DIY Projects

Cognitive Wellbeing Monitoring

About the Project

Mental health includes our emotional, psychological, and social well-being. It affects how we think, feel, and act. Python comes with a huge number of inbuilt libraries. Many of the libraries are for Artificial Intelligence, Machine Learning, and Deep Learning. Learning Outcomes Understanding Data and Problem Statement in it. Step-wise code understanding, and steps undertaken to solve Problem and selecting suitable ML models.

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Gauging Customer Sentiment

About the Project

Sentimental reviews of customers towards the restaurant services and their like dislike are in 0 & 1. Python comes with a huge number of inbuilt libraries. Many of the libraries are for Artificial Intelligence, Machine Learning and Deep Learning. Learning Outcomes Understanding Data and Problem Statement in it. Step-wise code understanding and steps are undertaken to solve NLP(Natural Language Processing) Problem and select suitable ML models.

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Workforce Wellness Analytics

About the Project

Python comes with a huge number of inbuilt libraries. Many of the libraries are for Artificial Intelligence, Machine Learning and Deep Learning. Learning Outcomes Understanding Data and Problem Statement in it. Step-wise code understanding, and steps are undertaken to solve the problem and select suitable ML models.

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Bike Sharing Demand Prediction

About the Project

This project develops a machine learning model to predict bike-sharing demand in Seoul using Python. Leveraging datasets containing features such as weather conditions, temperature, humidity, wind speed, seasonality, holidays, and time-of-day, the model forecasts daily rental counts. The workflow includes data cleaning, feature engineering, and training models like linear regression, random forest, and gradient boosting. Evaluation metrics such as RMSE and R² score measure performance. The solution enables city planners and bike-sharing operators to optimize fleet management, reduce shortages, and improve customer satisfaction. It highlights how predictive analytics can support smart mobility and sustainable urban transportation systems.

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Cardio Vascular Risk Prediction

About the Project

This project develops a machine learning model to predict cardiovascular risk based on patient health data. Using Python libraries such as Pandas, Scikit-learn, and XGBoost, the system processes features like age, blood pressure, cholesterol levels, BMI, smoking habits, and medical history. The workflow includes data preprocessing, feature engineering, handling class imbalance, and model training with techniques such as logistic regression, random forest, and gradient boosting. Performance is evaluated using metrics like ROC-AUC, precision, and recall. The solution empowers healthcare providers with early risk detection, enabling timely interventions and improved patient outcomes through data-driven decision-making.

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Credit Card Fraud Detention

About the Project

This project builds a machine learning model to predict credit card defaulters using Python. By analyzing customer financial data such as income, spending behavior, credit history, outstanding balances, and payment records, the model identifies individuals likely to default. The pipeline includes data preprocessing, feature engineering, and model training using algorithms like logistic regression, decision trees, random forest, and XGBoost. Performance is evaluated with metrics such as accuracy, precision, recall, and ROC-AUC. The solution helps banks and financial institutions reduce risks, improve credit scoring systems, and make informed lending decisions, ensuring better financial security and customer portfolio management.

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Telecom Customer Retention

About the Project

This project builds a machine learning model to predict customer churn in the telecom sector using Python. By analyzing customer data such as demographics, usage patterns, billing details, contract type, and service quality, the model identifies factors influencing churn. The workflow includes data preprocessing, feature engineering, and training models like logistic regression, random forest, and XGBoost. Performance is measured using ROC-AUC, accuracy, and precision-recall metrics. The system helps telecom providers proactively identify at-risk customers, reduce churn through targeted retention strategies, and optimize customer satisfaction. It demonstrates the role of AI-driven insights in enhancing business sustainability and customer loyalty.

