G{Code} House

Fellows of G{code} House had to go through many weeks of learning about Data Analytics. Each week they were assigned different courses through Treehouse so they can build their skills week after week. These courses include: Spreadsheet Basics, Intermediate Spreadsheets, Data Visualization Foundations, Data Visualization with Google Sheets, Data Analysis Basics, SQL Basics, Practice Simple WHERE Clauses with SQL, Practice Column Selection and Aliasing with SQL, Modifying Data with SQL, Reporting with SQL, Querying Relational Databases, Python Basics, and Introduction to NumPy, Introduction to Pandas, Introduction to Data Visualization with Matplotlib, Analyzing Books with Panda, and Presenting an Analysis. Below is a more detailed breakdown of what each student learned in Treehouse's courses that were listed above. -Spreadsheet concepts and vocabulary -Importing data into a spreadsheet -Using functions and formulas to analyze data -Formatting spreadsheets -Spreadsheet best practices -Lookup Functions -Conditional Formatting -Pivot Tables -Data Validation -Define Data Visualization -Describe the difference between data and information -Recall that data visualization should tell a story and help users make decisions -List a number of charts and visualizations and describe their uses -Recall that data should be double-checked for accuracy -Recall that visualizations should never distort data -Recall that visualizations should never communicate using only color -Cleaning and preparing data in spreadsheets -Summarizing data with formulae -Normal distributions and standard deviations -Simple visualizations in spreadsheets -Presenting findings -Write SELECT statement to query data from a relational database -Select specific columns -Searching tables using `WHERE` -Filter by comparing values -Inserting rows of data -Updating data for specific entries -Removing data from any table -Understanding transactions for data integrity -Ordering, limiting and paging through a result set -Manipulating text -Working with numbers -Working with dates -What is a Relational Database? -Database Normalization -Database Keys -Table Relationships -Set Operations -Fundamental programming concepts -Input and Output -Conditional branching -Loops -Exception handling -Use the N-dimensional array to organize and report on data -Describe the fundamentals of Array Programming -Explore fundamental concepts and terminology -Create and explore the fundamental data structures of the pandas library -Use labels and indices to narrow data -Use common DataFrame exploration techniques -Recognize the importance of performing vectorized operations in place -Introduction to the Python matplotlib library -Uses and reasons behind the selection of a particular chart type -This course will introduce the user to the concepts of data visualization, which will help you understand business drivers and data trends -Explores graph customization to further enhance data reporting and communicating meaning -Analyzing books -Utilizing Pandas for analysis -Thinking through a project -Know who your stakeholders are -Decide on the best method for presenting your analysis -Create a story around your analysis