Machine Learning 1: Introduction to Computation


Dive into the world of machine learning with our exciting course, Machine Learning 1: Introduction to Computation. Designed for eager minds from 6th to 12th grade, this course harnesses the power of Python's Scikit-learn library to unravel the mysteries of AI. Students will explore the dynamic landscape of machine learning, mastering regressive, classifying, and clustering models. Through hands-on projects like challenging a computer AI in Rock Paper Scissors or developing advanced text analyzers, students will cultivate creativity and problem-solving skills. Unlock the future of technology and embark on a journey to innovate and impact the world!

Level

L4 Applied Programming

Pathway

Machine Learning

Skill Level

Intermediate - Advanced

Class Size

1-on-1 or Group (2-4 students)

Master the Basics of Machine Learning

Get a strong foundation in key machine learning concepts like regressive, classifying, and clustering models using fun and interactive projects.

Hands-On Learning with Python

Utilize the popular Scikit-learn library within Python to get practical experience in designing AI algorithms through step-by-step guidance.

Exciting Projects and Challenges

Engage in creative projects such as building a Rock Paper Scissors AI or developing a text analyzer to apply your newly acquired skills.

Prepare for Future Innovation

Gain the necessary skills in machine learning during your formative educational years, setting you up for advanced studies in AI and technology.

Interactive and Engaging Learning Experience

Participate in a dynamic course structure that blends theoretical knowledge with practical application, making learning both effective and enjoyable.

Learning Objectives

    Unlock the Future: Dive into AI with Python and Master Machine Learning Foundations through Interactive Projects!

  • Understand the basics of machine learning and AI algorithms.
  • Learn how to use Python's Scikit-learn library for data analysis.
  • Build foundational skills in designing regressive, classifying, and clustering models.
  • Create hands-on projects like a Rock Paper Scissors AI and text analyzers.
  • Gain confidence in applying machine learning concepts to solve real-world problems.

Course Features

  • In-person or Online Available
  • Project-Oriented Learning
  • Exercise System Support

Scheduling

Upon finishing the trial and assessment, classes will be scheduled based on the student’s availability. Please contact us for the Trial class.

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Project Based

Our courses are designed to lead students to build their own startup projects.

Experienced Instructors

Passion for code. Unmatched expertise. Personality that brings interaction and encouragement always.

Aim at Competitions

Beyond learning programming, students are prepared to compete in science fairs, research, and entrepreneurship competitions.

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