Codersarts Blog.

Course:  LLM Foundational Course Level:  Medium Type:  Individual Assignment Duration:  5–7 days Total Marks:  100 Objective The objective of this assignment is to help you: Understand tokenization  and how it affects API costs Implement token counting  and cost calculation functions Build a vector database from scratch  using embeddings Perform semantic search  to retrieve relevant documents Create a simple RAG system  that answers questions using retrieved context Think pra

Course:  AI Backend Engineering with FastAPI  Assignment Type:  Applied Project Assignment  Difficulty Level:  Medium → Advanced  Estimated Time:  12–18 hours  Submission Mode:  Online LMS (Moodle / Canvas / Blackboard) Assignment Context Modern AI systems rarely consist of a single model endpoint. Instead, they involve multiple components working together such as: API orchestration model inference retrieval systems asynchronous processing background workflows logging and mon

Course:  AI Backend Engineering with FastAPI  Assignment Type:  Capstone Implementation + Architecture Report  Difficulty:  Medium → Advanced  Estimated Effort:  10–15 hours  Submission Platform:  LMS (Moodle / Canvas / Blackboard) Assignment Overview In this assignment, you will design and implement a production-style AI backend API  using the concepts introduced throughout this course. You will build a modular FastAPI system that integrates: LLM inference Retrieval-Augmente

Course: MCP Fundamentals  Level: Medium → Advanced Type: Individual Assignment Duration: 5–7 days Objective The objective of this assignment is to help you: Understand advanced agentic MCP capabilities (Sampling, Elicitation, Roots) Design multi-agent systems with appropriate orchestration patterns Analyze security implications of agentic workflows Implement human-in-the-loop design patterns Reason about long-running workflows and error handling Think critically about prod

Course: MCP Fundamentals  Level: Medium Type: Individual Assignment Duration: 4–5 days Objective The objective of this assignment is to help you: Understand the architectural problem MCP solves and why earlier approaches failed Master the distinction between Tools, Resources, and Prompts Apply primitive selection logic to real-world integration scenarios Design MCP Server architectures with appropriate primitives Analyze trade-offs in transport mechanisms and deployment m

Course: Chunking Strategies for Production RAG Systems Level: Medium → Advanced Type: Individual Assignment Duration: 5–7 days Objective The objective of this assignment is to help you: Understand and implement multiple chunking strategies Analyze trade-offs between different approaches Design a hybrid chunking pipeline Evaluate chunking quality in a Retrieval-Augmented Generation (RAG) context Think like an engineer building production-ready systems Problem Statement You a

Course: RAG Evaluation Level: Beginner to Medium Type: Individual Duration: 5 to 7 days Objective This assignment tests your ability to build the two foundational components of any RAG evaluation workflow: a golden dataset and a retrieval quality report. Without a golden dataset, no evaluation metric has meaning. Without retrieval evaluation, you cannot tell whether failures come from the retrieval stage or the generation stage. By completing this assignment, you will have a

Course: Docker for AI Apps Level: Beginner to Medium Type: Individual Duration: 5 to 7 days Objective This assignment tests your ability to work with Docker's core building blocks: running and inspecting containers, writing a production-ready Dockerfile, containerizing a Python AI application, and persisting data across container restarts using named volumes. By completing this assignment, you will have built and deployed a fully containerized multi-turn AI chatbot that retai

Course: RAG from Scratch Level: Medium to Advanced Type: Individual Duration: 7 to 10 days Objective This assignment tests your ability to build the retrieval and generation stages of a RAG pipeline from scratch. You will implement cosine similarity without external vector search libraries, build a similarity search function, design a grounding-focused prompt template, and assemble a complete end-to-end RAG system that retrieves context and generates accurate, grounded answer

Course: RAG from Scratch Level: Beginner to Medium Type: Individual Duration: 5 to 7 days Objective This assignment tests your ability to build the foundational stages of a RAG pipeline: loading documents, extracting clean text, attaching metadata, enriching documents with LLM-generated keywords, and splitting them into retrievable chunks. By completing this assignment, you will have built a reusable knowledge base preparation pipeline that you can apply to any document colle

Get expert help on 2026’s most in-demand skills including AI agents, LLM engineering, DevOps, and full-stack development. Codersarts offers assignment help, mentorship, and project support to help you build real-world applications faster.

As the demand for domain-specific AI chatbots grows in 2025, developers and tech companies are racing to build intelligent assistants...

In 2025, the future of content isn’t just written—it’s spoken. As audio-first platforms continue to grow, creators, educators, and...

In the age of generative AI, storytelling is evolving. Writers no longer have to work alone or hit creative blocks—now, they can...

Key Points Codersarts offers comprehensive help with classical physics assignments using Jupyter notebooks, essential for students and...

LangChain assignment or project help involves providing expertise and guidance to students , developers , or businesses working on...

Welcome to Codersarts! In this guide, we dive into  statistical analysis  of soccer match data, offering comprehensive  Data Science...

Welcome, fellow data and algorithm explorers! The journey through a Master's thesis in Data Science, Machine Learning, and AI can be...

Java is a popular programming language that is used for a variety of applications, including web development, mobile development, and...

Introduction Predictive modeling plays a crucial role in various industries, including data science. In this assignment, we will explore...