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You want to become a Robotics Software Engineer!?
You have a job in a field that you used to be passionate about. It probably pays you well enough to sustain yourself and your loved ones. So, you stay at your job because it pays the bills. For the first 6 months, you find it fascinating. You are learning!
The next 6 months fly by quickly as you start contributing to projects. Another year goes by. You are decent at your job, and you probably connect well with your colleagues. You spend the weekends enjoying the fruits of your labor and spend time with the people close to you.
Life is comfortable.
But something is missing!
All these years of following the path that the society asked you to follow have slowly killed the spark that you once had. The work does not light you up as much as it did before. You wanted to learn! You wanted to grow! And contribute to something meaningful!
Something significant enough to have an impact on the world. And yet you feel tied to your dead-end job. Because of money? Familial pressures? Comfort? The truth is that most people start working in their early 20s and work till they are 65. This means that you will spend a vast majority of your life (at least 2,000 weeks) doing serious adult work. If work contributes to a vast majority of your life, a boring/mediocre career = an unfulfilled life.
Some of you are conscious enough to come to the conclusion yourself.
And you start taking action towards something that has fascinated you for a long time.
ROBOTICS
Couple that with the current boom within the robotics industry and the promise of autonomous household robots, and you start taking action.
You start applying for jobs! Only to realize that you lack the skills and the experience to enter the industry.And that you are competing with people who have a master's degree in robotics/artificial intelligence. You take more action.
This time to level up your skills to deserve that dream robotics job.
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"I don't know where to start."
This is perhaps the biggest problem you face when starting to learn fields such as Robotics, Computer Vision, Machine Learning or any sub-domain of Artificial Intelligence.In today's day and age there is an abundance of resources made available to each and every one of us. On the click of a button, you can get access to the best video lectures from the top universities in the world. You get access to novel projects and repositories contributed by great content creators and robotics and machine learning engineers and researchers. A variety of different types of courses are available to each and every one of us at a very nominal cost.
Having looked at this information, it sounds like you are making an excuse. If you were motivated enough, you should have been able to take advantage of the resources and start learning robotics, computer vision, or machine learning already, right? Well, yes and no!
Although the vast amount of resources makes education accessible to everyone with a decent internet connection, resource abundance is a double-edged sword. Accessibility comes at the cost of overwhelm. Beginners with little-to-no knowledge about robotics find themselves easily overwhelmed, as they do not know which resources to refer to. They try out a few Arduino projects, take up an online course, and watch a few tutorials online, never really finding one specific subdomain they would want to master to a professional level.
Then, there are these buzz words that are being thrown around all the time.
ROS, ROS 2, Gazebo, Manipulation, Nav2, OpenCV, Ubuntu, Tensorflow, Machine Learning, Artificial Intelligence, Robotic navigation, Grippers, Deep Learning, Reinforcement Learning, Controls, System Identification, Git, Docker, ...
I am sure you have heard even more. It is hard not to be overwhelmed by this. Plus, we see a new AI tool being launched on a weekly basis if not every day. Unitree Robotics reveals its new humanoid performs its back-flip, Agility Robotics releases their new foundation model for general robot grasping. NVIDIA makes another crazy announcement on how they plan to design chips specifically for Robotics. And OpenAI releases a new large language model (because why not?).
If all this does not overwhelm you, you are probably not a human but an AI robot yourself.
Looking at all the crazy developments over the past few years, it isn't totally outrageous to say that we are already living in the future. Or we are getting very close towards an existence, in which robots would be an integral part.
It is the smartphone era for Robotics. Robots will be in the factories, in the hospitals, in the offices and in the homes sooner or later (Probably more sooner than later!). You can either watch this happen or be an active part of this revolution!
For me the only option was going for a Master's in Robotic Systems Engineering. I did not know any better.
The number 1 thing that I got from the master's program was the well-defined structure that the University offered. The program allowed me to explore several sub-domains in robotics and take up elective subjects of my interest. This was good exposure!
However, I was only able to cultivate the right skill set that the industry would value by working for the industry. I took up multiple working student and internship roles along with additional projects in research institutes to gain exposure to enough sub-domains in robotics so that I could choose one specific niche I would like to work in. And this is where a majority of my "real" learning was—working for startups, bigger companies, and research institutes on real-world projects.
And I understand that going for a master's is not a real possibility for a large proportion of engineering students/working professionals. There can be time constraints, monetary constraints, and social and familial constraints, just to name a few.
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I am here to tell you that it is absolutely possible to become a self-taught Robotics Software Engineer.
I can say this so confidently because of the following reasons :
1️⃣ Realize that M.Sc./ M.Tech in Robotics/ Data Science/ Machine Learning are just starting to become mainstream. This was not widely taught as a specialization even 5 years ago. There were fewer such courses. But the industries still employed Machine Learning Engineers. Most of the people had to learn it on the job because one or more projects at their company required that.