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Steganography- Hiding message in an Image

Network Stress Test Simulation

About the Project

NS2 stands for Network Simulator Version 2. It is an open-source event-driven simulator designed specifically for research in computer communication networks. This course will give you the necessary skills to perform Network and Security related hands-on. Learning Outcomes Install NS2 (Network Simulator) and NAM (Network Animator) in Ubuntu Operating System Create a Network topology and generate TCP and UDP Traffic Perform Denial of Service (DOS) attack on Network

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Keystroke Logging Demonstration

About the Project

This course will help you to understand the basics of keylogger and how can we capture keystrokes from a device and how can you develop a keylogger. Learning Outcomes Understand the basic concepts of keylogger Understand how to access keystrokes from system Understand the process of storing accessed keystrokes into file Implementation of keylogger Basics of Python GUI

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Steganography in Action

About the Project

About the Project Hiding data in images, also known as image steganography, is a technique used to conceal sensitive or confidential information within digital images. The process involves embedding the data within the pixels of an image, making it appear as a normal image to the human eye. The hidden data can be any form of digital information, such as text, files, or other multimedia content. Learning Outcomes Understand Steganography Techniques Perform Image Processing and Manipulation Understand the concept of Data Security and Encryption Implement steganography by hiding secret data in an image

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Perform DoS Attack

About the Project

This project involves simulating Denial-of-Service (DoS) attacks in a controlled environment to study their impact on networked systems and enhance cybersecurity measures. Using ethical hacking tools and Python scripts, the system generates traffic overload scenarios to observe server performance, response times, and potential vulnerabilities. The project emphasizes legal and safe experimentation within isolated test networks. Analysis of the results helps identify weaknesses in network configurations, firewall settings, and application resilience. The insights gained support the development of mitigation strategies, such as rate limiting, intrusion detection, and load balancing, strengthening overall system security against DoS threats.

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Develop a Secure Website that Prevents SQL Injection

About the Project

This project focuses on developing a secure web application that mitigates SQL injection and other common cybersecurity threats. Using secure coding practices, parameterized queries, and input validation, the system ensures that user inputs cannot manipulate the database maliciously. The platform includes features like user authentication, role-based access control, and secure data storage. Cybersecurity tools and libraries are integrated to detect vulnerabilities, monitor traffic, and enforce encryption for sensitive data. This project demonstrates how combining web development best practices with proactive cybersecurity measures can create robust, safe, and trustworthy web applications for users and organizations.

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Retail Insights from Superstore Data

About the Project

Data analytics (DA) is the process of examining data sets in order to find trends and draw conclusions about the information they contain. Learning Outcomes Data analytics , Types of data analytics, platforms for analytics Case Study – Data Analysis of Superstore data, ETL( Extract, Transform and Load ) operation , EDA (Exploratory Data Analysis) operation

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Healthcare Analytics for Doctor Visits

About the Project

Data analysis using Python tools involves several libraries and tools that provide powerful capabilities for working with data. Analyzing doctor visit data using Python tools can provide valuable insights into various aspects of healthcare. In this course, you will find explanations of Python libraries and examples of analysis techniques to effectively analyze doctor visit data. Learning Outcomes Understand the data science concepts and will be able to work on any kind of data set Differentiate terminologies, processes, tools, and technologies used for dealing with data Use the libraries such as NumPy and Pandas for data manipulation Visualize the data using clear and informative charts, graphs, and other visualizations.

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Car Market Trends Analysis with Car Dekho Data

About the Project

This course will help you to understand the basics of data analytics, pandas, numpy and matplotlib. Learning Outcomes Basics of data analytics , pandas , numpy and matplotlib Data analytics case study on car dekho

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Airbnb Hotel Booking Analysis

About the Project

This project performs a comprehensive analysis of Airbnb hotel booking data using Python to uncover trends and insights for hosts and stakeholders. By examining features such as booking patterns, customer demographics, seasonal demand, pricing, and property types, the project identifies factors influencing occupancy and revenue. Data preprocessing, visualization, and statistical analysis are performed using libraries like Pandas, Matplotlib, Seaborn, and Plotly. The analysis enables hosts to optimize pricing strategies, manage inventory, and improve customer satisfaction. This project demonstrates how Python-driven analytics can help the hospitality sector make data-driven decisions and enhance business performance.

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Exploring Global Terrorism Patterns & Trends

About the Project

This project analyzes global terrorism data to uncover patterns, trends, and insights using Python. Leveraging datasets like the Global Terrorism Database (GTD), the project examines factors such as attack types, target profiles, geographical distribution, and temporal trends. Data preprocessing, visualization, and statistical analysis are performed using Python libraries like Pandas, Matplotlib, Seaborn, and Plotly. Interactive dashboards and visual reports help identify hotspots, recurring tactics, and high-risk regions. The analysis supports policymakers, researchers, and security agencies in understanding terrorism dynamics, making informed decisions, and developing effective counter-terrorism strategies. This project demonstrates how data-driven insights can enhance global security intelligence.

