AI engineering programs for college students

5XMinds

From Python basics to AI agents you can ship, in 4 to 6 weeks.

Practical batches on LLMs, RAG, LangChain, LangGraph, Hugging Face, open-source and frontier models. You write code in every session, on your own laptop, with a mentor beside you.

View the curriculum Book the 3-day workshop

4–6 weeksprogram length

4–6 hrsper practical session

Fri–MonFri · Sat · Sun · Mon

3 dayshands-on workshop

02The gap

College teaches how AI works. Recruiters hire students who have built with it.

Syllabus

Course content trails the industry

Agents, RAG and LangGraph went from research papers to job descriptions in about three years. Most college courses have not caught up yet.

Hiring

Recruiters ask to see projects

A GitHub repo with a working RAG app and a live demo link says more than a list of completed courses.

Interviews

The vocabulary is a filter

Interviewers check whether you can talk about tokens, embeddings, evals, latency and hallucinations with confidence.

5X Minds closes that gap with practical sessions on the tools companies use today, and a portfolio of projects by the final day.

03What you'll learn

The full modern AI stack, hands-on.

Python for AI

Notebooks, NumPy, pandas, calling APIs and writing clean, reusable scripts.

Python 3Jupyterpandas

LLM fundamentals

Tokens, embeddings, attention, context windows, temperature and prompting patterns.

tokensembeddingsprompts

GPT & frontier models

Build with GPT, Claude and Gemini APIs. Function calling, structured output, cost and latency.

OpenAIClaudeGemini

Hugging Face & open source

Run Llama, Mistral, Qwen and Gemma locally or in Colab, and choose the right model from the Hub.

TransformersOllamaHF Hub

RAG

Chunking, embeddings, vector databases and retrieval checks, so answers come from your documents.

FAISSChromarerankers

LangChain

Chains, prompt templates, retrievers, tools and output parsers that turn a model into an app.

LCELretrieverstools

LangGraph & agentic AI

Stateful graphs, tool-using agents, memory, human-in-the-loop steps and multi-agent teams.

LangGraphMCPagents

Datasets & fine-tuning

Collect, clean and label training data, fine-tune small models with LoRA, then measure the result.

datasetsPEFTLoRA

Image models

How diffusion works, Stable Diffusion, ControlNet and vision-language models that read images.

diffusersSDXLVLMs

AI-assisted coding

Pair-program with Claude Code, GitHub Copilot and Cursor, then review and test what the AI writes.

Claude CodeCopilotCursor

Deploy & share

Put your project on a public link with a simple UI that recruiters can open and try.

GradioStreamlitHF Spaces

Industry language & pitching

Explain your work like an engineer and pitch it like a founder, from evals and guardrails to demo day.

evalsguardrailsdemo day

04The roadmap

Six weeks, one skill stacked on the last.

Week 1

Setup & Python for AI

Install the toolchain, refresh Python and start coding with an AI assistant.

Week 2

LLMs & frontier models

How LLMs work, prompting, and the GPT, Claude and Gemini APIs.

Week 3

Open source & Hugging Face

Run open models locally, Transformers pipelines and model selection.

Week 4

RAG with LangChain

Embeddings, vector stores and a chatbot over your own documents.

Week 5

Agents with LangGraph

Tools, memory, multi-agent workflows and how to evaluate them.

Week 6

Fine-tuning, images & demo day

LoRA on your dataset, image models, deployment and your capstone pitch.

The 4-week Sprint follows the core path through Python, LLMs, RAG and agents. The 6-week Deep Track adds open-source models, fine-tuning, image models and demo day.

05Programs & schedule

Pick the pace that fits your semester.

AI Kickstart Workshop

3days · 4–6 hrs a day

LLM and prompting basics
GPT, Gemini and open models, hands-on
AI coding tools set up on your laptop
Build your first RAG chatbot

Best for: first- and second-years, or anyone who wants a fast, practical start.

4-Week Sprint

4weeks · 4–6 hrs a session

Python for AI
LLMs and frontier model APIs
RAG with LangChain
Your first LangGraph agent
One capstone project

Best for: students who want job-ready AI basics in one month.

6-Week Deep Track

Most complete

6weeks · 4–6 hrs a session

Everything in the Sprint
Hugging Face and open-source models
Datasets and LoRA fine-tuning
Image models and deployment
Career launchpad and demo day

Best for: final-years aiming for AI internships and roles.

MONTUEWEDTHUFRISATSUN

Sessions run on Friday, Saturday, Sunday and Monday, 4–6 hours each, so they fit around college weekdays. Every session is practical, with laptops open.

Concept→Live build→Your lab→Show & review

06Your setup

Bring your laptop. We'll help you get the credits.

Bring your own laptop

OS: Windows 10/11, macOS or Linux
Memory: 8 GB RAM minimum, 16 GB recommended
Storage: 20 GB free space
GPU: Not required. Heavy training runs on free cloud GPUs.

In the first session we install Python, VS Code, Git and an AI coding assistant together, so nobody falls behind on setup.

Free tiers & student credits we'll help you claim

Google ColabFREE GPU

Cloud notebooks with GPU time for training labs.

Kaggle NotebooksFREE GPU

Weekly GPU hours and thousands of public datasets.

Hugging FaceFREE TIER

Model hub, datasets and Spaces to host your demos.

Google AI StudioFREE TIER

A Gemini API key to build with a frontier model.

GroqFREE TIER

A fast API for open models such as Llama.

GitHub Student PackSTUDENT

GitHub Copilot for verified students, plus partner offers.

Azure for StudentsSTUDENT

Cloud credit for verified students, no credit card needed.

Ollama & LM StudioLOCAL

Run open models on your own laptop, offline and free.

Free tiers and student offers change often. We check what's available at the start of every batch and help you sign up where you're eligible.

Open-source toolkit

VS CodeGit & GitHubJupyterOllamaLangChainLangGraphTransformersPEFTChromaFAISSGradioStreamlit

07Career launchpad

Skills get you ready. We help recruiters find you.

Professional resume

An ATS-friendly resume written around your AI projects, with results recruiters notice.

Naukri profile setup

Headline, key skills and project sections tuned to the searches recruiters run.

LinkedIn setup

Headline, About section, featured projects and a simple plan for sharing your work.

Your own website

A personal portfolio site on your own link, showing your projects and resume.

Internship guidance & referrals

We share openings we hear about, run mock interviews and refer students where we have connections. Referrals are guidance, not a commitment or a placement guarantee. We'll tell you plainly what's realistic and help you work toward it.

08Your portfolio

Leave with projects you can demo in an interview.

Chat with your notes

Upload your semester PDFs and ask questions. Every answer shows the page it came from.

RAGLangChainChroma

Research agent

An agent that searches, reads sources and writes a short report, with you approving each step.

LangGraphtoolsmemory

Model arena

Send one prompt to four models and compare quality, speed and cost side by side.

GPTClaudeGeminiLlama

Your fine-tuned model

A small open model fine-tuned on a dataset you collect and clean yourself.

HF datasetsLoRAevals

Image studio

A text-to-image app with style controls, hosted on Hugging Face Spaces.

Stable DiffusionGradio

Portfolio site

Your own website, built with an AI coding assistant, showing everything above.

HTML/CSSAI coding

09Join the next batch

5XMinds

Multiply what you can build with AI.

Batches stay small so every student gets hands-on help. Start with the 3-day workshop, or go all in with the 6-week Deep Track.

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