Online Data Science I: Essential Tools
DSI: Essential Tools Courses
February 04 - February 27

Grouped product items
Course Date Price Tax Quantity
DSI: Essential Tools Feb 04, 2020 $2,385.00 $0.00

Answer complicated questions, uncover greater insights and learn high-demand skills with Python and the power of data science. This 4-week course provides the foundational knowledge needed to move beyond the limitations of traditional spreadsheets to streamline and automate time-consuming tasks and encourage data-driven decision making.

The Essentials of Python for Data Science:

-Construct variables in Python and understand commonly used data structures
-Perform iterations in Python to easily apply a process over multiple values
-Encapsulate a process into a function to streamline and reduce repetition
-Utilize if/else statements to handle various cases and conditions
-Understand string data types and common operations applied to strings

Object-Oriented Programming (OOP) and NumPy and Pandas Python packages:

-Understand how OOP is implemented and used throughout Python and its packages
-Use NumPy ndarray data structures for fast, multidimensional numerical operations
-Utilize Pandas’ data structures and load CSV and Excel files as Pandas dataframes
-Combine tables across multiple spreadsheets into one dataframe
-Handle missing entries/data with Pandas, and utilize methods to replace missing values

Advanced Panda Techniques and Task Automation

-Use grouping operations in Pandas to create groups within a dataframe
-Use NumPy functions in Pandas and understand the connection between them
-Utilize manipulation and analysis tools in Pandas for times series
-Up and down sample time series to change frequency
-Understand time series transformations
-Visualize data analysis results using
     -Matplotlib to create line and scatter plots, histograms and bar charts
     -Seaborn package to generate statistically focused plots

Classes will be held from 7:00pm-9:00pm ET on Tuesdays and Thursdays.  

Classes will be held on the following dates: 2/4, 2/6, 2/11, 2/13, 2/18, 2/20, 2/25, 2/27

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