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Artificial Intelligence

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Home Course AI with Python

AI with Python

Learn Python programming and Artificial Intelligence step-by-step through fun projects, games, and real AI models. This course takes students from coding basics to building their first Machine Learning systems.

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1000+ Students
Beginner Level
46 Classes 2.5 months
India
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Course Description

Explore the world of Artificial Intelligence by learning Python, one of the most widely used programming languages. Designed for learners aged 8–16, this course introduces programming fundamentals alongside hands-on AI projects in a simple and engaging way.

Students start with core Python concepts such as variables, loops, conditions, and functions, then gradually move into data handling, visualization, and basic AI and Machine Learning concepts. Through project-based learning, they gain practical experience while developing logical thinking and problem-solving skills. By the end of the course, students will be able to build simple AI-powered applications with confidence.

What You'll Learn

This course follows a structured, beginner-friendly approach that introduces Python programming before gradually expanding into Artificial Intelligence concepts and practical applications. Throughout the course, learners will explore:

  • Python programming fundamentals
  • Variables, data types, operators, and expressions
  • Conditional statements and loops
  • Functions and modular programming
  • Data handling and basic data visualization
  • Introduction to Artificial Intelligence and Machine Learning
  • Computer Vision fundamentals
  • Building AI-powered applications
  • Project-based learning with real-world examples
  • Final capstone AI project

Learning Outcomes

By the end of this course, students will be able to:

  • Write clean and structured Python programs with confidence.
  • Apply programming concepts to solve logical and computational problems.
  • Understand the fundamental principles of Artificial Intelligence and Machine Learning.
  • Work with data and create simple visualizations.
  • Build beginner-friendly AI applications using Python.
  • Develop projects involving computer vision, automation, and intelligent systems.
  • Strengthen analytical thinking, creativity, and problem-solving skills.
  • Complete an end-to-end AI project that demonstrates their learning.

Tools & Skills Covered

  • Python Programming - Learn to write structured code and build functional programs using Python.
  • Computational Thinking & Problem Solving - Develop the ability to break down complex problems into manageable steps.
  • AI Fundamentals - Understand the core concepts behind how intelligent systems work.
  • Introduction to Machine Learning - Explore how machines learn from data to make decisions.
  • Data Handling & Visualization - Work with data and present it visually using charts and graphs.
  • Computer Vision Basics - Learn how computers interpret and process visual information like images and videos.
  • Algorithm Design & Logical Reasoning - Build step-by-step solutions and strengthen logical thinking skills.
  • Project-Based Software Development - Apply concepts by creating real-world projects from start to finish.
  • Creativity and Critical Thinking - Enhance innovative thinking while solving practical challenges.

What Makes This Course Special?

  • Beginner-Friendly Learning Path that introduces programming concepts step by step before advancing to Artificial Intelligence.
  • Hands-On Projects that help students apply concepts through practical coding challenges and real-world applications.
  • Industry-Relevant Skills that introduce learners to technologies used in modern AI development.
  • Real AI Applications including chatbots, computer vision systems, and intelligent automation projects.
  • Capstone Project Experience where students build a complete AI solution using the knowledge gained throughout the course.
  • Self-Paced Learning that allows students to learn, practice, and revisit lessons anytime.

Capstone Projects

During the course, students will work on exciting AI-based projects and complete a final capstone project. Examples include:

  • AI Chatbot - Build a simple chatbot that can respond to user questions.
  • Face Detection System - Create a system that can detect and recognize faces using a camera.
  • AI Game Bot - Develop a bot that can play and make decisions within a game.
  • Voice Assistant - Design a basic assistant that can understand and respond to voice commands.

These projects help learners apply their programming and AI knowledge to create practical, interactive applications while building a strong portfolio of beginner-friendly AI projects.

By completing this course, students will build a strong foundation in Python and Artificial Intelligence while gaining hands-on experience through projects, preparing them to confidently explore advanced technology topics.

Learning Path
12 Modules • Click a step to explore
0%
Module 1
Module 2
Module 3
Module 4
Module 5
Module 6
Module 7
Module 8
Module 9
Module 10
Module 11
Module 12
1
Python Basics & Programming Foundations
4 lectures
1.1

Lecture 1.1 Introduction to Python, variables, and basic data types used in programming.

1.2

Lecture 1.2 Understanding input and output operations for user interaction.

1.3

Lecture 1.3 Type conversion techniques and why data type handling matters.

1.4

Lecture 1.4 Practice session with basic exercises to strengthen foundational concepts.

2
Logical Thinking & Decision Making
4 lectures
2.1

Lecture 2.1 Understanding conditions using if-else statements for decision-making.

2.2

Lecture 2.2 Applying decision logic to real-life scenarios for better problem-solving.

