Join us for exciting AI and ML events, workshops, and competitions organized by our club.
Introduction to Generative AI with Google Cloud
This session provided a beginner-friendly introduction to Generative AI
and how it can be implemented using Google Cloud tools. Participants
gained insights into the fundamentals of Gen AI & its real-world
applications.
Learn more
September 22, 2023
Embedded ML with Nvidia Jetson Nano for Faculties
This session was designed to introduce faculty members to the world of
Embedded Machine Learning using the NVIDIA Jetson Nano, a powerful
edge AI platform, under the Nvidia Academic Hardware Grant Program.
Learn more
June 20, 2023
High Performance Computing (HPC) Workshop
This hands-on workshop was focused on introducing participants to the
world of High-Performance Computing (HPC) — a critical domain that
powers large-scale scientific research, simulations, and data-intensive
computations.
Learn more
March 11-12, 2025
Embedded ML with Nvidia Jetson Nano for Students
This hands-on workshop introduces students to the exciting field of
Embedded Machine Learning using the powerful yet compact NVIDIA
Jetson Nano platform. Designed as a recurring event, it is conducted at
regular intervals.
Learn more
Docker Foundations
This online workshop provided a beginner-friendly introduction to
Docker, one of the most widely used containerization platforms in
modern software development.The session focused on helping
participants understand how Docker simplifies application deployment.
Learn more
February 15, 2025
Peer-to-Peer Learning Sessions on Machine
Learning
These weekly peer-to-peer learning sessions are designed to help
newcomers build a strong foundation in Machine Learning through
interactive, beginner-friendly lessons.
Learn more
Embedded Machine Learning with Nvidia Jetson Nano
Peer learning workshop series on Embedded Machine Learning using the NVIDIA Jetson Nano — hands-on sessions focused on edge AI and practical deployments.
Learn more
September 15-16, 2025
Introduction to Generative AI with Google Cloud
Generative
AIGoogle
CloudVertex
AICloud-Based
AI
September 22, 2023
Room 638, AI & ML Lab, CSE Department
Workshop Overview
This session provided a beginner-friendly introduction to Generative AI
and how it can be implemented using Google Cloud tools. Participants
gained insights into the fundamentals of Gen AI, its real-world
applications, and how Google Cloud’s platform — including Vertex AI
and pre-trained models — supports the development of powerful AI
solutions.
Topics Covered
History of GenAI
Classical ML Approach
What are LLMs?
Evolution of Cloud ML APIs
GenAI on Google Cloud
Vertex AI Integration
Workshop Presenter
This event was presented by Harshul Yagnik, who is working as an
assistant professor in the department of computer science engineering
at Charotar University of Science and Technology. He has more than 12
years of academic experience. He has done a master of engineering in
signal processing and communication and presently pursuing a Ph.D. in
the area of computer vision in part-time mode.
Embedded ML with Nvidia Jetson Nano for Faculties
Embedded
Machine LearningJetson
NanoEdge
AIAI on
Embedded Systems
June 20, 2023
Room 638, AI & ML Lab, CSE Department
Workshop Overview
This session was designed to introduce faculty members to the world of
Embedded Machine Learning using the NVIDIA Jetson Nano, a powerful
edge AI platform, under the Nvidia Academic Hardware Grant Program.
The workshop aimed to introduce the participants to the fundamentals of
embedded machine learning and provide them with practical experience
in using the Nvidia Jetson Nano platform for developing machine.
Topics Covered
Introduction to Jetson Nano and its architecture
Basics of Embedded Systems and their role in AI
Setting up Jetson Nano for development
Working with Python, OpenCV, and TensorFlow Lite on Jetson Nano
Deploying pre-trained ML models on the device
Real-time object detection and image processing
Workshop Presenter
This event was presented by Harshul Yagnik, who is working as an
assistant professor in the department of computer science engineering
at Charotar University of Science and Technology. He has more than 12
years of academic experience. He has done a master of engineering in
signal processing and communication and presently pursuing a Ph.D. in
the area of computer vision in part-time mode.
