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Launch - SEPTEMBER 20th | Now $4,800/ Regular Price $8,000

Your 8-Month AI Engineering Journey: A Project-Based Plan

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This bootcamp is designed to turn you into a practical, hireable Machine Learning Engineer.

You will learn by building

Each month, you'll tackle new projects while iteratively developing a complex, multimodal AI assistant as your main capstone.

Prerequisites

Python
- Python fundamentals
- Python data structures (lists, dictionaries, sets, tuples)
- List/dictionary comprehensions and functional programming tools
- OOP principles in Python (classes, inheritance, encapsulation)
- Virtual environments (venv, conda)
- Package management
Git (branching, merging, pull requests)
15-20 hours/week commitment

Core Continuous Project
Your Capstone in Development

You will build the "Virtual Travel Explorer," an AI assistant that evolves each month. It starts as a simple script and finishes as a deployed, tool-using, multimodal AI that can chat, recognize landmarks, and give real-time travel advice.

ML Portfolio Dashboard: Develop a personal portfolio website that showcases your projects and ML experiments. This grows throughout the course as you add new projects and visualizations.

COURSE SCHEDULE

Start: September 20th, 2025

2 webinars per week/ PST

Wednesdays 7pm
Saturdays 10am

COURSE PROGRAM

Focus: Mastering the data science toolkit, EDA, and core regression models.
Project: House Prices - Advanced Regression Techniques
You'll build models to predict home values, mastering feature engineering and regression on a complex, real-world Kaggle dataset.
(Skills: EDA, Feature Engineering, Regression Models, XGBoost, Kaggle Competitions)

Main Project Goal: Build the v0.1 command-line version with simple, rule-based responses.

Focus: Mastering finding hidden patterns in data.
Project: Credit Card Customer Segmentation
You'll act as a data scientist for a bank, using clustering algorithms to find distinct marketing groups in a dataset of customer spending habits.
(Skills: Unsupervised Learning, K-Means, PCA, Customer Segmentation)

Main Project Goal: v0.2, with a classical ML model to understand user travel intents.

Month 2: Advanced Classification & Unsupervised Learning

Month 1: Tabular Data Mastery & Foundations

Month 4: Core Computer Vision - Classification & Detection

Focus: Training high-performance classifiers on your custom data and tackling a real-world medical object detection challenge.
Project: AI Lego Sorter (Part 2 - Classification)
Using the dataset you created, you'll train a powerful image classifier to identify different Lego brick types.
(Skills: Custom CNNs, Data Augmentation, Transfer Learning)

Project: AI for Medical Image Analysis - Pneumonia Detection
You'll work on a high-impact medical project, fine-tuning a YOLO model to find and draw bounding boxes around signs of pneumonia in chest X-rays.
(Skills: Object Detection, YOLO, Medical Imaging)

Main Project Goal: v0.4, with a core visual feature to recognize famous landmarks from photos.

Focus: Completing an advanced segmentation pipeline and diving deep into modern NLP with Transformers.
Project: AI Lego Sorter (Part 3 - Segmentation)
You'll take your project to the final level. Using your custom masks, you'll train a U-Net model to find the exact, pixel-perfect silhouette of each Lego brick.
(Skills: Image Segmentation, U-Net Architecture, Custom Loss Functions)

Project: Comment Toxicity Detector & Explainer
You'll build a system to moderate online discussions by fine-tuning a Transformer to detect toxic comments, and then use Explainable AI (XAI) to understand why the model made its decisions.
(Skills: NLP, Transformer Fine-Tuning, Hugging Face, XAI)

Main Project Goal: v0.5, with a powerful Transformer NLU and basic conversational memory.

Month 5: Advanced CV & Natural Language Processing

Focus: Building Neural Networks from the fundamentals and experiencing the critical skill of creating your own dataset.
Project: 'Street Fighter' Attack Classifier from Scratch
You'll demystify deep learning by building a complete Neural Network from zero, using only NumPy, to recognize iconic video game moves.
(Skills: Neural Network Fundamentals, Backpropagation, Python/NumPy)

Project Task: The Data Creator (AI Lego Sorter Part 1)
You will begin your CV anchor project by creating your own dataset. You'll photograph Lego bricks and meticulously label them with segmentation masks using CVAT, a professional annotation tool.
(Skills: Data Collection, Manual Labeling, CVAT)

Main Project Goal: v0.3, with a simple Neural Network to improve intent understanding.

Month 3: Neural Networks & Custom Data Creation

Focus: Mastering time series forecasting and learning the essential engineering skills to deploy a model into production.
Project: Store Sales Time Series Forecasting
You'll tackle a classic business problem by predicting future sales for a retail chain, mastering temporal feature engineering and comparing various forecasting models.
(Skills: Time Series Analysis, Forecasting, Prophet, LSTMs)

Project: Deploying Your CV Model API
You'll take your trained Lego Detector model and turn it into a real product by packaging it into a professional, containerized (Docker) API with tests and a simple CI/CD pipeline.
(Skills: MLOps, FastAPI, Docker, pytest, GitHub Actions)

Bonus Projects (If you have time or want an extra challenge):
💪 Real-Time Exercise Form Guide: Use pose estimation for live workout feedback.
🎨 Neural Art Gallery: Style Transfer: Turn your photos into famous paintings.

Main Project Goal: v0.7, now an agent that can use tools (like a Weather API) and is deployed locally.

Month 7: Specialized Skills & MLOps

Focus: Synthesizing all your skills into a flagship portfolio project and preparing for the job market.
Capstone Project: Your Main Project v1.0
You will build a polished, multimodal AI assistant that can chat, recognize landmarks, use a RAG knowledge base, and connect to live APIs. This is your flagship portfolio piece.
(Skills: System Integration, Advanced Agent Design, Product Polish)

Career Launchpad:
You will finalize your portfolio, polish your resume, practice ML system design questions, and conduct mock interviews to get you ready to be hired.

Month 8: Capstone & Career Launchpad

Focus: Building modern AI applications with Retrieval-Augmented Generation and Parameter-Efficient Fine-Tuning.
Project: AI Trip Planner - RAG
You'll build the core knowledge system for your main project. This chatbot will "read" real travel guides and answer complex, conversational questions.
(Skills: RAG, LangChain, Vector Databases, LLM APIs)

Project: Text-to-SQL LLM Fine-Tuning
You'll dive into modern LLM customization, using LoRA to teach an open-source LLM to become a specialist at converting plain English questions into accurate SQL queries.
(Skills: LLM Fine-Tuning, PEFT, LoRA, Hugging Face trl)

Main Project Goal: v0.6, with a powerful LLM brain and the RAG system for providing deep travel knowledge.

Month 6: The Age of LLMs - RAG & Fine-Tuning

SECTION 1: Tabular data

SECTION 2: Neural Networks & Computer Vision

SECTION 3: NLP

SECTION 4: PRODUCTIZE, PREPARE & OTHER

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