Welcome to CampusX's curated collection of comprehensive courses designed to help you master key technologies and concepts in AI, ML, Data Science, and more.
- Introduction to Generative AI with LangChain
- End-to-End Machine Learning Projects with AWS Sagemaker
- Time Series Forecasting Methods
- e-KYC Solutions Using Computer Vision
- SQL for Data Analysis and Problem Solving
- Emotion Detection with Convolutional Neural Networks (CNNs)
- Building End-to-End ML Systems with MLOps
- Advanced Deep Learning with PyTorch
- Credit Risk Modeling Techniques
- Leveraging LlamaIndex for Generative AI Tasks
- Object Detection using Deep Learning
- Retrieval Augmented Generation (RAG)
- Generative AI for Vision
- Building AI Agents
- Flask for Machine Learning
- Data Analysis using MS Excel
| Course Name | Course Description | Link |
|---|---|---|
| Emotion Detection using Deep Learning | Delve into deep learning techniques for detecting human emotions based on facial expressions. Includes essential theory, practical applications, and hands-on projects. | [Emotion Detection with CNNs](Emotion Detection using Deep Learning/README.md) |
| Gen AI Projects using LangChain | A comprehensive guide to building generative AI projects using LangChain, covering both fundamental concepts and intricate project designs. | [Introduction to Generative AI with LangChain](Gen AI Projects using Langchain/README.md) |
| Credit Risk Modeling using ML | Learn to develop machine learning models that accurately predict credit risk, featuring real-world datasets and techniques for predictive modeling. | [Credit Risk Modeling Techniques](Credit Risk Modeling using Machine Learning/README.md) |
| Deep Learning Projects using PyTorch | Gain hands-on experience building deep learning applications like machine translation and next-word prediction systems using PyTorch. | Link Placeholder |
| Building e-KYC System with Computer Vision | Build an e-KYC system using Computer Vision techniques, exploring identity verification and fraud detection use cases. | Link Placeholder |
| SQL Case Studies | Work through five real-world case studies to apply SQL skills in data analysis and problem-solving contexts. | Link Placeholder |
| Time Series Forecasting Project | Develop models for time series forecasting, using traditional statistical methods and modern ML techniques for predictive analysis. | Link Placeholder |
| Gen AI Projects using LlamaIndex | Explore LlamaIndex and its capabilities for AI project development, from basic setups to advanced generative AI solutions. | Link Placeholder |
| End-to-End ML Project using AWS Sagemaker | Learn how to build machine learning projects using AWS Sagemaker, covering all phases from data preprocessing to model deployment and monitoring. | Link Placeholder |
| Object Detection using Deep Learning | Dive into object detection techniques using deep learning frameworks to create AI-driven systems capable of identifying and classifying objects in real-time. | Link Placeholder |
| Generative AI for Vision | Deep dive into Stable Diffusion, GANs, Variational Autoencoders, and leveraging Hugging Face models to implement cutting-edge vision projects using Generative AI techniques. | [Generative AI for Vision](Generative AI for Vision/README.md) |
- Your Background: Are you a beginner or have prior experience in Data Science, AI, or relevant technologies?
- Your Goals: What do you aim to achieve? Are you learning for career advancement or personal interest?
- Course Sequencing: Some courses may build on others (e.g., Intro to Generative AI, followed by advanced AI courses).
- Prerequisites: Make sure to check if any courses have specific prerequisites to help you plan accordingly.
- Prioritize Your Interests: Start with topics that genuinely interest you.
- Assess Difficulty: If you’re a beginner, start with introductory courses.
- Check Descriptions: Ensure the course aligns with your goals by reviewing the descriptions and prerequisites.
- Time Commitment: Plan your schedule to ensure you can dedicate enough time to the course.
This repository is intended for educational purposes only. All content belongs to CampusX, and is designed to support learning and exploration. We encourage responsible use of the information provided. Neither the creators nor contributors are liable for any misuse or misinterpretation of the content in this repository.
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