2️⃣There are countless examples of people who switched from Mechanical/ Electronics engineering to software engineering. Software engineering is at the core of AI.
3️⃣ For a new job, you have to learn new skills anyway. Even if you have prior experience in, let's say, Computer Vision, you have to deal with certain tools and frameworks that are specific to the company. So, you are learning on-the-job in any case.
4️⃣ A candidate who demonstrates their skill-set acquired by doing projects on their own shows self-initiative and that they have the ability to work independently and are disciplined enough. Such a candidate will often even stand out in comparison to other candidates.
5️⃣ At the end of the day, a company values the right skill-set in a candidate. Such a skill-set can be developed by taking part in practical projects. If you have a portfolio of projects that you developed, that is demonstration of your work experience. And such experience is in no way less as compared to someone who has a Master's in Robotics/ Data Science/ Artificial Intelligence. Your skill-set is your most valuable asset.
So, get rid of the idea that it is not possible to become a self-taught professional roboticist/ AI engineer. You just need to get rid of this limiting belief and start learning.
And the single biggest reason why you constantly fail to start learning is because you lack a...
clear, systematic, step-by-step, practical, project-based, personalized, and well-defined roadmap!
That's it. That's all you need. You need a system - A system that is tailored to your own individual goals and needs, is project-based, and gives you the skill set that would make you employable in the industry.
I have been thinking about the problem of finding the "best way to learn robotics and AI" for a very long time now. I started thinking about it when I was working full-time as a mechanical design engineer and started learning robotics on my own with only the internet at my disposal.
After years of conceptualization of the idea, making use of my practical exposure to industry and academia, experience of studying in a top-notch conventional master's program, and just a lot of trial-and-error, I would like to share with you the exact roadmap that you can use to become a "self-taught" robotics software engineer!
But before I introduce you to my
system, let's talk about money.
While money should not be the primary motivator, it undeniably is a very powerful resource!
And, hence any career decisions need to take monetary ROI (Return on Investment) into account.
The amount of money you earn is directly proportional to the value you offer to the world.
So, if you want to earn loads of money while doing the things that you love anyway, while at the same time learning and growing continuously and having a significant impact on the world, you need to master the skills that the companies would value.
Money Earned ∝ Value offered ∝ Your skillset
So, if there is one thing you need to become a well-paid professional Robotics Software Engineer, that is: Industry-relevant skillset
And once you make an investment to develop a strong skill set, you unlock a higher pay scale. Robotics Software Engineers offer immense value to the companies and hence are one of the highest paid profiles in the industry.
A typical Master's Program in the United States would cost you Tens of Thousands of dollars.
To study in such programs, you would most likely need to take a student loan. Student loans are a huge gamble and the likelihood of you getting a return of that investment is actually very low.
We just do it because everyone else is doing it and hence it seems more trustworthy.
And even if you can afford the tuition fee, a Master's Degree is no guarantee that you will work at your dream Robotics company.
You would still have to demonstrate your technical skillset by mastering the right tools and frameworks used in the industry and showcasing company-relevant projects. You would still need to clear technical interviews and coding tests.
What if you can bypass the entire conventional route of going for a Master's, then building projects and then applying for jobs and directly focus on what is and has always been the most important thing for the industry.
Your skillset.
Skill beats degree any day!
What if you invested all of that time, energy, and money towards cultivation of your technical skillset?
How much more efficient would that be?
You save time, energy, and money and increase your likelihood of having a high-paying career.
Win-Win-Win
Also, most university master's programs would teach you all the theoretical concepts within all major sub-domains within robotics and AI, such as computer vision, kinematics, dynamics, machine learning, control theory, sensor systems, and simulation. Now this is generally a good thing ...
But if your goal is to work as an academic researcher. If you want to work in academia and publish papers, you need to have a strong technical foundation and hence this is probably an effective (although still not efficient) way to create Robotics and AI Researchers.
This is the reason why there is emphasis on understanding the algorithms deeply and having a strong theoretical foundation. And not too much on the technical skillset - Which the Industry values more.
The primary task of a researcher is not to build robotic systems but to conduct experiments with a goal to discover novel algorithms and solutions to unsolved research problems and then publish papers.
Researchers publish papers whereas engineers build and program things.
The university curriculum is designed for the researchers by the researchers.
Trust me, I have worked in Research and I know this very closely.
However, you probably, like most graduate students, want to work in the industry.
Which means that your publications are not the most important thing.
Your technical skillset is.
So, why would you spend years learning all the theoretical algorithms within all domains of Robotics and AI?