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Building a Responsive Code Editing Experience with Bootstrap

About the Project

Bootstrap is the best framework for making a responsive webpage/website. In the course, we will be learning how to make an online code editor along with light/dark mode functionality. Learning Outcomes Design a Code Editor using Bootstrap. Implementation of Favicon and Bootstrap Icons. Get to know about DOM(Document Object Model) of JS and power of inspect while developing the web page. Implementation of dark mode in the code editor.

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Crafting Your Digital Identity - A Front-End Portfolio

About the Project

Bootstrap is the best framework for making a responsive webpage/website. In the course, we will also be learning other CSS & JavaScript libraries like – AOS (Animate on Scroll), animate.style and much more. Learning Outcomes Create a Webpage using Bootstrap and Real-time techniques used while designing it. DImport external Fonts, implementing Favicon and Bootstrap Icons. Implement various CSS & JS Libraries.

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Website/Application Replication

About the Project

This course will give you the necessary skills to develop your own website. Learning Outcomes Be aware of the Front End Development tools Get to know various tags used in HTML Understand how to use CSS in a webpage. Implement JAVASCRIPT in a webpage

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Password Generator Using JavaScript

About the Project

This project implements a web-based Password Generator using JavaScript to help users create strong and secure passwords. The application allows customization of password length and character sets (lowercase, uppercase, numbers, and symbols) to meet different security needs. It includes features such as real-time strength estimation, entropy calculation, copy-to-clipboard, and download options for generated passwords. Built with HTML, CSS, and JavaScript, the project showcases how client-side scripting can deliver a lightweight, interactive, and user-friendly tool for enhancing online security.

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Product Filtering in Ecommerce Website using JS

About the Project

This project develops a dynamic Product Filtering system for e-commerce websites using JavaScript. Users can filter products by categories, price range, brand, or rating, enabling quick discovery of relevant items. The system updates results in real-time without reloading the page, improving user experience and navigation efficiency. Built with HTML, CSS, and JavaScript, the project demonstrates how client-side scripting enhances interactivity and usability in modern e-commerce platforms.

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Sticky Notes Application using JavaScript

About the Project

This project creates a Sticky Notes Application using JavaScript to help users capture, organize, and manage quick notes digitally. Users can add, edit, delete, and drag notes on the interface, with data persistence using local storage. Built with HTML, CSS, and JavaScript, the application demonstrates how client-side scripting can deliver an interactive, user-friendly, and lightweight productivity tool.

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Develop a Smart Contract for Land Registry

About the Project

This project leverages Ethereum blockchain and smart contracts to build a decentralized land registration system. It ensures transparency, security, and immutability in recording property ownership and transactions. Land details such as owner information, area, location, and supporting documents are stored on-chain with references to IPFS for document storage. Smart contracts automate key processes like registration, ownership transfer, and dispute management, reducing the need for intermediaries and minimizing fraud. The system empowers government authorities, landowners, and buyers by providing tamper-proof records, faster transactions, and improved trust. It demonstrates blockchain’s potential in transforming land governance and real estate management.

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Develop a Centralised Application for Bank

About the Project

This project focuses on building a decentralized application (dApp) for the banking sector leveraging blockchain technology. The solution aims to ensure secure, transparent, and tamper-proof financial transactions without reliance on centralized intermediaries. Smart contracts automate core banking processes such as payments, lending, and settlements, reducing operational costs and improving efficiency. The dApp provides features like real-time transaction tracking, enhanced fraud prevention, and immutable record-keeping. By integrating blockchain’s distributed ledger, the system enhances trust between banks and customers. This project demonstrates how decentralized technologies can reshape traditional banking, fostering greater security, transparency, and financial inclusion in the digital economy.

