ENROLLMENT: OPEN
Robotics 101

Master the First Principles
of Robotics

Stop copying code you don't understand. Build a complete autonomous drone and ground vehicle from scratch using Control Theory and Sensor Fusion. No ROS. No shortcuts. Pure Engineering.

View Curriculum Read Manifesto

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1. Math Explained

You can't miss the dynamics in robotics. So, we will go over them first.

2. Code Explained

But we don't miss the actual implementation in the code.

3. Connect with the Virtual Robots

It's critical that you verify with the robot's behavior. Make sure to your code works as intended.

Become Indispensable

One-Man R&D Department

Most engineers in this field are stuck in the Consumer Mindset. They follow tutorials, clone repositories, and run sudo apt install like a script. They are "Integrators"—they wait for the world to build a bridge so they can walk across it.
But when the sensor fails, or the PID controller starts oscillating into a death spiral, the Integrator is powerless. They are waiting for a GitHub issue to be resolved by someone who actually understands the system.

The "Consumer" vs. The "Engineer"

The transformation begins when you stop seeing code as "software" and start seeing it as physics in digital form.

The Integrator sees a library. They wait months for a ROS package to support a new sensor. The Engineer sees the math. They realize that a sensor integration isn't a coding task—it's a coordinate frame transformation.
When you understand the underlying reality, you don't wait. You simply adjust the model:

The Math is the Map

Imagine you’ve mounted your sensor at a 45-degree offset. The "Integrator" panics, searching for a software flag or a library update that doesn't exist.

The Engineer doesn't wait. They realize that a physical rotation is just a linear transformation. By multiplying the Observation Matrix (H) by a Rotation Matrix (R), you instantly align the sensor's "eyes" with the robot's "body."

This small adjustment flows directly into the Kalman Gain:

H_new = H @ R_matrix
K = P @ H_new.T @ inv(H_new @ P @ H_new.T + R)

To an integrator, this is a "black box" that crashes. To an architect, this is the heartbeat of the system’s certainty. You aren't just coding; you are commanding how the machine perceives reality.

(Don't understand the math in this example or how that multiplication fixed the filter? That’s exactly why I built this course)

Your New Identity: The One-Man Command Center

Robotics 101 is designed to break your dependency on the "Consumer" cycle. We strip away the abstractions until you are left staring at the raw physics and noisy data.

This is where you evolve.

You are no longer a "coder." You are an Almighty Architect. In this new identity:
  • You provide the Vision: You identify exactly where the physical system is failing.
  • You command the Math: You define the logic and the constraints.
  • You lead the AI: You don't spend hours debugging syntax. You command AI agents to execute your vision because you are the only one who knows exactly what needs to be implemented.
The "hard problems" stop being hard when you know exactly what is happening under the hood. You transition from someone who uses robotics packages to the person who defines how the robot interacts with reality.
You are no longer part of the crowd. You are the one-man team that the crowd relies on.

Math -> Code -> Reality

We start with the equation. We translate it into code. We deploy it to hardware. That is the only valid learning loop.

No Black Boxes

We do not use 'easy' libraries. We build our own drivers, our own controllers, and our own state estimators.

Engineering Authority

Gain the confidence to walk into any interview and explain exactly how an autonomous system works, from the transistor to the trajectory planner.

First Principles First

Black boxes are forbidden until understood. We derive algorithms from scratch before importing them.

Math over Heuristics

We don't patch behavior with 'if' statements. We fix the cost function, the gain matrix, or the system model.

The Sim2Real Gap

Simulates often come with perfect physics. Ubicoders Virutal Robots are designed to generate the noisy signals

REALITY CHECK

Is this course for me?

Course thumbnail

This is NOT for you if...

  • The Toy-Botics Hobbyist: We treat robotics like Data Science: a rigorous discipline focused on autonomy. This course is not for you if you are looking for a hobbyist experience involving simple plug-and-play kits or basic mechanical assembly.
  • The "Black Box" Addict: You are looking for a 'magic' library that hides the math so you don't have to face the physics.
  • The Tutorial Tourist: You are addicted to the dopamine hit of finishing a tutorial, but you panic when the git clone fails.
  • The API Dependent: You are happy being a 'wrapper engineer'—someone who just glues other people’s genius together without understanding why it works.
  • The Prompt Junkie: You want an LLM to think for you, rather than using it as a tool to execute your own superior logic.

This IS for you if...

  • The Indispensable: You want to be a one-person R&D department.
  • The Mathematical Sovereign: You want to look at a complex sensor fusion problem and see the matrix, not just the error logs.
  • The AI Orchestrator: You want to spend your time architecting systems and let your AI fleet handle the boilerplate and implementation.
  • The First-Principles Thinker: You refuse to use a tool you couldn't build yourself. You crave the 'God-mode' that comes from mastering the fundamentals.
  • The System Architect: You aren't looking for a job; you’re looking to become an indispensable one-man R&D department.