2.3

Lecture 2.3 Nested conditions and use of logical operators in complex situations.

2.4

Lecture 2.4 Practice challenges and puzzle-solving to build logical thinking.

3
Loops & Pattern Thinking
4 lectures
3.1

Lecture 3.1 Introduction to loops (for and while) for repeated task execution.

3.2

Lecture 3.2 Understanding loop control and pattern-based logical thinking.

3.3

Lecture 3.3 Combining loops with conditions to solve structured problems.

3.4

Lecture 3.4 Mini Project: Build a Number Guessing Game using loops and logic.

4
Data Structures & Problem Solving
4 lectures
4.1

Lecture 4.1 Introduction to lists and their role in storing multiple data values.

4.2

Lecture 4.2 List operations and basic data handling techniques.

4.3
Lecture 4.3 Using loops with lists to process and analyze data efficiently.
4.4
Lecture 4.4 Mini Project: Student Marks Analyzer using lists and loops.
5
Functions & Code Modularity
1 lectures
5.1

Lecture 5.1 Introduction to functions and how they organize reusable code blocks.

Lecture 5.2 Importance of functions in AI programs and large applications.

Lecture 5.3 Functions with parameters and return values for flexible programming.

Lecture 5.4 Practice exercises to build modular and structured programs.

6
Applied Programming Projects
1 lectures
6.1

Lecture 6.1 Designing logic-building challenges using structured programming.

Lecture 6.2 Mini Project: Building a Smart Calculator with multiple operations.

Lecture 6.3 Debugging, optimizing, and improving project code quality.

Lecture 6.4 Project extension activities and feature enhancement practice.

7
Python for Fun Applications & Games
1 lectures
7.1

Lecture 7.1 Introduction to Python’s random module and randomness concepts.

Lecture 7.2 Generating random values for simulations and simple games.

Lecture 7.3 Game logic design and creating scoring systems.

Lecture 7.4 Mini Project: Rock-Paper-Scissors AI Game development.

8
Foundations of Artificial Intelligence
1 lectures
8.1

Lecture 8.1 Introduction to Artificial Intelligence and its evolution.

Lecture 8.2 Understanding differences between AI, Machine Learning, and Deep Learning.

Lecture 8.3 Real-world AI systems and applications across industries.

Lecture 8.4 Activity: Identifying and designing AI ideas from daily life problems.

9
Machine Learning Foundations
1 lectures
9.1

Lecture 9.1 How machines learn: training vs prediction concepts.

Lecture 9.2 Importance of data and introduction to datasets.

Lecture 9.3 Structured vs unstructured data with practical examples.

Lecture 9.4 Activity: Exploring datasets and understanding data patterns.

10
Data Handling & Visualization
1 lectures
10.1

Lecture 10.1 Introduction to NumPy arrays and numerical data handling.

Lecture 10.2 Introduction to Pandas for dataset loading and analysis.

Lecture 10.3 Graph basics and importance of data visualization.

Lecture 10.4 Using Matplotlib to plot graphs and visualize patterns.

11
Machine Learning Models & Predictions
1 lectures
11.1

Lecture 11.1 Understanding Machine Learning, features, and labels.

Lecture 11.2 Types of ML: Supervised and Unsupervised learning methods.

Lecture 11.3 Building first ML model using Scikit-Learn for predictions.

Lecture 11.4 Mini Project: Student Marks Prediction using Linear Regression.

12
Advanced AI Applications & Capstone Projects
1 lectures
12.1

Lecture 12.1 Classification models and Decision Trees for categorization tasks.

Lecture 12.2 Introduction to Computer Vision and image processing using OpenCV.

Lecture 12.3 Building AI applications: Chatbots, Voice Assistants, and Face Detection.

Lecture 12.4 Final Capstone Project: Student builds an AI project and presents it for evaluation.

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Satendra Patel | AI and Robotics Instructor

Hey there! Learn with me in a gamified way.

4.2
Rating
100+
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200+
Students
10+
Courses
Biography
“

I am a Robotics Teacher with experience in teaching STEM concepts through hands-on, engaging lessons designed for young learners. I specialize in simplifying complex topics into practical, easy-to-understand activities that emphasize creativity, critical thinking, and real-world problem solving. I have successfully taught 200+ students aged 10–13 across India, the US, UK, and Canada using platforms such as Arduino, Raspberry Pi Pico, and Micro:bit. Along with teaching, I also contribute to curriculum design to make learning accessible and impactful.

Passionate about making technology learning exciting and future-ready, I am committed to preparing students through interactive methods and practical projects. My student-centric and detail-oriented teaching approach ensures that every learner feels supported and inspired.

