Booz | Allen | Hamilton x Data Society
Extended Data Science Bootcamp

Hours of Instruction: 64 Hours
Duration of Bootcamp: 72 Hours
Modality: Virtual, Zoom classroom

Text Mining

Learn to prepare data for text mining. Integrate into commercial applications. Extract key summary metrics and words from a corpus of documents.

Model in Spark

Learn to optimize code and speed up data processing using Spark. Explore best practices and how to use distributed computing.

Click here to download syllabus
Download the FlexEd Funding Request
Who should enroll?

Intermediate Data Science Bootcamp

Who is this class for?
  • Students applying for this course should have demonstrable experience using Python to manipulate and visualize data and feel comfortable learning new packages and interpreting new code snippets.
  • Applicants should have a background of building and assessing the performance metrics of basic classification models and are looking to expand on this skillset.
  • This course is for professionals ready to take learning from the classroom to the “real world” and into advanced applied scenarios. Students in this course understand that working with applied/live datasets can present challenges that don’t exist in a controlled learning environment.
Suggested Hardware Setup

Although it is not a requirement, we strongly urge students to have a two-monitor setup to improve the virtual learning experience.

Certificate Requirements

Booz Allen and Data Society will enforce the following criteria to receive a course completion certificate:

  • Students will be required to attend at minimum 25 of the 32 live sessions. Please note: session recordings will be available for two weeks after the instruction date but will not count towards live-instruction attendance.
  • Capstone Projects will require a passing grade. For additional information/grading rubric criteria, please contact bah@datasociety.com

Extended Data Science Bootcamp

Please complete the following fields to process your payment for the Extended DS Bootcamp. FlexEd options for advanced funding or reimbursement are available. More information can be found in Degreed.

Advanced Classification

Learn to make your classification model perform better and choose your methods and parameters based on the problem at hand. Logistic Regression as it relates to neural networks. Ensemble methods using Random Forest.

Deep Learning

Learn the foundations of this complex and exciting topic including CNN & RNN. Build powerful predictive systems using deep learning. Automate the analysis of time-series data.

Questions? Get in Touch

Send us an email:

Booz Allen Hamilton

DataScience5K@bah.com

Or contact your Data Society representative:

Data Society

bah@datasociety.com

For urgent questions:

Call 202-670-6090