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Develop a Blockchain based Healthcare Record

About the Project

This project focuses on developing a secure and decentralized healthcare records management system using blockchain technology. Patient data, including medical history, prescriptions, lab reports, and treatment details, is stored in a tamper-proof and transparent manner while ensuring privacy through encryption and controlled access. Smart contracts manage permissions, enabling patients to share records with doctors, hospitals, or insurers securely and instantly. The system eliminates duplication, reduces data breaches, and ensures interoperability across healthcare providers. By empowering patients with ownership of their medical records, the project enhances trust, improves decision-making, and demonstrates blockchain’s potential to revolutionize digital healthcare.

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Generative AI Text Summarization Using IBM Watsonx

About the Project

This project leverages IBM Watsonx’s generative AI capabilities to develop an advanced text summarization solution. By applying large language models, the system can process lengthy documents, articles, and reports to generate concise, accurate, and contextually relevant summaries. The solution supports extractive and abstractive summarization, ensuring flexibility based on user needs. Power BI integration enables visualization of summarized data for actionable insights. This project is valuable for professionals, researchers, and businesses who deal with large volumes of information, as it enhances productivity, accelerates decision-making, and demonstrates the practical application of AI in knowledge management and content optimization.

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Build a Chatbot using IBM Cloud

About the Project

This project focuses on designing and deploying an intelligent chatbot powered by IBM Watsonx Assistant. The chatbot leverages natural language processing (NLP) to understand user queries, provide accurate responses, and deliver a personalized conversational experience. It can be trained with domain-specific datasets, integrated with websites or applications, and customized to handle FAQs, support tasks, or transactional queries. With features such as intent recognition, dialogue flow design, and multilingual support, the chatbot enhances customer engagement and reduces response time. The project demonstrates how Watsonx Assistant simplifies chatbot creation while enabling businesses to improve efficiency, customer satisfaction, and user experience.

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ML Model Development using Watson Studio

About the Project

This project utilizes IBM Watson AutoAI to streamline the end-to-end process of machine learning model development. AutoAI automates critical steps such as data preprocessing, feature engineering, model selection, and hyperparameter optimization, enabling faster and more accurate outcomes. The platform generates multiple candidate models, evaluates their performance, and recommends the best fit for the problem at hand. Through its intuitive interface and automated workflows, even complex ML tasks become accessible to users with varying levels of expertise. The project demonstrates how AutoAI accelerates AI adoption, reduces development time, and delivers scalable, data-driven solutions for real-world business challenges.

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Unicorn Business Analysis

About the Project

This project leverages Microsoft Power BI to conduct an in-depth analysis of unicorn companies—startups valued at over $1 billion. The solution integrates datasets covering funding rounds, valuations, sectors, geographies, and growth patterns. Through dynamic dashboards and interactive visualizations, users can explore investment trends, sectoral strengths, and global distribution of unicorns. Drill-down capabilities provide insights into individual companies, investor networks, and market shifts. The project supports stakeholders such as investors, policymakers, and entrepreneurs in identifying opportunities, assessing risks, and understanding the evolving startup ecosystem. It demonstrates the power of data visualization in driving strategic business insights.

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Healthcare Data Driven Analytics

About the Project

This project applies Microsoft Power BI to transform complex healthcare data into actionable insights for better decision-making. By integrating datasets on patient records, hospital performance, resource utilization, treatment outcomes, and cost analytics, the project builds intuitive dashboards that provide real-time visibility. Stakeholders can track key health indicators, identify trends, and address inefficiencies through interactive visualizations. The system supports doctors, administrators, and policymakers in making evidence-based decisions that enhance patient care, optimize resource allocation, and improve operational efficiency. Ultimately, the project demonstrates how data-driven insights can strengthen healthcare delivery and drive measurable improvements in public health outcomes.

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Exhaustive Analysis of Indian Agriculture Sector Using Power BI

About the Project

This project uses Microsoft Power BI to deliver a comprehensive analysis of India’s agricultural sector, a vital contributor to the economy and rural livelihood. By integrating datasets on crop production, rainfall, fertilizer usage, subsidies, and market trends, the project builds interactive dashboards that provide clear, data-driven insights. Users can drill down by crop, region, or timeframe to identify trends, challenges, and opportunities. The analysis supports policymakers, researchers, and agribusinesses in making informed decisions, improving resource allocation, and enhancing food security. It highlights how data visualization can drive sustainable growth in Indian agriculture.

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