Analytics Training: May & June 2019
|
|
|
|
|
INTRODUCTION TO TABLEAU
May 2 & 3
This two-day training is designed for beginner Tableau users and anyone who works with data with or without technical or analytical backgrounds. Those with some prior Tableau experience will benefit from the many tips and trick covered in this training.
|
|
|
|
INTRODUCTION TO PYTHON
May 16 & 17
In this two-day course we will cover the basics of using Python for data science, including a mental model for the Python language, Importing and exporting data, Understanding dataframes and types of columns, Data wrangling with select, filter, column creation, aggregation, joins, and more.
|
|
|
|
INTERMEDIATE/ADVANCED TABLEAU
June 6 & 7
This two-day workshop on Tableau will cover intermediate and advanced topics. Attendees should have attended previous "Introduction to Tableau" trainings or have significant experience using Tableau in a professional environment. Course content will include advanced chart types and business dashboards, advanced calculations in Tableau, using calculations, parameters, and table calculations, and other topics.
|
|
|
|
|
INTRODUCTION TO MS POWER BI
May 9 & 10
This two-day introductory training will cover how to load data into PowerBI, create visualizations and dashboards, model large datasets, generate dynamic dashboards and share and deploy dashboards in business organizations. No prior experience is needed
|
|
|
|
DATA ANALYTICS IN EXCEL
May 23 & 24
This course takes students through hands-on examples in building dashboards, interactive decision support, data visualization theory and applications, advanced charting, and predictive analytics. Topics include descriptive prescriptive and predictive analytics and using special functions.
|
|
|
|
INTERMEDIATE PYTHON
June 27 & 28
In this course we will cover Python's powerful data science capabilities at an intermediate level, including control flow, writing functions, using python from the shell, plotting with user-friendly libraries, such as seaborn and plotly, and preview scikit-learn. Attendees should have attended previous "Introduction to Python" trainings or have experience using Python in a professional environment.
|
|
|
|
|