You would forget most of it anyway because you would never use most of it in the real world.
If your goal is to become a Robotics Software Engineer, this is a huge waste of time.
The system that is used in this course is not just practical and suited for Robotics Software Engineering roles but is also highly efficient. You would get straight to learning the foundation skills, tools, and frameworks and building projects without wasting time watching long, boring lectures or learning theoretical concepts you would never use anyway.
By the way, if you are curious about how I personally transitioned from Mechanical Engineering to Robotics, here is a long-form unfiltered video of my own learning journey for you.
If you are ready to take your career seriously and transition to robotics, here are the modules for the course "Become a self-taught Robotics Software Engineer":
Get a certificate by the end of the course, but more importantly your dream job at your favourite Robotics company and a fulfilling career in Robotics Software Engineering!
Projects available in the course:
Mini-projects (Included in the Self-taught and all Skilled-professional plans)
Curiosity-driven mini-projects
Hand-writing recognition
using LeNet
Face Blur for
Street interview
Playing Atari using
Deep Reinforcement Learning
Domain-specific mini-projects ⭐
Task and motion planning
in a factory setting
Inverse kinematics
of a 3 DOF arm
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Foreground object extraction using segmentation
Cloth detection using YOLO
Course Preview
Private Accountability Group Preview
❓ "But what if I get stuck while doing a project?"
❓ "What if I lose my rhythm?"
❓ "And what if I do not know what next step to take?"
❓ "What if you are unable to debug an obscure problem in my project?"
Well, I am absolutely sure, you will. In fact, it is only normal to face obstacles when building projects for the first time.
Which is why you get exclusive access to a Private Accountability Group as part of this course. This group allows you to form accountability groups to discuss topics with, do projects with and keep each other accountable to your learning goals. Moreoever, I, myself, am available 24-7 to answer any of your queries or problems associated with any of the modules within the course.
Join 150+ Professionals Making The Same Career Transition to Robotics
Course Preview:
Week 0: About the instructor
Week 0: Module Overview
All plans except the "Entry-level plan" are subject to a 7-day refund policy. To claim your refund, shoot an e-mail at learnroboticsandai@gmail.com with a valid reason for cancellation
NOTE: The prices are subject to change based on course updates
Entry-level plan
299
Lifetime access to the course content
Curated lists of resources for skill development
Roadmaps for Perception, Planning, Learning, Control
Curated list of 12 mini-projects in different domains
Job application guide
Self-taught plan
599
Lifetime access to the course content
Curated lists of resources for skill development
Roadmaps for Perception, Planning, Learning, Control
Curated list of 12 mini-projects in different domains
Job application guide
Free access to new course modules
Quizzes to test your understanding
Solutions to 3 curiosity-driven mini-projects ⭐
Solutions to Learning and Control mini-projects ⭐
Solutions to Perception and Planning mini-projects ⭐
Membership to Private Accountability Group
Monthly Meetups
Niche-pro plan: Perception
799
Lifetime access to the course content
Curated lists of resources for skill development
Roadmaps for Perception, Planning, Learning, Contro
Curated list of 12 mini-projects in different domains
Job application guide
Free access to new course modules
Quizzes to test your understanding
Solutions to 3 curiosity-driven mini-projects ⭐
Solutions to Learning and Control mini-projects ⭐
Solutions to Perception and Planning mini-projects ⭐
Monthly Meetups
Membership to Private Accountability Group
Solution for ⭐⭐⭐⭐ niche project - Perception
Solution for ⭐⭐⭐ niche project - Perception
Solution for ⭐⭐ niche project - Perception
Productivity guide for aspiring Roboticists
SCRUM Guide
List of Robotics companies in US, Germany and India
Guide to clearing coding tests
Coding test samples from top Robotics companies in Germany
Access to my actual CVs and Cover Letters
Choose your pricing plan
Find one that works for you
Individual modules are not subject to the 7-day cancellation policy
NOTE: The prices are subject to change based on course updates
Mathematics for Robotics
199
Comprehensive list of Mathematics resources for Robotics
Self-Assessment Test
Linear Algebra fundamentals
Calculus and numerical methods fundamentals
Geometry fundamentals
Statistics and probability fundamentals
Practical quizzes to test your understanding
Python and C++ programming solutions for every concept
Robotics applications for every concept
Easy-to-understand illustrations for each concept
Robotics Job Seeker Blueprint
199
Access to REAL coding tests from REAL ROBOTICS companies
Complete Guide to clearing coding tests
List of companies in US, Germany, India & beyond
Customizable job tracking guides
Access to my actual CVs and cover letters
Customizable templates for CVs and portfolios
Buy individual modules
Already included fully in Self-taught and Skilled-professional plans
and partially in the Entry-level plan