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Coding Activities by Kieran

Life Expectancy Survey

You are a part of a survey team trying to analyze the life expectancy of different categories. A dataset of Life Expectancy for different countries for the year 2007 is provided to you. Various features may be a responsible factor for different life expectancies.

Life Expectancy Survey

You are a part of a survey team trying to analyze the life expectancy of different categories. A dataset of Life Expectancy for different countries for the year 2007 is provided to you. Various features may be a responsible factor for different life expectancies.

Iris Data Set Analysis

In this activity, you have to analyse Penguin Dataset

House Rent Prediction

In this activity, you will predict housing rent

Analysis of Blood Sugar Level

In this activity, students will analyse the blood sugar level between males and females.

Analysis of Blood Sugar Level

In this activity, students will analyse the blood sugar level between males and females.

Population Growth

In this Project, you have to find out the top 10 countries with the biggest population growth for the year 1952 - 2007 using Bar Plot.

Solve the Equation

In this activity, students will solve (y=2x+1 & y=2x^2+2) these two equations using Line Chart

Make a Time-Velocity Line Graph

In this Activity students will make a Time Velocity Graph

Data Cleaning

In this activity, you will be cleaning the USA housing dataset

Prompts with Clarity, Specificity & Contextual Information

"AI Prompt Engineering Tutorial" is an interactive learning activity that guides users in creating and refining prompts for AI models like Groq, Hugging Face or OpenAI's GPT. The tutorial focuses on teaching Clarity and Specificity and Contextual Information in crafting effective prompts for AI. Users will start by providing a vague prompt, then refine it to be more specific, and finally, add contextual information to see how the AI’s responses evolve with each iteration.

Single Image AI captions

In this activity, a local image file is processed through the robust "nlpconnect/vit-gpt2-image-captioning" model from Hugging Face. The model generates a descriptive caption by analyzing visual content in the image.