Autonomous Systems Engineer

Design, build, test, and operate autonomous systems that combine robotics, sensing, AI, embedded software, simulation, and safety engineering.

4Modules

16 WeeksWeeks Duration

TBCAvg. Salary

TBCJob Placement

OUR GRADUATES ARE HIRED BY

About this course

The Autonomous Systems Engineer program prepares learners to design, simulate, integrate, and validate intelligent systems that can sense, decide, and act in dynamic environments. Over 16 weeks you will build foundations in robotics, embedded systems, perception, planning, control, autonomy software, simulation, safety, and deployment, graduating with a portfolio-ready autonomous systems capstone.

You'll have access to:

6 Live Sessions

16 Audio Lessons

Book Summaries

Robotics & Autonomy Projects

Simulation Labs

GitHub Portfolio

Autonomous Systems Engineer Certificate

Duration: 16 Weeks (4 Months)

Choose Your Learning Path

Standard Bundle

Tools You'll Learn

Python

ROS 2

OpenCV

NumPy / SciPy

Gazebo / Isaac Sim

GitHub / CI/CD

Linux / Bash

Safety & Systems Engineering Toolkits

Autonomous Systems Engineer — Hybrid Program

Topics Breakdown

Week 1

Autonomous Systems Landscape & Engineering Workflow

Key Points

• Autonomous systems categories: robotics, drones, vehicles, industrial systems, and smart devices
• The sense-plan-act loop and how autonomy stacks are structured
• Autonomy levels, operating design domains, and human supervision models
• Hardware, software, data, and safety boundaries in autonomy projects
• Systems engineering lifecycle: requirements, design, integration, validation, and operations
• Project constraints: cost, latency, energy, reliability, environment, and regulation
• Capstone selection and portfolio documentation setup

Summary

Build a clear map of the autonomous systems field and the engineering workflow used to move from concept to validated deployment. You will define your capstone scope and connect system requirements to technical design choices.

Skills Developed

Autonomy stack mapping

Systems thinking

Requirements analysis

Capstone scoping

Engineering communication

Week 2

Python, Linux & Robotics Development Environment

Key Points

• Python for robotics and autonomy applications
• Linux command line workflows for engineering projects
• Virtual environments, package management, and dependency isolation
• Git and GitHub workflows for version-controlled autonomy projects
• Project structure for reproducible simulations and experiments
• Logging, debugging, and error tracing in technical systems
• Documentation practices for engineering notebooks and repositories

Summary

Set up a professional development environment for autonomy work. You will practise Python, Linux, Git, debugging, and project organization patterns used in robotics and intelligent systems teams.

Skills Developed

Python development

Linux workflows

Git version control

Debugging

Technical documentation

Week 3

Sensors, Actuators & Embedded Interfaces

Key Points

• Sensor types: cameras, LiDAR, radar, IMU, GPS, encoders, ultrasonic, and tactile sensors
• Sensor noise, calibration, sampling rates, drift, and synchronization
• Actuator types: motors, servos, steering systems, grippers, and electronic speed controllers
• Embedded communication interfaces: serial, I2C, SPI, PWM, and CAN concepts
• Data acquisition and signal conditioning basics
• Latency, timing, and power constraints in physical autonomous systems
• Basic hardware safety checks before integration and testing

Summary

Understand how autonomous systems sense and act in the physical world. You will learn the role of common sensors, actuators, embedded interfaces, timing constraints, and safety checks.

Skills Developed

Sensor selection

Actuator fundamentals

Embedded interface literacy

Calibration awareness

Hardware safety checks

Week 4

Robotics Middleware & ROS 2 Fundamentals

Key Points

• ROS 2 concepts: nodes, topics, services, actions, messages, and parameters
• Building and organizing ROS 2 workspaces and packages
• Publishing and subscribing to sensor and control data
• Launch files, configuration, and runtime parameter management
• Coordinate frames, transforms, and robot state representation
• Recording, replaying, and inspecting system data with bag files
• Debugging communication across distributed robotics components

Summary

Learn the middleware patterns used to connect autonomous system components. You will build ROS 2 nodes, exchange data, configure launches, inspect transforms, and debug distributed robotics workflows.

Skills Developed

ROS 2 fundamentals

Distributed component design

Message-based communication

Transform management

Robotics debugging

Our proven approach to student success

Maybe you’ve tried YouTube or a low-cost web development course. If you have, you know learning on your own can only take you so far. Humans learn best from other humans.
Ustack’s proven human-centric approach means you have a team behind you from day one.

Mastery from your mentor

Build software engineering skills faster with an expert in your corner. Your mentor will keep you accountable and give you an insider's view.

Counsel from your career coach

Get prepared for the job search. Your career coach will help you gain confidence and know-how to land the role.

Support from your student advisor

Stay on track and achieve your goals. Your student advisor has your back and will keep you on track to graduation.

Build a portfolio that proves your skills to hiring managers

In this bootcamp, you’ll work on six hands-on mini projects and five full portfolio projects, including a capstone product you can proudly showcase. By the end, you’ll have an interview-ready portfolio that proves your skills to hiring managers—and sets you apart from the crowd.

Projects by our Graduating Students

Effective Compliance Training with VR

While other companies use lengthy, monotonous compliance training, SISU VR’s product uses virtual reality to make this a more immersive and educative experience. They deliver compliance and prevention training with the competitive edge of Virtual Reality with immersive, realistic situations.