Overview

A Hands on Training Program on

AI, MACHINE LEARNING, COMPUTER VISION, DEEP LEARNING and Nvidia DGX100 Supercomputer

Centre for Artificial Intelligence in Medicine, Imaging & Forensics (CAIMIF)

Starting from 01st February to 03rd May 2025 (40 Hrs Total) (Every Working Saturdays)

 

The "AI, Machine Learning, Computer Vision, Deep Learning and Nvidia DGX100 Supercomputer" training program is designed to empower participants with the essential skills and knowledge needed to excel in the fields of programming and artificial intelligence. This program offers a comprehensive introduction to Python, covering foundational concepts and practical coding techniques. Participants will also explore key AI, machine learning and deep learning principles, learning how to implement and apply these techniques to real-world problems. Through hands-on projects and guided exercises, attendees will gain practical experience in developing and deploying AI/ML models, equipping them with the tools to navigate the rapidly evolving tech landscape


AI,_MACHINE_LEARNING,_COMPUTER_VISION_BROCHURE.pdf

Objectives of Event

  • Foundational Python Skills: Equip participants with a solid understanding of Python programming basics, including data types, control structures, functions, and libraries, to ensure they can write and debug simple Python scripts. Exploratory Data Analysis: Understanding various types of data, techniques for pre-processing the data and visualizing the data using Matplotlib and Seaborn libraries and implementing statistical functions on data using python.
  • Machine Learning Foundations and Advanced Concepts: Provide an overview of key AI/ML concepts, such as supervised and unsupervised learning, model evaluation metrics, and common algorithms Linear and Logistic Regression, decision trees, random forests, support vector machines, K-means Clustering, Concept of dimensionality reduction and ensemble techniques
  • Practical Application of AI/ML Techniques: Enable participants to apply AI/ML techniques using Python libraries (e.g., NumPy, Pandas, Scikit-learn, TensorFlow) to solve real-world problems, including data preprocessing, model training, and evaluation.
  • Deep Learning Foundations and Advanced: Demonstrating neural networks using feedforward neural networks and backpropagation algorithm, understanding activation and cost functions, using artificial neural networks for regression and classification. Understanding and using Convolution neural networks for image classifications.
  • Hands-on Project Development: Guide participants through developing and deploying a simple Machine Learning (ML) project, from problem definition and data collection to model implementation and performance optimization, fostering practical experience and problem-solving skills.

Convener Details

  • Prof. Ashok Kumar, Head, Center for AI in Medicine, Imaging & Forensics Sharda University, ashok.kumar6@sharda.ac.in, 8294600356

Co-ordinators:

Speaker Details:

  • Prof. (Dr.) Vasudha Arora, Professor CSE, SSET & member CAIMIF, Vasudha.arora@sharda.ac.in
  • Dr. Shree Harsh Attri, Associate Professor CSE, SSET & member CAIMIF, Shree.harsh@sharda.ac.in