machine-learning

Machine Learning

Course Overview

Machine Learning is a rapidly growing field, and understanding the basics can be a valuable skill in today’s job market. This course provides an introduction to supervised learning, a fundamental area of machine learning, by building a classification model using Python. Through a combination of theory and hands-on practice, students will learn about various mathematical models and techniques used in machine learning.

Course Objectives

  • Learn the functions and make use of different block types (motion, looks, sounds, pen, data, sensing, events, control, operators, etc.) in their creation
  • Learn strategies for solving problems, designing projects, and communicating ideas
  • Learn to make their very own animations and games

Python

Students further explore and build a classification model using Python programming language, including how to preprocess data, split data into training and testing sets, and evaluate model performance.

Introduction to Machine Learning

Learn about the basics of machine learning and its various applications.

Real-World Applications

Explore various real-world applications of machine learning, including image recognition and natural language processing.

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Supervised Learning

Understand the concept of supervised learning and how it is used in building machine learning models.

Classification Models

Dive into regression and classification models, and learn more about how these models work

real-life-application

Problem Solving Techniques

Learn techniques to troubleshoot and overcome problems that arise during the machine learning process.

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Course Completion

2 Modules (avg. 32 Lessons)

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