What Engineers Are Saying

Really good detailed explanation of different theoretical things and really good code explanation, not just the code, but the logic behind it, planning on buying the new courses when they are out :)
— Enrique
Everything great in this course.. all the math and real time concepts are well explained. This makes easy understanding and unique when compared to other courses available out there.
— rvishnuraman
There's a lot of information out there when looking for a start into Mechatronics & Robotics. It's very difficult to find a comprehensive solution to figure out what you need to learn to get started. I went to a polytechnic school and got a 2 year diploma in Instrumentation Engineering. During my education I joined a Mechatronics club and would spend Wednesdays afternoon learning PLC Programming. This lead up to competing in SkillsAlberta and placing third. This experience spawned a love, passion and desire to learn more and continue going. I was a good student and got a job at a global engineering company through a recommendation and although I am happy and thankful, it didn't really fulfill the same joy I got out of Mechatronics. After work, I would come home and try to see where I could learn more about Mechatronics without essentially going back to school for a 4-year degree. I would ask Chat-GPT which would come up with a plan to learn but it wasn't "cohesive" enough. It would hyper focus on the different disciplines of engineering and learning heavy topics within them without much cross reference. The links would often be broken, resources recommended for learning were expensive, and it was just hard to follow. Which was why I was happy I found Elliot's Youtube videos and course. To be honest, I was fairly skeptical at the price tag, but I decided to give it a try. Although I have not completed the course yet, I have been very happy with the experience. I've searched sites like Coursera & Alison Free Learning for alternatives and nothing really comes close to this. Maybe bits and pieces of what you may want to learn but not a complete package. Ubicoders provides a streamlined path for learning and the expertise in an organized manner. It is truly a one of a kind package, and if you're interested in learning more about Robotics, I highly recommend Ubicoders as your starting point. As a cherry on top, when struggling with an issue during the Windows WSL Setup, I reached out to Elliot on discord, he responded kindly & quickly with personalized help and even updated the course instructions to provide future clarity. That type of service goes above and beyond and really speaks to how much he cares about helping others learn. ~Kaid
— K. Miller
This course teaches a lot of hard math in simple words and in small amount of time. For people that want to make things its ideal because you don't have remember eveything because you accualy understand material when you code your own robot eveything is just logical to you and algorithms bacome fun when programing. Course offers you a couple of simulators where you can test your code like on real vechicle. If you are someone who want to really dive into robotics you found a perfect place to start.
— S. Nyderek
this is a no-brainer for people who are interested in robotics but don't know where to start. a good mix a theory and practice.
— Sebastien
Thank you for making this course so practical focussed. It took me from an amateur to intermediate level. Looking forward to the next one.
— A. Jadhav
This course provided working examples of code while making the mathematics needed for robotic control practical and intuitive. The simulator was a helpful motivator and comprehension check.
— D. Rocha
The course provides everything you need to start your robotics career, and even more, it includes the holy grail of robotics, which is often omitted in other classes. I mean the basics of math, which are crucial to understand and learn robotics. So, if you want to start and skyrocket your career, but don't know how and where, don't wait and choose this course.
— Robert
This course offers a no fluff breakdown on the complex topics of robotics. It's a great way to get exposure to core robotics concepts.
— C. Lucido
Really good detailed explanation of different theoretical things and really good code explanation, not just the code, but the logic behind it, planning on buying the new courses when they are out :)
— Enrique
Everything great in this course.. all the math and real time concepts are well explained. This makes easy understanding and unique when compared to other courses available out there.
— rvishnuraman
There's a lot of information out there when looking for a start into Mechatronics & Robotics. It's very difficult to find a comprehensive solution to figure out what you need to learn to get started. I went to a polytechnic school and got a 2 year diploma in Instrumentation Engineering. During my education I joined a Mechatronics club and would spend Wednesdays afternoon learning PLC Programming. This lead up to competing in SkillsAlberta and placing third. This experience spawned a love, passion and desire to learn more and continue going. I was a good student and got a job at a global engineering company through a recommendation and although I am happy and thankful, it didn't really fulfill the same joy I got out of Mechatronics. After work, I would come home and try to see where I could learn more about Mechatronics without essentially going back to school for a 4-year degree. I would ask Chat-GPT which would come up with a plan to learn but it wasn't "cohesive" enough. It would hyper focus on the different disciplines of engineering and learning heavy topics within them without much cross reference. The links would often be broken, resources recommended for learning were expensive, and it was just hard to follow. Which was why I was happy I found Elliot's Youtube videos and course. To be honest, I was fairly skeptical at the price tag, but I decided to give it a try. Although I have not completed the course yet, I have been very happy with the experience. I've searched sites like Coursera & Alison Free Learning for alternatives and nothing really comes close to this. Maybe bits and pieces of what you may want to learn but not a complete package. Ubicoders provides a streamlined path for learning and the expertise in an organized manner. It is truly a one of a kind package, and if you're interested in learning more about Robotics, I highly recommend Ubicoders as your starting point. As a cherry on top, when struggling with an issue during the Windows WSL Setup, I reached out to Elliot on discord, he responded kindly & quickly with personalized help and even updated the course instructions to provide future clarity. That type of service goes above and beyond and really speaks to how much he cares about helping others learn. ~Kaid
— K. Miller
This course teaches a lot of hard math in simple words and in small amount of time. For people that want to make things its ideal because you don't have remember eveything because you accualy understand material when you code your own robot eveything is just logical to you and algorithms bacome fun when programing. Course offers you a couple of simulators where you can test your code like on real vechicle. If you are someone who want to really dive into robotics you found a perfect place to start.
— S. Nyderek
this is a no-brainer for people who are interested in robotics but don't know where to start. a good mix a theory and practice.
— Sebastien
Thank you for making this course so practical focussed. It took me from an amateur to intermediate level. Looking forward to the next one.
— A. Jadhav
This course provided working examples of code while making the mathematics needed for robotic control practical and intuitive. The simulator was a helpful motivator and comprehension check.
— D. Rocha
The course provides everything you need to start your robotics career, and even more, it includes the holy grail of robotics, which is often omitted in other classes. I mean the basics of math, which are crucial to understand and learn robotics. So, if you want to start and skyrocket your career, but don't know how and where, don't wait and choose this course.
— Robert
This course offers a no fluff breakdown on the complex topics of robotics. It's a great way to get exposure to core robotics concepts.
— C. Lucido

