AI BOOTCAMP (5DAYS)

The Axolotron AI Bootcamp is an intensive 5-day, 25-hour hands-on program that transformsbeginners into industry-ready AI builders. LearnPython, data handling, machine learning, deeplearning, and Git — all while building realprojects. No theory, just execution. Leave withconfidence, a portfolio, and skills to join real AIteams.

03What You Learn (Day-by-DayBreakdown)

Day 1: AI Mindset + Git Setup + Python for AI

Hours 1-2: AI in the real world: how it powers business, not just sci-fi

Git & GitHub crash course (init, commit, push, clone, branches)

Hours 3-5: Python essentials for AI: logic, control flow, lists, functions

Mini Project: Build an AI-powered number guessing game

GitHub push + walkthrough on teamwork habits

Outcome: Dev-ready setup + Python + Git confidence

Day 2: Data Like a Real AI Engineer

Hours 1-2: What is data in AI: structured vs unstructured

NumPy deep dive (arrays, ops, slicing)

Hours 3-5: Pandas mastery: filtering, groupby, merging

EDA (Exploratory Data Analysis) challenge

Mini Project: Sales trend analyzer (with graphs)

Outcome: Can clean & analyze real datasets

Day 3: Machine Learning That Actually Works

Hours 1-2: ML mindset: supervised learning + use cases

scikit-learn: regression/classification

Model training + testing workflow

Hours 3-5: Evaluation metrics: accuracy, precision, recall

Project: Predict diabetes / customer churn

Version control: push working model to GitHub

Outcome: Fully trained ML model + team-reviewed code

Day 4: Deep Learning That Delivers

Hours 1-2: What is a neural net (visual breakdown, intuition)

Keras/TensorFlow intro (hands-on)

Hours 3-5: CNNs for image classification

Train your own digit/disease/image recognizer

Push to GitHub + peer review

Outcome: Can build and explain a DL model confidently

Day 5: Industry Tools + Final Project Build

Hours 1-2: AI tools: ChatGPT, Prompt Engineering

Bonus: Business AI use cases + automation demos

Hours 3-5: Final Project: Build in pairs (healthcare, e-com, etc.)

Presentation prep: pitch + walkthrough

GitHub cleanup + career roadmap Q&A

Outcome: Capstone project, Portfolio-ready repo, Interview-ready clarity

Day 4: Streamlit UI + Docker Packaging

Outcome: You turn your AI model into a working app and container

Build an interactive app using Streamlit

Add input widgets, model inference, and error handling

Write Dockerfile, build image, run container

Lab: Run your app in Docker, push Dockerfile + UI to GitHub with screenshots

Day 5: Capstone + Demo + Portfolio Build

Outcome: You finish a production-grade AI project, present it, and walk out with a portfolio

Choose: Fake News Detector, Resume Parser, etc.

Apply all skills: Python, ML, Git, UI, Docker

Polish GitHub repo: GIF/video demo, README, /docs

Live Demo Day: Present your project to peers & mentors

Career tips + next steps

Bootcamp Outcomes

Set up a full AI dev environment with Git, VS Code, and Python

Build and train multiple ML models using real datasets

Create and push projects to GitHub with clean commit history

Design and launch an AI web app using Streamlit

Package projects in Docker for real-world deployment

Complete a capstone project ready for portfolios or internships

Receive a certificate + live demo exposure

Walk away with a real GitHub portfolio that proves their skills