Live online AI & Machine Learning course with Python
Dive into the world of AI and machine learning using Python!
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STEM.ORG accredited globally recognized program
AI & Machine Learning is accredited by STEM.org
STEM.ORG accredited globally recognized program
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Ages 14+
Grades KG-12
144 sessions
STEM.ORG certification
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What is AI & Machine Learning with Python?

Artificial Intelligence (AI) and Machine Learning (ML) are two of the most transformative technologies in the world today, driving innovation in fields ranging from healthcare to finance, robotics, and entertainment. AI refers to the simulation of human intelligence in machines, enabling them to perform tasks that typically require human cognition, such as problem-solving, pattern recognition, and decision-making. Machine Learning, a subset of AI, focuses on the development of algorithms that allow computers to learn from and make predictions or decisions based on data. Together, AI and ML form the backbone of modern technological advancements, and learning these skills has become essential for young learners aspiring to enter the tech industry.

Python, an incredibly versatile and easy-to-learn programming language, is widely regarded as one of the best languages for AI and machine learning. Its simplicity, readability, and vast libraries make it ideal for beginners and professionals alike. Codeyoung’s AI & Machine Learning with Python course introduces students to the fascinating world of AI by teaching them how to build intelligent systems using Python programming. It’s designed to help kids and teens grasp the fundamental concepts of AI and ML while developing practical coding skills.

What you’ll learn in AI & Machine Learning with Python
Sessions 1-6
Introduction to Python
Sessions 7-13
Control flow
Sessions 14-27
Variables and data
Sessions 28-33
OOPS
Sessions 34-48
GUI programming
AI & Machine Learning with Python helps solve real-life applications and improve academically
✨ 100s of exercises to challenge yourself and master the language ✨
Medium
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QR Code Generator
Learn how to create a QR code generator
Hard
real life application Card 1
Scientific Calculator
Learn how to create a scientific GUI calculator
Medium
real life application Card 2
Bank Management System
Learn how to create a bank management app using conditions and loops
Hard
real life application Card 3
Currency Converter
Learn how to create a currency converter using tkinter, functions, & requests library
✨ Improvement in STEM and cognitive skills ✨
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Improved STEM skills
Simple & compound interest
Foundational algebra
Combined arithmetic operations
Mensuration
Improved cognitive skills
Logical thinking
Creative thinking
Spatial reasoning
Sequential thinking
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AI & Machine Learning with Python is accredited by STEM.ORG
Check accreditation here.
Codeyoung’s AI & Machine Learning with Python course is loved by both parents and kids
We’re rated 4.5+/5 on Trustpilot and Google!
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Meet our expert AI & Maching Learning programming mentors
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Less than 1% applicants make it through - we prioritize quality
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At Codeyoung, mentors go beyond just teaching; they are your personal Gurus
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Mentors ensure a continuous feedback loop with SPR and Glimpse assistance
FAQs about AI and Machine Learning with Python
What makes this AI course with Python an excellent choice for learning AI and machine learning?
Codeyoung’s AI course with Python offers a hands-on, project-based learning approach, combining foundational AI and machine learning concepts with real-world applications. It is designed to be engaging and interactive, providing students with the tools to build practical AI projects from scratch.
Yes, Codeyoung’s AI with Python course is beginner-friendly. It is structured to start with fundamental AI and machine learning concepts, making it accessible even for students with no prior coding or AI experience.
The course covers essential technologies and frameworks such as Python, NumPy, Pandas, and scikit-learn. Students will also explore machine learning libraries like TensorFlow and Keras for building AI models.
Students will work on hands-on projects such as building basic AI models, developing machine learning algorithms, and creating applications like image recognition and predictive analysis, helping them apply theoretical concepts to real-world challenges.
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