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Back to Foundations

The Curriculum

Main Topics

🚀 Kalman Filter: The #1 robotics interview question.

🚀 Inertial Sensors: The most popular yet notorious sensors for beginners in robotics.

🚀 Rotation Matrix: The alphabet of robotics engineering.

🚀 State-Space Method: A foundational building block of modern control engineering.

Prerequisites

🚀 Python basics (if, for, array, function, class)

🚀 Calculus (derivative, integral)

🚀 Linear algebra (matrix & vector multiplication)

🚀 Differential equations - d e(x) /dx = ?

🚀 Statistics (mean and variance)

Onboarding

  • Intro
  • Backgrounds
  • Course Guide (Download The Code Here)
  • Which Code Environment?
  • What is Conda? (Optional)
  • What is Docker? (Optional)
  • Easy Setup Windows Conda
  • Easy Setup Mac Conda
  • Standard Setup Ubuntu 22
  • Standard Setup - Windows WSL

Review: Python & Math

  • 1) Python Basics 1
  • 2) Trig. Functions
  • 3) Calculus
  • 4) Taylor Series & Fourier Series
  • 5) Linear Algebra
  • 6) Differential Equation
  • 7) Statistics (Mean and Variance)
  • 8) Statistics (Gaussian Distribution)
  • 9) Eigen Values and Vectors
  • 10) Closure

Level 0: Giving You Items and Weapons for Level 1

  • 1) Level Introduction
  • 2) Virtual Robot Scripts
  • 3) Realtime Graphing
  • 4) Data Collection
  • 5) Terminals in Virtual Robots
  • 6) PID Control 1
  • 7) PID Control 2
  • 8) PID Control 3
  • 9) PID Control 4: Cascade PI
  • 10) States
  • 11) Rotation Matrix 1
  • 12) Rotation Matrix 2
  • 13) Rotation Matrix 3
  • 14) Inertial Sensors
  • 15) Inertial Sensors: Accelerometer
  • 16) Inertial Sensors: Magnetometer
  • 17) Inertial Sensors: Gyroscope 1
  • 18) Inertial Sensors: Gyroscope 2
  • 19) Inertial Sensors: Gyroscope 3
  • 20) Noise Filtering
  • 21) Noise Filtering: Average Window
  • 22) Noise Filtering: Low-pass Filter

Level 1: Quadcopter Height Control

  • 1) Introduction
  • 2) Height (Altitude) Control 1
  • 3) Height (Altitude) Control 2
  • 4) Rate Control
  • 5) Attitude Control
  • 6) Velocity Control 1
  • 7) Velocity Control 2
  • 8) Capstone

Level 2: First Sensor Fusion: IMU Theory - Direction Cosine Matrix

  • 1) DCM Introduction
  • 2) DCM Preview 1
  • 3) DCM Preview 2
  • 4) DCM Theory
  • 5) DCM Code
  • 6) DCM Multirotor

Level 3: State Space Method

  • 1) State Space Introduction
  • 2) State Space Control
  • 3) State Space Multirotor 1
  • 4) State Space Multirotor 2
  • 5) Mass Spring Damper
  • 6) Nonlinear System

Level 4: Kalman Filter

  • 1) Kalman Filter Introduction
  • 2) Kalman Filter Code
  • 3) Kalman Filter Theory
  • 4) Extended Kalman Filter

Outro

  • 1) Exit
  • 2) Course Code Answer Pack