RSS Featured Blog Posts
  • An overview of feature selection strategies
    Introduction Feature selection and engineering are the most important factors which affect the success of predictive modeling. This remains true even today despite the success of deep learning, which comes with automatic feature engineering. Parsimonious and interpretable models provide simple insights into business problems and therefore they are deemed very valuable. Furthermore, in many occasions […]
    Burak Himmetoglu
  • Helping Non-Profit Organizations as a Data Scientist
    Data Scientists are considered to be highly technical professionals and are typically seen exercising their talent in conventional business industries. However, Data Science is a problem-solving field. Therefore, it can be applied in any field that uses set of data and determines patterns to make decisions. For this reason, Data Scientists have the ability to […]
    VAMSI NELLUTLA
  • Free Book: Introduction to Statistics
    Online Statistics Education: A Multimedia Course of Study.  Project Leader: David M. Lane, Rice University. Content: Introduction Graphing Distributions Summarizing Distributions Describing Bivariate Data Probability Research Design Normal Distributions Advanced Graphs Sampling…
    Capri Granville
  • Introduction to Deep Learning
    Guest blog post by Zied HY. Zied is Senior Data Scientist at Capgemini Consulting. He is specialized in building predictive models utilizing both traditional statistical methods (Generalized Linear Models, Mixed Effects Models, Ridge, Lasso, etc.) and modern machine learning techniques (XGBoost, Random Forests, Kernel Methods, neural networks, etc.).…
    Vincent Granville
  • The Fourth Way to Practice Data Science – Purpose Built Analytic Modules
    Summary:  Purpose Built Analytic Modules (PBAMs) such as those for Fraud Detection represent a fourth way to practice data science, a new model for the good use of Citizen Data Scientists, and a new market for AI-first companies.   It appears that data science has…
    William Vorhies

Corporate Sponsorship

Divergence Academy – Data Science Immersive Program

Towards the end of every quarter along with Divergence Academy, we host an invitational data science talent competition. We invite recent graduates from Master’s level programs, twenty something talent early in data analytics and consulting careers, technical and data analytics talent in career transition, and even liberal arts graduates who have learned computer programming on their own or to gain entry level work. At minimum we recruit a pool of 20 participants that would be willing to participate in a 12 week data science immersive program. And, we select 8 to be sponsored with a full scholarship provided. Optional: sponsor a candidate that you choose.

Benefits to our Corporate Sponsors:

Invitation to Student Networking events

Personal Introductions to any you may be interested to hire

Optional Mentor Day, you can invite them to your workplace for a day

If you choose not to hire one of our students, we will provide access to our data science network for an additional 3 months to assist you in hiring a candidate for a reduced contingency fee of 10%

Cost to Sponsor:

$15,000

Student receives a NEW MacBook Pro, your company is acknowledged as a sponsor

Student receives full tuition ride, $13,300

Corporate Sponsorships are limited to two per company per cohort