A portfolio is a way to show your work and standout.

5 data science project ideas to highlight in your portfolio

A data science portfolio should highlight job relevant skills that show you can perform day-to-day tasks of a data scientist.

1. Data Cleaning

According to a study published by Forbes, Data Scientists on average spend 80% of their time on preparing, managing and cleaning data. Data prep is a good way to show that you can work with various types of clean and unclean data.

Structure a data cleaning project:

1. Import data
2. Join multiple data sets
3. Detect missing values
4. Look for anomalies (1, 2, 3, “Sundus”?)
5. Impute for missing values
6. Data quality assurance

2. Exploratory Data Analysis

Exploratory Data Analysis (EDA) allows you to understand the data and make unintended discoveries through visualizations and data stats.

Framing an EDA project:

1. Formulate a hypothesis and relevant questions
2. Visualize data to test the hypothesis
3. Identify key trends in the data
4. Identify relationships between variables