FutureImpactInitiative

Program Overview

Nexus AI

The Nexus AI Program is a 10-week initiative mentored by domain specialistsdesigned to equip students with the skills to apply AI toward research and social good projects that serve a meaningful purpose towards the community.

Students will be able to participate in research conferences for cash prizes, Apple products and tech gadgets, and the chance to join our research lab and work with university researchers. Apply now!

See more details about our program here!
Complete our Free Pre-Coursework Now!

Apply now for FREE!

Application Form

About the program:

  • 10 Week Program
  • 8 Async ML Readings; 8 DL Lectures by Reputed PhD/Grad Students; Projects & Assignments
  • 24+ Total Hours of Instruction (3-hr lectures + 1-hr office sessions)
  • Present Research Poster & Presentation @ Nexus AI Research Conference (NARC)
  • Compete @ NARC for Prizes, Free Publication, & Research Internship at 1 of our Labs!
  • Application Required – No Application Cost. $700 Fee Once Accepted Into The Program
  • Prerequisites: Recommended Completion of Pre-Coursework Material

Program Syllabus

Pre-Coursework

  • Asynchronous
  • Python
  • Preprocessing Libraries
  • PyTorch Basics
  • Concepts & Math of ML/DL
  • Assignments & Mini-Projects
Curriculum

Phase One
DL Lectures

  • Weekly 3-Hour Lectures
  • Neural Network Architectures
  • Computer Vision, NLP, LLMs
  • Mini-Projects & Practice
Curriculum: Nexus AI Our Instructors: Nexus AI

Phase One
ML Readings

  • Weekly Readings
  • Scikit-Learn
  • Regression
  • Classification Algorithms
  • Clustering Algorithms
  • Mini-Projects
Curriculum: Nexus AI

Nexus AI Pre-Coursework

Published and open to everyone!

Join the Canvas LMS Course!

This content is designed to be completed asynchronously before the start of the Nexus AI program.

Completion of pre-coursework will ensure that students will be well-versed in fundamental skills prior to the instruction in Phase One.

Section 1 | Essentials of Python
  • Learn fundamentals of Python!
  • Complete problem sets!
  • Apply concepts to mini-projects!
  • Variables & Data Types
  • Simple Data Structures & Print Statements
  • Operators
  • Conditional Statements
  • Loops
  • Exceptions
  • Functions
  • Classes & Objects
Section 2 | Essentials of MatPlotLib & Pandas
  • Understand data preprocessing!
  • Create graphs using PyPlot!
  • Understand Pandas DataFrames!
  • Complete problem sets!
  • Apply preprocessing to mini-projects!
  • PyPlot Basics
  • Various Graphs in MatPlotLib
  • Pandas Basics
Section 3 | Essentials of NumPy
  • Learn key functionalities of NumPy!
  • Understand how to use NumPy for efficient numerical computations!
  • Understand basics of linear algebra!
  • Complete problem sets!
  • NumPy Arrays
  • Mathematical Operations
  • Utility Functions in NumPy
  • Intro to Linear Algebra
Section 4 | Introduction to Machine Learning
  • Understand ML & DL!
  • Learn fundamental concepts!
  • What is ML? DL? AI?
  • Fundamental ML Concepts
  • Types of Machine Learning
  • Fundamentals of Neural Networks
Section 5 | Essentials of PyTorch
  • Learn fundamentals of PyTorch!
  • Understand importance of GPUs!
  • Create tensors in PyTorch!
  • Implement neural networks!
  • Complete problem sets!
  • Intro to PyTorch & GPUs
  • Tensors in PyTorch
  • Neural Network Operations