Build with AI

This is a event on GEN Ai, this event will be giving information about

May 23, 1:00 PM – May 24, 11:16 AM



Key Themes

Cloud Study JamGoogle CloudMachine Learning

About this event

1. Prompt Engineering

1.1. Definition :  Prompt engineering involves refining input prompts to guide AI models like GPT-4 towards desired outputs, ensuring relevance and accuracy.

1.2. Importance: It aligns AI outputs with user expectations, enhances clarity, and mitigates biases, improving model reliability.

1.3. Example: Crafting a prompt tailored for a specific audience, like "Explain quantum computing to a high school student."

2. Machine Learning

2.1. Definition: Machine learning (ML) enables computers to learn and make predictions based on data, improving performance over time.

2.2. Key Concepts: Supervised, unsupervised, and reinforcement learning are fundamental approaches to training ML models.

2.3. Applications: ML finds applications in image recognition, predictive analytics, natural language processing, and recommendation systems.

3. Generative AI

3.1. Definition: Generative AI creates new content resembling its training data, using techniques like GANs, VAEs, and transformer models.

3.2. Techniques: Generative adversarial networks (GANs), variational autoencoders (VAEs), and transformer models facilitate content creation.

3.3. Applications: Generative AI contributes to content creation, data augmentation, and realistic simulations.


  • Vishal Kumar Mahato

  • Dhruba Singha Roy

    GDSC Lead

  • Swagata Das


  • Dhruba Singha Roy

    GDSC Lead


  • Dhruba Singha Roy

    GDSC Lead

  • Ashish kumar choudhary


    Web developer

  • Apurv Ajay Kumar

    Android developer

  • Sumit Kumar

    Project Manager


    Tech lead

  • Ishan Banerjee

    Digital management lead

Contact Us