Unlock the Potential of Robotics and AI: Get the Most Advanced Lab for Your ICSE School

AI Lab along with Robotics is designed for the implementation of the latest education trends as per ICSE, and National Education Policy (NEP) 2020. The Lab is the upgrade of the existing computer lab to include DIY robotics kits for the students working in a group of 2.

AI curriculum and kits are recommended for ages 7+ to 17 years / Grade 3 to 12. Block-based coding is recommended for primary and middle school i.e, Grades (3rd to 8th) or beginners, whereas Python coding is used for secondary and senior secondary i.e, Grades (9th to 12th).

Yes, we provide activities for coding, and robotics for grade first onwards. It is designed for age group 5+ (Jr. Kindergarten to Second Grade) for fun and engaging activities. Although our standard curriculum covers the concepts and curriculum for Coding, Robotics and AI (which are covered in AI and Robotics Lab), they are taught after classes/grade 3.

1. AI Lab (AI  and Robotics Lab): For schools looking to start an year-long Coding, AI, and Robotics education with curriculum, assessment, annual competition. It includes Quarky robots, DIY Kits (Mars Rover, Humanoid, Art Paper creatives), Alexa with smart devices, consumables, spares (for items like sensors, motors, fasteners,  etc.), charging stations, etc.
2. AI Classroom Bundle: For schools or libraries or activity centers looking to add AI courses with existing CS/Robotics/STEM/STEAM/ATL programs. Read more for details  and pricing

Considering one session of 40-60 mins of AI and Robotics per week running over the year, and two-three students working in groups,

1. AI Classroom Bundles: Upto 200 students
2. AI Lab (AI  and Robotics Lab): 200 – 400 students. For engaging more students, you can add more AI Classroom Bundle per 200 students.

1. It’s depends on the school. If you are looking to start AI curriculum, then a fully equipped computer lab is sufficient. 
2. If you are looking for best-in-class lab with decorative infrastructure and furniture or for other packages (like  3D printing and drones), then a separate space of 500-1,000 sqft for the lab is recommended.

Infrastructure Requirement (to be provided by the School): Each school selected for setting up a lab should have the following infrastructure available.

• Computer lab for performing practical activities.
• Each lab should be provided with 10 PCs or 10 nodes connected through a server. Accessories like printers, projection systems, etc will also be provided.
• Computers or laptops with Windows 7 or above, Linux, Chromebooks, macOS. For Tablets or Mobile Phones with Android 9 or above, iOS 14 is required.
• 40 Stools/Chairs for Students and 1 Chair for Teachers.
• Electricity Plugs on Worktables, Extension Boards.
• Projector with 30 Watts Speakers, 6×4 sq feet White Board, Project Screen, and Notice Board.

Note*: Python coding is not supported in Tablet/iPad.

Yes. We have additional packages for 3D printing with laser engraver, drones which can be added separately with AI and Robotics lab.

(Only for India) We provide IT equipment package also or AI lab with tablets/laptops as per the need.

We can customize and provide full educational lab solutions including furniture, training, IT and many above 10,000 USD  or 8L INR budget.

We  also provide curated curriculum, and kits for  government organizations or education departments  or education ministeries or Non-profit organizations (NGOs) as per the need  of the CSR activities. For bulk procurement or government tenders on AI education kits and program, do contact us at contact@thestempedia.com.

Yes, we provide onsite capacity-building programs for teachers and yearlong support for efficient working of AI and Robotics Lab. We also seek feedback from teachers and connect over a virtual meet on every 2nd Saturday of the month.

We have 20+ global partners and distributors across the world. We have shipped our educational kits in more than 75 countries so far. Do contact us at contact@thestempedia.com.

We usually ship our kits and AI lab package via DHL as our courier partner.

For becoming our partner or bulk distributor,  please visit: https://thestempedia.com/distributors-and-partners

Currently, AI and Robotics curriculum and kits are available in English and Korean.

If you want to create AI and Robotics curriculum in other languages, please contact us at contact@thestempedia.com. We help experienced CS teachers or STEM-Robotics education companies or book publishing companies to create their own AI and ML curriculum.

Our  coding and AI platform PictoBlox is supported in English, Korean, Spanish, Chinese, Arabic, Hebrew, Hindi, Gujarati, and Kannada.

Yes, it is different from Atal Tinkering Lab. The Indian government granted ATL lab focus on tinkering, core electronics-robotics, IoT, machine tools, etc. While AI lab for schools focuses on Artificial Intelligence, Machine Learning and skill based subjects included in NEP.

We strongly suggest ATL schools to buy AI classroom bundle using the annual INR 2 Lacs (as per the ATL budget consumption guidelines or consumables and training) budget to upgrade the lab as per the NEP 2020.

1. To develop an understanding of concepts and applications in Robotics and Artificial Intelligence (AI).
2. To develop competencies in Robotics and AI via classroom instruction, laboratory, and self-directed project-based learning approach.
3. To facilitate appreciation, understanding, and application of concepts of Robotics and AI through learning and engaging in hands-on activities.
4. To instill AI-Readiness skills in students vide key concepts in AI, such as Data, Computer Vision, and Natural Language Processing.
5. To introduce the students to the concepts of the AI Project Framework.
6. To familiarize students with computational skills (basic Python coding language).
7. To create awareness about ethical considerations of AI.

