What will you learn in this Internship
- Predictive Maintenance in Smart Manufacturing Hands-on: How can machine learning models analyze IoT sensor data to predict equipment failures and reduce downtime?
- Customer Segmentation & Personalized Marketing in E-commerce Hands-onHow can clustering algorithms be used to segment customers based on their purchasing behavior, and how do these segments improve marketing strategies?
- Real-Time Sentiment Analysis for Brand Monitoring Hands-on How can Natural Language Processing (NLP) be used to analyze social media conversations in real time and track brand sentiment effectively?
- AI-Powered Fraud Detection in Financial Transactions Hands-on What machine learning techniques can detect fraudulent financial transactions, and how can a real-time fraud alert system be implemented?
- A/B Testing for Optimizing Online Ads & Website Performance Hands-on How can businesses use A/B testing to evaluate different website designs, ad campaigns, or UI elements, and what statistical methods ensure reliable results?
- Debugging & Performance Optimization in a Distributed System Hands-on How can engineers identify and resolve complex performance bottlenecks, memory leaks, and race conditions in a distributed microservices-based system?
- Architecting & Deploying a Scalable REST API for High-Traffic Applications Hands-on How can you design a REST API that ensures high availability, security, and low latency while handling thousands of concurrent requests?
- Large-Scale Code Refactoring for Maintainability & Performance Hands-on How can a legacy monolithic codebase be refactored using best practices to improve modularity, scalability, and maintainability without breaking existing functionality?
- Implementing a Secure & Scalable CI/CD Pipeline for DevOps Automation Hands-on How can a fully automated CI/CD pipeline be built to ensure secure, efficient, and zero-downtime deployments for a cloud-based application?
- Enhancing & Modernizing Legacy Code for Scalability Hands-on What strategies can be used to introduce new features into a legacy application while ensuring backward compatibility and gradually migrating to a modern architecture?
- Image Classification for Medical Diagnosis Hands-on: Train a CNN model to classify medical images (e.g., X-rays) using TensorFlow or PyTorch.
- Chatbot Development for Customer Support Hands-on: Build a simple chatbot using NLP libraries like spaCy or Hugging Face.
- Recommendation Systems for Streaming Platforms Hands-on: Implement a collaborative filtering algorithm to recommend movies or songs.
- Time Series Forecasting for Sales Data Hands-on: Use ARIMA or LSTM models to predict future sales trends.
- Hyperparameter Tuning for Model Optimization Hands-on: Use tools like Optuna or Grid Search to optimize model performance.
- SWOT Analysis for a Startup Hands-on: Conduct a SWOT analysis for a hypothetical startup and present actionable insights.
- Pricing Strategy for a New Product Hands-on: Use cost-based and value-based pricing models to determine the optimal price.
- Market Entry Strategy for a Global Brand Hands-on: Develop a market entry plan for a brand expanding into a new region.
- Supply Chain Optimization Hands-on: Use linear programming to optimize supply chain logistics.
- Crisis Management Simulation Hands-on: Role-play a crisis scenario (e.g., PR crisis) and develop a response strategy.
