DRIPBL® Offerings

mission

To help and promote each and every K-16 students to invest in their curiosity and individuality and sharpen their soft and hard skills while promoting their success using DRIPBL methodology

vision

To enable each individual kid to know their passion, be successful and make lasting impacts in society, become more informed, responsible and socially intelligent and hence contributing to the future workforce by becoming entrepreneurs, innovators and visionaries.

Incubator Programs

Resources

Student Mentoring Insights

Camps/Workshops/Seminars

Counseling

Competitions

Tutoring

Personalized Mentorship

Future Scholars Journal

We support this mission through a range of offerings including Incubator Programs, Resources, Student Mentoring Insights, Camps, Workshops, Seminars, Counseling, Competitions, Tutoring, Personalized Mentorship, and the Future Scholars Journal. Each is designed to guide students every step of the way.

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Data Science and Data Analytics for Research Project

Dr. Calvin Williamson

Professor, Science and Math, State University of New York & Fashion Institute of Technology

Prof. Rajasekhar Vangapaty

Academic Advisor, Fashion Institute of Technology
State University of New York
Founding Member and President of Empowerment Skills International

Schedule: 2 days per week (Tuesday & Thursday)

 

What you’ll learn

Regression

  • Regression
  • Simple Regression
  • Multiple Regression
  • Applications
  • Conjoint Analysis

Introduction to Python

  • Google Colab Notebook
  • Variables, DataTypes
  • Lists, Strings
  • Functions

Machine Learning

  • Classification, Accuracy
  • Training, Testing
  • Decision Trees
  • Pandas, Dataframes
Register

Understanding AI and it’s proper use

Dr. Calvin Williamson

Professor, Science and Math, State University of New York & Fashion Institute of Technology

Prof. Rajasekhar Vangapaty

Academic Advisor, Fashion Institute of Technology
State University of New York
Founding Member and President of Empowerment Skills International

Schedule: 2 days per week (Monday & Wednesday)

 

What you’ll learn

Introduction to Python for Artificial Intelligence

  • Google Colab Notebook
  • Using LLM as Coding Assistant
  • Calculations
  • Variables
  • DataTypes
  • Lists
  • Dictionaries
  • Functions
  • Dataframes
  • f-Strings

Introduction to Large Language Models (LLMs)

  • LLM Examples (GPT, Claude, Gemini)
  • Completions, APIs
  • Prompting
  • Prompt Chaining
  • Roles and Personas
  • Chain of thought
  • Few-shot and zero-shot Learning
Register