The 9th class curriculum is divided into 2 parts:

1. Part 1: Robotics
   1. Introduction to Robotics
      1. Understanding Robots: Basic understanding of what a robot is; definition and characteristics; benefits of using robots (with respect to humans): increased quality, increased productivity, increased efficiency, longer working span, working in hazardous environments, improved workplace.
      2. Evolution of Robots; Laws of Robotics: Brief history of Robots with respect to their evolution from the 1900s till date. Definition of Robotics, the three Laws of Robotics by Isaac Asimov (statements only).
      3. Classification of Robots: Classification of Robots as field/terrain based (aerial, ground, underwater) and control based (manual, automatic): Meaning and examples of each. Bio-inspired robots: meaning, purpose, and examples (humanoids, birds, snakes, and insects).
      4. Real-world Robots and their Applications: Application of robots in different fields (domestic, industry, medical, defense, entertainment, and agriculture) with at least one example of each.
   2. Robot as a System
      1. Building blocks of Robots: General block diagram of a robot. A detailed study of the building blocks of a robot. Concept of a robot as having mechanical, electronic, and computational blocks; with functioning and working principle of each block. Design aspects using examples of humanoid, aerial, underwater, and mobile robots.
      2. Identification of Robots: Identification of robots (through demonstration/ video/graphic details). Illustration using an industrial robot (e.g., Industrial Robotic Arm), humanoid and mobile robot. The idea that a mechanical body can be of any form must be emphasized.
   3. Concepts in Robotics
      1. Types of motion; motion in one-dimension and two-dimension; types of joints and links: Types of motion (linear, angular, and circular); a brief understanding of motion in one-dimension and two-dimension; types of joints (prismatic, revolute, and spherical); types of links (rigid and soft). Relevant examples for each of the above.
      2. Using links and joints to create specific motion: A detailed study of how links and joints help create specific motion. Identification of links and joints used in a given system. Examples of the demonstration can include Industrial Robot Arms.
      3. Degree of freedom of a robot: Definition; identification through illustration.
2. Part 2: Artificial Inteligence (AI)
   1. Introduction to Artificial Intelligence (AI)
      1. Meaning and brief history: Definition of Artificial Intelligence; brief account of the history of AI since the time John McCarthy first coined the term in 1956; Turing Test, its use and importance.
      2. Applications and Benefits of AI: Applications of AI in different fields: commercial, industry, medical/health care, defense, banking, entertainment, transport, security and agriculture. Commonly used AI applications in daily life such as, online shopping, search engines, chatbots, voice assistants, entertainment portals, facial recognition, driver assisting vehicles, and augmented/ virtual reality. Benefits of using AI – Automation, smart decision making, assisting humans, remote patient monitoring & monitoring the progression of contagious diseases, analysis of data for research and development, efficiently solving complex problems, speedy disaster recovery strategy, performing recurring business tasks, reducing the chances of manual errors, ensuring 24-hour service availability with the same performance and consistency throughout the day.
      3. Ethical considerations in AI: A brief understanding of ethics in artificial intelligence including bias, prejudice, fairness, accountability, transparency, interpretability, and explainability.
   2. Role of Data and Information, Evolution of Computing
      1. Data and Information: Types of Data (audio, visual, numeric, text); Data to Information. Understanding that data is pivotal to Artificial Intelligence. A brief introduction to how relevant data is identified, acquired, and explored, as a precursor to the AI Project Cycle.
      2. Evolution of Computing: Pre AI/ML Binary Logic System, Conditional Gates, Deterministic computing for deterministic problems. An introduction to above mentioned topics, with the emphasis that earlier computing was suited for only deterministic problems; explaining deterministic computing and deterministic problems giving relevant examples. Illustrating the limitations of deterministic computing in solving real life problems, Comparison between deterministic and probabilistic nature of real-life problems.Note: Explanation of how AI can solve a new class of problems, based on a probabilistic paradigm. Hence Need for AI: Probabilistic, real-life problems; The AI Discretion (AI is not needed for solving deterministic problems) for example – the difference in description of temperatures by a machine and a human. A machine would make a discrete distinction between cool and hot at a given temperature for instance if 35°C is hot, then any temperature 34.9° C and below would be cool. Humans would, however, describe the temperature in a range of ‘cool, pleasant, warm, hot’ and so on based on their subjective experience of the temperature.
   3. Introduction to Data and Programming with Python
      1. Familiarization with Python: Introduction to Python and its elementary concepts: object-oriented, high-level, general-purpose programming language. Uses and advantages of Python.
      2. Introduction to data types and variables: Introduction to a simple Python program structure and the concept of indentation in Python, different data types in Python – numeric (int, float), Boolean, sequence type (tuple, list, strings), sets and dictionary, an understanding of what kind of data types should be used in different use cases. Introduction to variables and assignment of values.
      3. Introduction to Operators: Usage of different operators (arithmetic, logical, assignment, comparison, identity, membership) on data types, and kinds of statements that can be executed in Python.
      4. Conditional Statements: Introduction to blocks in Python, if conditions, if else conditions, nested if conditions, if-else-if (elif) conditional block, case, and switch. Shorthand conditional statements.
      5. Control Statements: Meaning and use of loops in Python. Different types of loops (while, for), nested loops, the syntax used. ‘for’ loop for different types of iterable (list, tuple, string, dictionary) along with the idea of a break, continue and pass statements, ‘while’ loop and their use cases.
      6. Functions: An understanding of both built-in and user-defined functions; the importance of functions to maintain modularity; arguments given to a function (fixed and variable length); the concept of default arguments and return type of a function.
   4. AI Concepts and AI Project Framework
      1. AI Concepts: Broad and narrow AI, strong versus weak AI. Expert systems in AI (e.g., Eliza). Computer vision (CV), Natural Language Processing (NLP), and Neural Network (NN).
      2. Components and Stages (alias AI Project Cycle): Understanding of AI Project Framework, Stages involved in AI project: Problem Scoping, Data Acquisition, Data Exploration, Modelling, and Evaluation (brief understanding of each).