This repository contains assignments and projects completed as part of the Cognizant training program.
- Variables, Operators, and Conditionals
- Loops
- Strings
- Data Structures
- Functions and Recursion
- Error Handling
- Eligible Elector - A program that checks if a user is eligible to vote based on age
- Password Strength Checker - A program that evaluates the strength of passwords
- Inventory Management - A system to manage product inventory
- Recursive Functions Menu - A menu-based program demonstrating recursive functions
- Calculator with Exception Handling - A calculator application with robust error handling
- Number Guessing Game - An interactive game where players try to guess a random number
- Study Planner (Capstone Project) - A comprehensive application for managing study tasks, tracking performance, and generating personalized study plans
- Tokenization and Embeddings - Exploring how text is tokenized and represented in LLMs
- Applying Concepts from Lessons - Implementation of prompt optimization techniques
- Fine-Tuning Theory and Practice - Reflection on fine-tuning techniques and applications
- Fine-Tuning Implementation - Python implementation of fine-tuning techniques
- Advanced Techniques, Ethics, and RLHF in LLMs - Analysis of advanced LLM techniques and ethical considerations
- Tokenization and Embeddings - Projects exploring tokenization, embeddings, and prompt crafting
- Tool Suggestion - Tool recommendation system using prompt engineering
- Mastering Prompt Optimization and Evaluation - Implementing effective prompt engineering techniques
- Comprehensive Fine-Tuning Task - End-to-end fine-tuning of an LLM for a specific domain
- Project Comprehensive RLHF and Ethical AI Design - Implementing RLHF principles with ethical considerations
- Application Development Capstone Project - Building an LLM-powered application with optimized prompts and fine-tuning
- Data Preparation - Data processing and preparation for model training
- Model Training - Fine-tuning and training of the language model
- Evaluation - Testing and evaluating model performance
- Application Development - Final application implementation
- Weather Prediction with Decision Trees - Implementing a decision tree model to predict weather conditions
- Clustering the Iris Dataset - Applying clustering techniques to analyze the Iris dataset
- Neural Networks and Deep Learning - Building a CNN for binary classification of spam messages
- AI-Powered Text Completion - Application for interacting with a pre-trained AI model to generate text
- Text Generation with LSTMs - Using LSTM networks to generate coherent text based on patterns learned from a text corpus
- LSTM Text Generation Class - Core implementation of the text generation model
- Train Script - Script to train the model on "The Old Worcester Jug" text
- Generate Script - Script to generate new text using the trained model
- Abstract Art Generation with GANs - Creating unique abstract art images using Generative Adversarial Networks
- Fine-tuning BERT - Fine-tuning a BERT model for specific NLP tasks
- AI-Powered Solutions - Comprehensive solution implementing multiple AI techniques
- Student Performance Predictor - Supervised learning to predict exam success
- Student Clustering Analysis - Unsupervised learning to identify student learning patterns
- Art Generation with GANs - Creating artistic designs using generative adversarial networks