App Development Incubator

$999.00

App Development Incubator: Deadlines: Early Bird: February 28th; Late Registration: Until April 12th.

SKU: DRP-APPDEVELOP-007 Category:
This program empowers students to design, develop, and launch a fully functional mobile application using a structured, innovation-driven curriculum. Participants will learn to identify real-world problems, conduct market research, create user-centered designs, and build apps using industry-standard tools. The course also covers entrepreneurship fundamentals, including business planning and pitching strategies, to prepare students for global competitions and real-world impact. By the end of the program, students will have a complete app prototype and a business plan ready for submission to Technovation and other innovation and research challenges.

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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

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