AI Engineer
Grades 7–9Introduction
Students learn the fundamentals of Machine Learning by training real predictive models using Python. They explore classification, regression, data visualization, and AI deployment using scikit-learn, Seaborn, and Gradio.Students move from using AI tools to engineering AI-powered systems. They learn Python, APIs, machine learning basics, and build real-world AI agents that automate tasks, analyze data, and interact with the web.
What Your Child Will Learn
Course Content
Students learn how machines classify and categorize data into groups. They train AI models that answer yes/no and multi-category prediction problems using real datasets.
* What is Classification?
* Labels, features, and datasets
* Binary vs Multi-class classification
* Training models with scikit-learn
* Model accuracy & evaluation
Students explore regression algorithms that predict numerical values and trends using machine learning models.
* What is Regression?
* Linear Regression fundamentals
* Continuous value prediction
* Understanding correlation & trends
* Evaluating prediction accuracy
Students learn one of the most powerful machine learning algorithms — Random Forest — and understand how ensemble models improve prediction accuracy.
* What is Random Forest?
* Decision Trees explained
* Ensemble learning concepts
* Training Random Forest models
Students discover what AI agents are, how they think, and why they are transforming industries. This module covers the complete developer setup, Python basics, APIs, and the four superpowers of AI agents.
Students build an AI-powered file organizer that automatically sorts files into folders based on file type, content, or categories.
Students build an AI assistant that creates personalized study schedules, tracks goals, and optimizes productivity.
Students create AI-powered analytics tools that process datasets, generate insights, and visualize trends for business decision-making.
Students develop an intelligent finance assistant that tracks expenses, categorizes spending, and gives budgeting insights.
Students build an AI email assistant that classifies, summarizes, and drafts emails automatically.
Students create systems that automatically generate and send personalized emails using AI and APIs.
Students build a travel assistant that creates itineraries, compares options, and recommends optimized travel plans.
Students create an AI shopping assistant that compares products, analyzes reviews, and helps users make better buying decisions.Students build browser automation agents that can search websites, open pages, extract information, and perform actions automatically.
Students create a scheduling assistant that integrates with calendars, manages meetings, and automates event planning.
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