Excel for Data Science: Practice Tests for Skill Mastery.

Learn Python + Pandas for data cleaning, profiling & EDA, and prep data for machine learning & data science with Python

Created by: Maven Analytics
Empowering everyday people with life-changing data skills

Created by: Alice Zhao
Data Science Instructor at Maven Analytics

What Will I Learn?

• Master the core building blocks of Python for data science BEFORE applying machine learning algorithms
• Scope data science projects by clearly defining the goals, techniques, and data sources needed for your analysis
• Import and export flat files, Excel workbooks, and SQL database tables using Pandas
• Clean data by converting data types, handling common data issues, and creating new columns for analysis
• Perform exploratory data analysis (EDA) by sorting, filtering, grouping, and visualizing data to discover patterns and insights
• Prepare data for machine learning models by joining tables, aggregating rows, and applying feature engineering techniques

Requirements

• Jupyter Notebooks (free download, we'll walk through the install)
• Familiarity with base Python and Pandas is recommended, but not required

Target audience

• Data scientists looking to learn core techniques and best practices for data prep and exploratory data analysis
• Python users who want to build the core skills required before applying AI and machine learning models
• Data analysts or BI experts looking to transition into a data science role
• Anyone interested in learning one of the most popular open source programming languages in the world