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The Robotics Simulation - Powered Learning Tool
For Every Student
Riders’ Institutional STEM Package is a discounted bundle offer for middle and high school levels that facilitates easier learning of programming for students and offers a unique experience for teachers! Utilized and endorsed by schools internationally.
Improving school performance, supporting students' technology career ambitions!
Riders helps put students on the path to better academic outcomes, new interests and career opportunities. The unique Riders program combines video tutorials with robotic simulations that let students apply those newly learned theories. Once they’ve mastered their studies, Riders also gives students the opportunity to compete globally in robotics competitions where they can experience all the excitement of e-sports. The motivation and adrenaline provided by realistic simulations shows how rewarding and fun it can be to specialize in STEM subjects!
Riders’ competitions offer students a way to recognize their own development and to showcase their new talents.
Robotics Coding Course Content
Year-round availability of the robotics programming courses and unlimited practice opportunities
Certification for the completed training
Rewatchable online course videos
Weekly support sessions with solutions to questions
Ability To Organize Internal Competitions
Ability to measure student progress through in-class competitions
Multiple practice opportunities thanks to trial competitions
The organization of Python or Blockly-based competitions specifically for your institution
Riders Robotics League Participation Ticket
1 season ticket of RRL excitement
2 teams’ free participation
Global Competition Ticket
Opportunity to compete in the global championship as one of the top 3 teams from the Local League competitions
Chance to win great Prizes
Selected by Innovators in education and technology
PREPARE YOUR STUDENTS FOR REAL LIFE SCENARIOS!
Advantages of the Riders School Package
A single investment allowing a school to teach coding to all its students
Free entrance for 2 teams in the Riders Robotics League competition, the most advanced educational on-line robotics league.
Zero kit and maintenance costs while providing STEM-based robotics coding training
Minimised costs per student for learning robotics and joining a competitive robotics league
The opportunity to build student skills in a fun way, by combining classroom learning with the reinforcement of a competitive environment to test new skills and knowledge
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Advantages of the
Riders School Package
01
Training Content Appropriate for STEM Curriculum
Offer students the enjoyment of stimulating educational content presented as narrated course content that offers gradually more challenging tasks.
02
Data Security Compliance
Student data is protected within the framework of Personal Data Protection Laws.
Student data is shared only with the relevant school.
03
Easy Integration
Riders is readily compatible with school LMS systems and testing the algorithms developed in our simulation environments only takes seconds.
04
Educational Resource Package
Provided as guide documentation for educators, the Educator Resource Packs provide a detailed description of each task and solution.
05
Educator Support
Video content includes tips on how to help students who are progressing at different speeds. All questions are answered in support sessions.
LEARN, PLAY, COMPETE
Learn with the most advanced
educational simulations
Junior STEM for
Middle Schools
Creating and programming real robots
Blockly
Control Flows
Sensors
Senior STEM for
High Schools
Creating and programming real robots
Python
AI
Image Processing
Schedule a Demo Meeting
Riders School Package
Robotics Coding
Lesson Content
Lesson 1: Introduction to Riders with “ScoutRider”
We will learn to make decisions in robotic coding.
Basic Python Commands: Discover simple Python commands that will enable you to perform a task.
Algorithms: Connect multiple instructions to create a sequence.
Problem Solving: Solve increasingly difficult logic puzzles.
Simple Transition: Move from one point to another along a floor in single steps.
Simple Rotation: Learn right and left turns within an algorithm.
Lesson 2: Programming Loops with "DirtRider"
We will learn about while loops.
While Loops: Implement While loops in Python.
Patterns: Recognize and apply patterns.
Algorithms: Connect multiple instructions to create a sequence.
Simple Transition: Move from one point to another along a floor in single steps.
Simple Rotation: Turn right and left in an algorithm
Lesson 3: Conditional Statements with "HotRider"
We will learn to use conditional statements in robotic coding.
Conditional Statements: Implement if and elif statements in Python.
Algorithms: Implement adaptive algorithms that respond to current conditions.
Simple Transition: Move from one point to another along a grid in single steps.
Simple Rotation: Turn right and left in an algorithm.
Lesson 4: For Loops with “GarbageRider”
We will learn about for loops.
For Loops: Repeat a certain number of times over a set course.
