Data Analytics Intensive
Demystify Data Analytics – Make Smarter Decisions for Your Business or Career.
For business owners and managers, sales and marketing directors, and professionals in any field who need to understand and use data to make effective decisions in their everyday work flow.
Join us for a four-day, bootcamp-style intensive.
Winter 2019 Dates
Friday & Saturday
January 11, 12, 18 & 19, 2019
10:00am - 4:00pm
835 Market Street, 6th Floor
Course Number: PM 9870
Class Number: 1062
Please note the Class Number: 1062.
Enter it in the Filter box on the Shopping Cart Class Schedule.
Data Analytics Intensive Overview:
Module 1: Data Analysis Using Excel
- Basic data manipulations: loading data to Excel, basic data manipulation using key-combinations
- Functions: arithmetic functions, IF and nested IF, SUMIF, logic functions (AND, OR, XOR, NOT), VLOOKUP, RAND, RANDBETWEEN, etc.
- Data filtering, sorting and pivot tables
- Charts and graphs: line charts, pie charts, column charts, scatter plots, histograms, pivot charts
Module 2: Visualization & Communication Using Tableau
- Tableau’s user interface
- Create important graphs in Tableau, such as scatterplots, bar charts, line charts, pie charts, treemaps, bubble charts, etc.
- Learn to identify/separate outliers using scatterplots, filters and groups
- Use trend lines and box plots to model your data
- Create calculated fields to enrich data analysis
- Blend multiple datasets
- Create table calculations for more advanced analytical tasks
- Use parameters to allow user interacting with the visualized data
- Create a dashboard and a data story
Module 3: MySQL for Data Storage and Manipulation
- RDBMS terminology
- Data types
- Import/export table data
- SQL queries
- The select statement
- The order by clause
- The group by clause
- Join tables
Module 4: Data Analysis Using Python
- Learn the basic features of Python: basic data structures such as list and dictionary, regular expressions, functions, file I/Os, etc.
- Get familiar with Pandas, a Python-based library for data preprocessing
If you have any questions, please contact program staff: