SQL Level I | 8 Hours
This course covers the fundamentals of relational databases, Microsoft SQL Server, and the SQL database language. Begin writing SQL code, including SELECT statements. Learn to sort, filter, and format data and produce reports based on your queries.
SQL Level II | 8 Hours
Master views, subqueries, logic statements, and data conversions in this hands-on SQL course. Combine advanced SQL functions with fundamentals like inner and outer joins to proof your work.
SQL Level III | 8 Hours
Gain the skills to begin a career in database management. Master advanced SQL processes and controls, and create stored procedures and temporary tables.
PostgreSQL Bootcamp | 18 Hours
Explore, modify, and export data from databases in PostgreSQL. Learn foundation concepts like tables, data types, and queries, and advanced techniques like join statements, subqueries, and stored procedures.
Tableau Level I | 7 Hours
In this course, you will be introduced to the field of data visualization and the various tools Tableau Public offers. Through concepts and exercises, you will learn to identify datasets to connect to, explore, analyze, filter and structure your data to create your desired visualizations.
Excel for Business Fundamentals | 7 Hours
Learn all the basics to use Excel as your primary data processing tool. Create charts and tables, get started with formulas and functions, and format and print your output.
Intermediate Excel for Business | 7 Hours
Go from beginner to experienced professional: summarize data with Pivot Tables, write advanced functions including VLOOKUP, and learn techniques to expedite your workflow.
Advanced Excel for Business | 7 Hours
Become an Excel guru in this hands-on advanced training. You'll make functions more flexible, take Pivot Tables to the next level, automate tasks with macros, and learn advanced analytical tools.
Python for Data Science Bootcamp | 30 Hours
Learn the fundamentals of Python and object-oriented programming in this 5-day intensive course. You'll gain a solid understanding of Python, with a strong emphasis on using libraries and frameworks for data science.
Python Machine Learning Bootcamp | 18 Hours
Take a step beyond normal programming, into using algorithms that can independently learn patterns and make decisions. Machine learning skills are in high demand, as these algorithms now run the majority of trading on Wall Street and the product recommendations at big companies like Amazon, Spotify, and Netflix.
Python for Automation | 6 Hours
Learn Python to extract data from websites. Along the way, you’ll learn how to write loops so that your web scraping code can process a large number of pages.
SPSS Essentials (Private training) | 6 Hours
Learn to create a data file and enter data, conduct preliminary analyses, use graphs to describe and explore the data, manipulate the data, check the reliability of a scale, apply correlations, conduct significance tests, and perform regression analysis.
Introduction to SPSS for Data Analysis (Private Training) | 6 Hours
This course introduces how to present, analyze and interpret data using the statistical analysis software package SPSS. In virtually every field of work, being confident and competent in analyzing data and drawing conclusions is extremely helpful. You'll learn to develop those skills using SPSS.
Intermediate SPSS (Private Training) | 6 Hours
This is an intermediate level course designed to introduce students to advance techniques used in data analysis and database management. Focus is placed on the use of scripts, the appropriate use of parametric and nonparametric tests, regression analysis and Decision Trees. The incorporation of these techniques will provide the tools necessary to perform sophisticated analysis and management of data.
Introduction to R for Statistical Analysis | 14 Hours
The aim of this course is to provide an introduction to R, the environment for statistical computing and graphics. Statistical analysis will be performed through the graphic user interface called RCommander. The focus of the course will be on getting familiar with the R environment, to use R for manipulation and exploration of data, and to perform simple statistical analyses.