is "whispering." Getting Started with Data Science: Making Sense...
Python is the "Swiss Army Knife" of data science—it's easy to read and has massive community support. This is the "science" part
Using algorithms to find patterns or make predictions. Getting Started with Data Science: Making Sense...
Explaining your findings to people who don't speak data. 4. Making it "Sense"
When an algorithm gives you a result, ask yourself why it chose that. Understanding the logic is more important than memorizing the formula.