Artificial Intelligence & Machine Learning
Discover AI. Train Smart Machines. Build the Future.
₹5000₹10000
Course Overview
Artificial Intelligence & Machine Learning at Let’s Robotics introduces students to the technology behind intelligent machines, smart applications, voice assistants, image recognition and autonomous systems.
Through interactive activities, guided coding sessions and practical projects, students explore how computers learn from data, recognise patterns, understand information and make predictions.
Students will experiment with AI tools, develop beginner-friendly machine learning models, explore computer vision and natural language processing, and build their own AI-powered applications.
The programme focuses on developing computational thinking, creativity, problem-solving abilities and
Course Schedule
- 18
- November 12, 2026 – November 30, 2026
Eligibility
Students studying in Classes 5–10 or aged 10–16 years who are curious about technology, computers, robotics and intelligent machines.
The programme is suitable for beginners as well as students with basic computer knowledge.
Prerequisites
– Basic computer operating knowledge.
– Interest in science, mathematics and technology.
– Basic typing and computer navigation skills.
– No previous AI or programming experience required.
– A willingness to experiment, explore and create.
Learning Outcomes
By the end of this programme, students will be able to:
1. Explain the fundamentals and applications of Artificial Intelligence.
2. Understand the difference between AI, Machine Learning and Deep Learning.
3. Write basic Python programmes.
4. Understand datasets, patterns and data classification.
5. Train and test beginner-level machine learning models.
6. Explore image recognition and computer vision.
7. Understand the fundamentals of Natural Language Processing.
8. Use Generative AI tools responsibly and effectively.
9. Explore the integration of AI with robotics and automation.
10. Design and present an AI-powered innovation project.
11. Develop computational thinking and problem-solving skills.
12. Understand responsible AI, privacy, fairness and digital ethics.
Course Curriculum
Module 01 – Introduction to Artificial Intelligence
Duration: Week 1
- What is AI?
- History and evolution of AI
- Types of AI
- Everyday applications of AI
Module 02 – Understanding Smart Machines
Duration: Week 2
- How computers think
- Human intelligence vs machine intelligence
- Algorithms and decision-making
- Introduction to automation
Module 03 – Python Programming Fundamentals
Duration: Week 3
- Introduction to Python
- Variables and data types
- Conditional statements
- Loops and functions
Module 04 – Data Science Fundamentals
Duration: Week 4
- What is data?
- Types of data
- Data collection and organisation
- Understanding patterns and visualisation
Module 05 – Introduction to Machine Learning
Duration: Week 5
- What is machine learning?
- Supervised learning
- Unsupervised learning
- Training and testing models
Module 06 – Build Your First AI Model
Duration: Week 6
- Introduction to AI model training
- Image and data classification
- Training datasets
- Testing model accuracy
Module 07 – Computer Vision and Image Recognition
Duration: Week 7
- How computers see
- Image classification
- Object recognition
- Real-world computer vision applications
Module 08 – Natural Language Processing
Duration: Week 8
- How machines understand language
- Text classification
- Chatbots
- Introduction to language models
Module 09 – Generative AI and AI Tools
Duration: Week 9
- What is Generative AI?
- Introduction to AI assistants
- Prompt engineering
- Responsible use of AI tools
Module 10 – AI and Robotics Integration
Duration: Week 10
- AI-powered robots
- Sensors and intelligent systems
- Decision-making in robots
- Introduction to autonomous systems
Module 11 – Build an AI-Powered Project
Duration: Week 11
- Project planning
- Selecting an AI application
- Model development
- Testing and improvement
Module 12 – Final Project and Innovation Showcase
Duration: Week 12
- Final project development
- Testing and debugging
- Project presentation
- Learning assessment and showcase