High Performance Computing (HPC) Workshop
High
Performance ComputingParallel
ProcessingMPI and
OpenMPHPC
ClustersMulti-GPU
Training
March 11-12, 2025
Lab 323A, A6 Building, CSPIT
Series Overview
This hands-on workshop was focused on introducing participants to the
world of High-Performance Computing (HPC) — a critical domain that
powers large-scale scientific research, simulations, and data-intensive
computations. The session aimed to provide both conceptual clarity and
practical experience with HPC tools, systems, and applications.
This workshop helped participants understand how massive
computational tasks are efficiently distributed across systems and how
they can leverage HPC for research, analytics, or high-demand machine
learning workloads. It served as a great starting point for those
interested in the intersection of computer science and large-scale
computation.
Topics Covered
Introduction to HPC
Understanding Parallel Processing
Architectiure of HPC and Supercomputers
Shared Memory Parallelism with OpenMP
Distributed Memory Parallelism with MPI
GPU Programming with Cuda
Multi GPU Training with PyTorch
Session Leaders
Mr. Harshul Yagnik, Assistant Professor, CSE Department, CSPIT
Dr. Amit Thakkar, Professor and Head, CSE Department, CSPIT
Dr. Ritesh Patel, Professor, CSE Department, CSPIT
Embedded ML with Nvidia Jetson Nano for Students
Embedded
Machine LearningJetson
NanoEdge
AIAI on
Embedded Systems
Dates organized
March 25, 2023
July 10-12, 2024
July 24-26, 2024
January 2-3, 2025
September 15-16, 2025
Locations
Lab 324D, A6 Building, CSPIT
Room 633 & 634, CSE Labs, A7 Building, CSPIT
Workshop Overview
This hands-on workshop introduces students to the exciting field of
Embedded Machine Learning using the powerful yet compact NVIDIA
Jetson Nano platform. Designed as a recurring event, it is conducted at
regular intervals to ensure that a wider group of students get the
opportunity to participate and benefit from practical exposure to AI at the
edge.
The primary objective of this workshop is to bridge the gap between
classroom concepts in machine learning and their practical, real-world
applications. By working directly with the Jetson Nano — a popular
platform for developing edge AI applications — students learn how
artificial intelligence can be deployed on resource-constrained, lowpower embedded systems.
Participants gain valuable experience in setting up the development
environment, running lightweight ML models, and implementing real-time
computer vision tasks such as object detection using tools like Python,
OpenCV, and TensorFlow Lite. The workshop also highlights how
Embedded AI is used in modern applications such as IoT, surveillance,
robotics, and smart automation.
Key Topics
Overview of Jetson Nano
Introduction to Embedded Syetems and Edge AI
Getting Started with Jetson Nano Setup and development Environment
Running Python, OpenCV & Lightweight ML Models
Basics of real-time computer vision and object detection
Applications of Embedded ML in IoT, automation and Smart Devices
Workshop Presenter and Guide
This event series is presented & guided by Harshul Yagnik, who is
working as an assistant professor in the department of computer science
engineering at Charotar University of Science and Technology. He has
more than 12 years of academic experience. He has done a master of
engineering in signal processing and communication and presently
pursuing a Ph.D. in the area of computer vision in part-time mode.
Student Volunteers
Harshil Mistry (D24CS112)
Meet Borkhatariya (D24CS110)
Jay Rathod (D24CS116)
Dharmil Gadhiya (D24CS118)
Aum Barai (22AIML002)
Yuvrajsinh Bodana
Apurv Chudasama (22CS016)
Melita Castelino
Meet Radadiya (22AIML042)
Yash Nashit (22CS043)
Krushna Parmar (22AIML028)
Docker Foundations
DockerContainerizationDevOps
February 15, 2025
Online Mode
Session Overview
This online workshop provided a beginner-friendly introduction to
Docker, one of the most widely used containerization platforms in
modern software development. The session focused on helping
participants understand how Docker simplifies application deployment,
increases development speed, and enhances portability across systems.
