basics of Julia • intermediate data wrangling • intermediate data visualization
skills learned
tabular data ingestion and integrity validation • exploratory data analysis using descriptive and graphical techniques • feature selection and feature engineering
Łukasz Kraiński and Bogumił Kamiński
1 week · 4-6 hours per week · INTERMEDIATE
In this liveProject, you’ll test your data wrangling and data processing skills using the Julia language. You’ll step into the role of a data scientist for a real estate company with a new task from your boss—analyze and clean housing and census data for the marketing and sales teams. You’ll employ the popular Julia package DataFrame.jl as well as powerful statistics related libraries to successfully explore these datasets, and prepare them for machine learning.
This project is designed for learning purposes and is not a complete, production-ready application or solution.
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prerequisites
This liveProject is for experienced data scientists and data analysts who are interested in building their skills in Julia. To begin this liveProject, you will need to be familiar with:
TOOLS
Basics of Jupyter notebook
Basics of Julia and intermediate knowledge of another high-level programming language such as Python or R
TECHNIQUES
Intermediate data wrangling
Intermediate data visualization
Basics of bootstrapping
Basic usage of command pipelines
Basic usage of functions and control flow
Basic errors and correlation analysis
features
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