Educational Qualification – B.Tech in Computer Science and Engineering from Lovely Professional University

Experience – 2+ year in NaivoTech, delivered live online and offline robotics sessions  

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AI with Python course learning machine learning programming

What’s Included

Everything you need to know about this course

Lectures
46 Classes
Duration
2.5 months
Level
Beginner
Language
English / Hindi

Certificate of Completion

Get certified and showcase your newly learned skills.

What you need / Requirement

Laptop/PC
Laptop/PC

A personal computer is essential for hands-on practice and project work.

Software Ready
Software Ready

Prepare your system with the necessary tools and applications to Practice Coding and Programming.

Basic Tools
Basic Tools

PDF Reader (for notes and study materials)

Internet Connection
Internet Connection

Stable Internet with at least 2 Mbps speed for smooth video streaming and interactive content.

Learning Path

Your Journey. Your Growth.

A structured path designed to take you from basics to mastery with clarity, confidence, and real-world impact.

01

Beginner

Start with fundamental concepts and build a strong foundation.

02

Intermediate

Expand your knowledge and start building practical projects.

03

Advanced

Dive deeper into specialized areas and master complex techniques.

04

Master

Achieve expert-level proficiency and innovate with your skills.

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Join 50k+ engineers leveling up today.

Python Basics & Data Types

Python Basics & Data Types

Input, Output & Conditions

Input, Output & Conditions

Loops and Logical Thinking

Loops and Logical Thinking

Lists and Data Handling

Lists and Data Handling

Problem Solving with Python

Problem Solving with Python

Functions and Code Structuring

Functions and Code Structuring

Working with NumPy and Pandas

Working with NumPy and Pandas

Data Visualization using Matplotlib

Data Visualization using Matplotlib

Introduction to Machine Learning

Introduction to Machine Learning

Building Simple Prediction Models

Building Simple Prediction Models

Classification Models

Classification Models

Computer Vision Basics

Computer Vision Basics

AI Chatbots and Automation

AI Chatbots and Automation

Join 50k+ engineers leveling up today.

Your Generative AI Learning Journey

  • Interactive Project-Based Python & AI Learning
  • Learn Through Coding Challenges, Activities and Real-World Projects
  • Build Intelligent Applications, Chatbots and AI-Powered Solutions
  • Develop Strong Computational Thinking and Problem-Solving Skills
  • Gain Hands-On Experience with Modern AI and Python Technologies
  • Dedicated Mentor Guidance Throughout Your Learning Journey
  • Personalized Doubt Solving and Technical Support Sessions
  • Regular Feedback and Performance Improvement Guidance
  • Access to Learning Resources, Practice Exercises and Projects
  • Continuous Progress Tracking and Skill Development Support
  • Build Future-Ready Skills for AI and Technology Careers
  • Create an Impressive Portfolio of Python and AI Projects
  • Explore Career Pathways in AI, Data Science and Automation
  • Develop Industry-Relevant Technical and Problem-Solving Skills
  • Earn Certification to Showcase Your Knowledge and Achievements
  • Collaborate with Peers Through Team Projects and Challenges
  • Participate in AI Showcases, Competitions and Innovation Events
  • Connect with a Community of Young Coders and Innovators
  • Share Ideas, Learn Together and Build Meaningful Connections
  • Present Your Projects to Mentors, Peers and Industry Experts
AI and Python Certification Program

Master AI with Python
Learn in-demand AI skills through hands-on projects and real-world applications.

Beginner Friendly Hands-On Projects Industry-Relevant Skills

100+ Hours Learning
10+ AI Projects
Career-Focused Curriculum
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YOUR ROADMAP

Go from Curious Beginner to AI Builder

A clear, step-by-step milestone path to take you from the basics to building real-world AI solutions.

01

Discover the Basics of Artificial Intelligence

Your journey starts with understanding what Artificial Intelligence is and how machines can learn from data. You will also get introduced to Python, one of the most popular programming languages used in AI.

01
02
02

Learn Python Programming Fundamentals

In this stage, you will learn the core building blocks of Python such as variables, conditions, loops, and lists. These concepts help you develop logical thinking and problem-solving skills needed for AI development.

03

Develop Logical Thinking with Coding

Once you understand the basics, you will practice writing programs and solving coding challenges. You will learn how to structure code using functions and build small Python programs.

03
04
04

Explore Data and Visualization

Artificial Intelligence works with data. In this step, you will learn how to handle datasets using tools like NumPy and Pandas and visualize information using graphs and charts.

05

Build Your First Machine Learning Models

Now you will step into Machine Learning. You will understand how AI models learn patterns from data and build simple prediction models using Python libraries.

05
06
06

Create Real AI Projects

In the final stage, you will apply everything you learned to create real AI projects such as prediction systems, simple AI games, or computer vision applications and present your final project with confidence.

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