The workshop was aimed at students and developers who wanted to get
started with containerization and explore how Docker can improve
project workflows, reproducibility, and scalability.
Topics Covered
What are Dockers?
Running and Managing Docker Containers
Writing Docker Files
Building and Debugging Containers
Netwworking and Data Persistance
Delivered by
Mr. Akshat Rajpoot – Software Engineer at Motorola Solutions
Student Coordinators
Aum Barai (22AIML002)
Apurv Chudasama (22CS016)
Peer-to-Peer Learning Sessions on Machine Learning
Peer
LearningMachine
Learning Basicsbeginner-friendly
ML
Every Week
Lab 637, CSE Labs, A7 Building, CSPIT
Workshop Overview
These weekly peer-to-peer learning sessions are designed to help
newcomers build a strong foundation in Machine Learning through
interactive, beginner-friendly lessons. Led by experienced senior
members of the AIML club, the sessions focus on creating an open and
collaborative environment where students can freely ask questions,
share ideas, and learn by doing.
Key Highlights
Introduction to Core ML Concepts
Understanding key Algorithms
Introduction to Data Preprocessing, Model evaulation & Performance Metrics
Hands-on Coding Exercises using Python and ML Libraries
Guidance on real world mini ML Projects
Regular Q&A, problem solving and discussion sessions
Exploring Kaggle, Google Colab and other ML Project Workflows
Embedded Machine Learning with Nvidia Jetson Nano
Embedded Machine LearningJetson NanoPeer Learning
15th & 16th September, 2025 — 4:30 PM to 6:30 PM
Lab no. 324(D), A6 Building, CSPIT
Workshop Overview
A two-day, hands-on workshop for 2nd year CSE students held on 2nd & 3rd January 2025 (4:30 PM — 6:30 PM). The workshop received 33 registrations, with 27 participants attending on Day 1 and 24 participants on Day 2. Sessions were conducted in small teams (groups of 3), each team provided a Jetson Nanokit and a dedicated workstation. The workshop was led by student facilitators Apurv Chudasama and Meet Radadiya, with technical guidance from Harshul sir.
Day 1 — January 2, 2025
The first day focused on introducing the Jetson Nano platform and core machine learning classification concepts. Meet began with an overview of Jetson Nano — its applications in IoT and embedded systems, hardware features, communication ports, and carrier board — and demonstrated device setup and configuration. Apurv followed with an accessible session on classification in machine learning: why it matters, common use-cases, and practical implementation steps. By the end of Day 1, participants were comfortable with device setup and the basics of ML classification.
Day 2 — January 3, 2025
Day 2 delved into more advanced computer-vision topics. Meet introduced object detection — practical applications and how to implement it on Jetson Nano. Apurv presented semantic segmentation, explaining its role in image analysis and differences from object detection. Later, Harshul sir demonstrated Monodepth (single-image depth estimation) and concluded with live demos including pose estimation and background removal. The day emphasized real-world workflows and showed how embedded ML pipelines are built end-to-end. Participants were encouraged to pursue the NVIDIA course for deeper learning.
Workshop Leads & Organizers
Workshop Leads: Apurv Chudasama and Meet Radadiya
Technical Guide: Harshul Yagnik
Student Organizers & Volunteers: Meet Borkhatariya, Harshil Mistry, Dharmil Gadhiya, Jay Rathod, and others from the AIML Club
Outcomes
In-depth understanding of embedded machine learning and model deployment on devices like Jetson Nano.
Hands-on ability to set up a hardware + software environment for edge AI projects.
Familiarity with real-world use-cases and applications of embedded ML in IoT and robotics.
Motivation and readiness among students to start their own projects in IoT, embedded systems, and ML.
Key Topics Covered
Jetson Nano hardware overview and device setup
Machine learning classification — concepts and practical implementation
Object detection on edge devices
Semantic segmentation and image analysis
Monodepth (single-image depth estimation)
Pose estimation and background removal demos
End-to-end workflow for deploying lightweight ML models on Jetson Nano