Refactoring: Improve code efficiency.
Patterns: Recognize and apply patterns for algorithm development.
Transition: Move from one point to another along a floor using fractional steps.
Coordinates: Recognize the points marked on an obstacle course.
Rotation: Rotate using radians to apply simple left/right rotations.
Lesson 5: Pathfinding with “LabRider”
We will learn about path finding and flood-fill algorithms.
Double For Loops: Implement nested for loops.
While Loops: Implement while loops in python.
Path Finding: Implement algorithms to find the shortest path on a grid.
Algorithms: Implement adaptve algorithms which respond to current
conditons.
2D Coordinates: Work with data assigned on a 2D grid.
Lesson 6: Feedback with "WallRider"
We will learn about feedback and contnuous-tme commands.
Translaton: Control robot velocity using meters/second.
Rotaton: Control robot angular velocity using radians/second.
Feedback Algorithms: Implement feedback to create a stable control algorithm.
Sensors: Use a distance sensor as an input to an algorithm.
Optmizaton: Tune an algorithm to improve a result.
Lesson 7: Image Processing with "LineRider"
We will learn about arrays and contnue to improve our skills with feedback algorithms.
Translaton: Control robot velocity using meters/second.
Rotaton: Control robot angular velocity using radians/second.
Arrays: Work with a 1D array in python.
Image Processing: Read a 1D camera image and interpret the pixel data.
Feedback Algorithms: Implement feedback to create a stable control algorithm.
Lesson 1: Introduction to Riders with “ScoutRider”
We will learn to make decisions in robotic coding.
Basic Blockly Commands: Discover simple Blockly commands that will enable you to perform a task.
Algorithms: Connect multiple instructions to create a sequence.
Problem Solving: Solve increasingly difficult logic puzzles.
Simple Transition: Move from one point to another along a floor in single steps.
Simple Rotation: Learn right and left turns within an algorithm.
Lesson 2: Programming Loops with "DirtRider"
We will learn about while loops.
While Loops: Implement While loops in Blockly.
Patterns: Recognize and apply patterns.
Algorithms: Connect multiple instructions to create a sequence.
Simple Transition: Move from one point to another along a floor in single steps.
Simple Rotation: Turn right and left in an algorithm
Lesson 3: Conditional Statements with "HotRider"
We will learn to use conditional statements in robotic coding.
Conditional Statements: Implement if and elif statements in Blockly.
Algorithms: Implement adaptive algorithms that respond to current conditions.
Simple Transition: Move from one point to another along a grid in single steps.
Simple Rotation: Turn right and left in an algorithm.
Lesson 4: For Loops with “GarbageRider”
We will learn about for loops.
For Loops: Repeat a certain number of times over a set course.
Refactoring: Improve code efficiency.
Patterns: Recognize and apply patterns for algorithm development.
Transition: Move from one point to another along a floor using fractional steps.
Coordinates: Recognize the points marked on an obstacle course.
Rotation: Rotate using radians to apply simple left/right rotations.
Lesson 5: Pathfinding with “LabRider”
We will learn about path finding and flood-fill algorithms.
Double For Loops: Implement nested for loops.
While Loops: Implement while loops in Blockly.
Path Finding: Implement algorithms to find the shortest path on a grid.
Algorithms: Implement adaptve algorithms which respond to current
conditons.
2D Coordinates: Work with data assigned on a 2D grid.
Lesson 6: Feedback with "WallRider"
We will learn about feedback and contnuous-tme commands.
Translaton: Control robot velocity using meters/second.
Rotaton: Control robot angular velocity using radians/second.
Feedback Algorithms: Implement feedback to create a stable control algorithm.
Sensors: Use a distance sensor as an input to an algorithm.
Optmizaton: Tune an algorithm to improve a result.
Lesson 7: Image Processing with "LineRider"
We will learn about arrays and contnue to improve our skills with feedback algorithms.
Translaton: Control robot velocity using meters/second.
Rotaton: Control robot angular velocity using radians/second.
Arrays: Work with a 1D array in Blockly.
Image Processing: Read a 1D camera image and interpret the pixel data.
Feedback Algorithms: Implement feedback to create a stable control algorithm.
Why wait to master the
world of Robotics?
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