GenAI & AI Agents Hands-On Internship – Zero to Agent Builder
Go from AI beginner to building your own working AI agent—learn Python, prompting, APIs, RAG, tool calling and Agentic AI through live hands-on sessions and a final capstone project.
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Class scheduleSat, Sun
Sat, SunMeets
10Seats
3Modules
5Projects
₹17,700Incl. GST
Enrol · ₹17,700 incl. GST
10 seats left
Why learn live, with a cohort
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Live, mentor-led sessionsLearn in real time with daisywithai and a batch of peers, not alone with videos. Your trainer shares the class recording if you miss one.🔨
Real projects you shipBuild 5 hands-on projects that go straight into your public portfolio, reviewed by your trainer.🎓
Certificate + visibilityFinish to unlock a verifiable certificate, 5 exam passes and 5 ByteLabs projects, and learn in public to get noticed.What you will learn and build
The full curriculum, module by module, with hands-on project steps along the way.
1
Python + AI Foundations
Sat 2h + Sun 2h · Learn coding through practical AI-focused examples rather than only theory. Understand how a program thinks through input → logic → output; write and run Python programs; work with variables, strings, numbers and user input; build decision-making logic with conditions; automate repetitive work with loops; create reusable functions; organize information using lists and dictionaries; understand common errors and basic debugging. Hands-on builds: Smart Age Assistant, Eligibility Checker, Personal Task Manager and Daily Expense Analyzer. Finish by understanding where Python fits
Project
Build a Smart AI Study Assistant with Python
Build a working Python-based AI assistant that takes user questions, applies Python fundamentals such as variables, input/output, conditions, loops and functions, and connects to an LLM API such as Gemini. Learners will understand how Python communicates with an AI model, send prompts, process responses, handle basic errors and create an interactive command-line chatbot. By the end, they will have their first end-to-end Python + Generative AI project to showcase in their portfolio.
2
Data + Prompt Engineering
Applied Skills · Sat 2h + Sun 2h · Learn how Python and LLMs work together with real information. Read and process text and structured data; work with files, JSON, lists and dictionaries; clean and prepare information before sending it to an AI model; understand how LLMs interpret instructions and context; design effective system and user prompts; use zero-shot and few-shot prompting; create structured outputs; experiment with temperature and response control; identify hallucinations and improve unreliable responses. Hands-on build: Create a Prompt Lab where learners compare prompts, test outp
Project
Build an AI Data Analyst with Python + LLM
Build a practical AI assistant that reads structured data such as CSV or JSON, prepares the data using Python, and sends relevant information to an LLM for analysis. Learners will design effective prompts, use zero-shot and few-shot techniques, control AI output, handle structured responses, and generate useful summaries and insights from real data. By the end, learners will understand the complete Data → Python → Prompt → LLM → Structured Output workflow and have a portfolio-ready mini AI project.
3
APIs + RAG + AI Agents
AI Application Development · Sat 2h + Sun 2h · Move from simply using AI tools to actually building with them. Connect Python to Gemini through an API; understand API keys, requests, responses, JSON and error handling; create a conversational AI application; understand embeddings and semantic search visually; learn why RAG is needed and how grounding reduces unsupported answers; load your own documents and ask questions against them; understand the difference between a chatbot, RAG application, AI agent and Agentic AI system; introduce tools, memory, reasoning and workflows; build a simple age
Project
Build a RAG-Powered AI Support Agent
Build an end-to-end AI agent that connects Python with an LLM API, reads knowledge from documents, creates embeddings, retrieves relevant information using RAG, and generates grounded answers. Learners will understand API requests and responses, JSON, vector search, chunking, retrieval, tool calling and basic agent workflows. The final agent will be able to understand a user question → retrieve relevant knowledge → reason with an LLM → use a tool/API when required → return a contextual response, giving learners a practical portfolio-ready RAG + AI Agent application.
Project
AI Agent Capstone & Demo Day
Capstone · 4 hrs live + independent build time + mentor checkpoints · Instead of copying one predefined project, learners choose a real problem and build their own working AI solution. Start with problem identification and user requirements → design the workflow → select prompts, data and tools → build the Python/LLM solution → add RAG or agent capabilities where appropriate → test normal and failure scenarios → improve responses → document the architecture → maintain the project in GitHub → prepare a short product demo.
Capstone choices: AI Document Q&A Assistant, Resume & Interview Coach,
Project
Capstone Build + Portfolio & Career Launch
Build and present an end-to-end AI solution using Python, LLM APIs, Prompt Engineering, RAG and AI Agents. Complete a real-world capstone with mentor guidance, then package it with GitHub code, README, architecture diagram and demo. Get support to showcase the project effectively on your portfolio, resume, LinkedIn and GitHub, and confidently explain it in interviews.
Your trainer
D
daisywithai
Leads this live cohort on CareerByteCode: sessions, project reviews, and your path to the certificate.
Common questions
Is this live or recorded?
Live, scheduled sessions with your trainer and cohort. Your trainer adds the class recording, files and notes to the classroom afterwards, so you can catch up if you miss one.
What do I get at the end?
Finish the cohort to unlock a verifiable CareerByteCode certificate, 5 exam passes and 5 ByteLabs projects, plus your shipped project work in a public portfolio.
How is the price shown?
The price is the base plus 18 percent GST, shown all-in (₹17,700). You pay securely via Razorpay.
Do I need experience?
Pick a cohort at your level (Beginner here). Your trainer supports you through every module and project.