Program

Data Driven Decisions are the Future of Business.

Students will earn:

The Data Analytics/Big Data courses from the Data Analytics Academy is designed for professionals who see the business landscape shifting in favor of data-driven decisions. Our students learn how to conduct analyses of structured and unstructured data, interpret the results to extract business insights, and then communicate these results to management and other non-technical audiences. Students learn these techniques within a business-value framework featuring authentic, professional roles and projects.

Our courses are unique in that we teach the real-world skills needed to perform the role from day one. Our courses are technical, but also grounded in the needs of business. Students use sophisticated, powerful analytics tools while polishing necessary business skills like identifying the types of problems data analytics can solve and presenting effectively to stakeholders.

Mastery of a broad range of job-ready skills
End-to-end project experience working on real-world problems
A portfolio of professional quality work
A Certificate of Completion

Mentoring

Students work on authentic problems with an experienced mentor as their guide. Mentors don’t lecture but rather help students learn and develop skills as relevant to the work they are doing. Mentors provide in-depth feedback on student projects and make recommendations for improvement spurring additional student growth in the process.

Flexible Schedule

You work online, attend regularly scheduled meetings and make appointments with your mentor just as you would do with a real-world supervisor.

Students can choose to attend:

Full time (30 hours per week) for 20 weeks, or
Part time (15 hours per week) for 40 weeks.

Data Analysis Techniques

During the certificate program students will acquire mastery of many data analytic techniques. Each technique is taught within a business value framework and can be applied to almost any data set. Techniques include:

Acquire, prepare, process, and analyze extremely large data sets using cloud-based data mining methods
Translation of business and engineering objectives into data mining opportunities
Predictive Analytics using statistical machine learning techniques for classification and regression
Time Series Analysis
Assessing model performance through error analysis
Data Visualization
Algorithm selection

Tools

Our tool set is constantly evolving to keep pace with changes in the industry.

Currently we work with the following:

SQL
Amazon Web Services Elastic Map Reduce
Hadoop Streaming
Python, Jupyter Notebooks, and a wide range of Python libraries