GenAI Full Interview Questions | Docker Day 2 + FastAPI Explained Step by Step

Description

In this video, we cover complete deployment using Docker for GenAI applications along with a real interview discussion. We also include a live session with a student, where all major GenAI interview questions, system design topics, and syllabus are discussed in detail. You will learn how to package and deploy your FastAPI or RAG application using Docker in a production-ready way. This video is highly useful for: GenAI Interviews System Design Rounds Deployment Knowledge Backend + AI Integration 🔗 Reference GitHub Repo https://github.com/switch2ai 🧠 What You Will Learn Docker fundamentals Real interview questions for GenAI End-to-end deployment understanding Industry-level system design thinking 🚀 Docker Basics Docker is used to package your application along with all dependencies so it can run anywhere Core Components Docker File Step-by-step instructions to run application Docker Image Built application using Dockerfile instructions Docker Container Running instance of the application Real World Example Manufacturing a car Docker File Blueprint to build a car Docker Image Manufactured car Docker Container Driving the car 🌐 Host and Port Host Machine where application is running Port Access point to communicate with application Example http://127.0.0.1:8000 127.0.0.1 Localhost 8000 Port Real World Understanding Host Building address Port Door number ⚙️ Dockerfile Dockerfile is used to define instructions to build the application Important Instructions FROM Defines base image like Python version COPY Copies files from local system to container RUN Executes commands during build process CMD Default command to run application WORKDIR Defines working directory inside container Docker Workflow Set base image Set working directory Copy dependency file Install dependencies Copy application code Run application 📂 .dockerignore Used to ignore unnecessary files Example Cache files Virtual environments Test files 🧠 Why Docker is Important Ensures consistency across environments Eliminates dependency issues Easy deployment Scalable for production 🎤 Interview Session Highlight In this video, we also include a real student interview discussion where: Complete GenAI syllabus is covered Important interview questions are discussed System design concepts are explained Real-world expectations are shared 🔥 Key Topics Covered in Interview RAG architecture Embedding models Vector databases Retriever types LLM selection Deployment strategies Scaling GenAI applications 🚀 Key Takeaways Docker simplifies deployment Same application runs everywhere Essential for production systems Highly important for interviews 🔥 Hashtags #Docker #GenAI #AI #Deployment #FastAPI #MachineLearning #SystemDesign #Backend #InterviewPreparation #Switch2AI 🔍 SEO Tags docker tutorial docker for ai deployment genai interview questions docker fastapi deployment docker basics explained ai system design interview rag deployment docker backend deployment tutorial docker container explained ml deployment docker 🔍 SEO Tags (500 char) docker tutorial,docker for ai deployment,genai interview questions,docker fastapi deployment,docker basics explained,ai system design interview,rag deployment docker,backend deployment tutorial,docker container explained,ml deployment docker,docker for machine learning,genai deployment tutorial,Switch 2 AI