Nanodegree Robotic Engineer

Nanodegree Robotic Software Engineer

The Robotics Software Engineer Nanodegree program focuses on teaching the core robotics skills needed for a successful robotics software engineering career. The program focuses on Localization, Mapping, SLAM, Path Planning, and Navigation. These are taught using C++ and the Robot Operating System (ROS) framework.
About the Nanodegree

Demand for software engineers with advanced robotics skills far exceeds
the current supply of qualified talent. This makes this an ideal time to pursue career advancement in this field, and this program represents a great
opportunity to develop and practice core robotics skills such as C++, ROS, and probabilistic robotics algorithms such as Localization, Mapping, SLAM, Path Planning and Navigation.

ESTIMATED TIME

4 months

8 – 10 hours / week

August 23, 2021

REGISTER BEFORE

What will you learn

You will graduate from this Nanodegree program having completed five hands-on robotics projects in the Gazebo simulator; these will serve as portfolio pieces demonstrating your acquired skills to hiring managers and recruiters. These skills will help you pursue and advance a career in the robotics field.

PREREQUISITES FOR ENROLLMENT
To succeed in this Nanodegree program, you should have experience with the following: • Advanced knowledge in any object-oriented programming language, • preferably C++ • Intermediate Probability • Intermediate Calculus • Intermediate Linear Algebra • Basic Linux Command Lines
Gazebo World

Learn how to simulate your first robotic environment with Gazebo, the most common simulation engine
used by Roboticists around the world.

Course Project Build My World

Use the tools that you’ve learned in Gazebo to build your first
environment.
Key Skills Demonstrated:
• Launching a Gazebo Environment
• Designing in Gazebo

ROS Essentials

Discover how ROS provides a flexible and unified software environment for developing robots in a modular and reusable manner. Learn how to manage existing ROS packages within a project, and how to write ROS Nodes of your own in C++.

Course Project Go Chase It!

Demonstrate your proficiency with ROS, C++, and Gazebo by  building a ball-chasing robot. You will first design a robot inside Gazebo, house it in the world you have built in the Build My World project, and code a C++ node in ROS to chase yellow balls.
Key Skills Demonstrated:
• Building Catkin Workspaces
• ROS node creation
• ROS node communication
• Using additional ROS packages
• Gazebo world integration
• Additional C++ practice
• RViz Integration

Localization

Learn how Gaussian filters can be used to estimate noisy sensor readings, and how to estimate a robot’s position relative to a known map of the environment with Monte Carlo Localization (MCL).

Course Project
Where Am I?

You will interface your own mobile robot with the Adaptive Monte Carlo Localization algorithm in ROS to estimate your robot’s position as it travels through a predefined set of waypoints. You’ll also tune
different parameters to increase the localization efficiency of the robot.
Key Skills Demonstrated:
• Implementation of Adaptive Monte Carlo Localization in ROS
• Understanding of tuning parameters required

Mapping and SLAM

Learn how to create a Simultaneous Localization and Mapping (SLAM) implementation with ROS packages and C++. You’ll achieve this by combining mapping algorithms with what you learned in the localization lessons.

Course Project
Map My World

Students will interface their robot with an RTAB Map ROS package to localize it and build 2D and 3D maps of their environment. Students must put all the pieces together properly to launch the robot and then teleop it to map its environment.
Key Skills Demonstrated:
• SLAM implementation with ROS/Gazebo
• ROS debugging tools: rqt, roswtf

Path Planning and Navigation

Learn different Path Planning and Navigation algorithms. Then, combine SLAM and Navigation into a home service robot that can autonomously transport objects in your home!

Optional KUKA Path Planning

Optional Course Project
KUKA Path Planning

Students will apply what they have learned about ROS and path planning to search for a path and navigate a KUKA robot through a 2D maze.
Key Skills Demonstrated:
• Path planning
• Using C++ and Python with external ROS API

Mentor Support
  • Support for all your technical questions.
  • Questions answered quickly by our team of technical mentors.
  • Responsibility
  • Your mentor will help you stay on track and achieve your goals.
Program Offers It includes
Real world projects Yes
Project reviews Yes
STUDENT SERVICES
Mentor Tech Support Yes
Student community Yes
CAREER SERVICES
CV support Yes
Freelance Projects Yes

Real World Project

Develop an End-to-End project that will allow you to interact in a real work environment.
Matrícula

La matrícula completa del programa es de $ 10,140. Si paga por adelantado, obtiene un 16% de descuento. Recuerde, si no consigue un trabajo dentro de los 6 meses posteriores a la finalización, recibirá un reembolso completo. Ver los términos de elegibilidad de la garantía de empleo

 
Descuento por adelantado | Pague por adelantado y ahorre un 16% en la matrícula | $5000
Pagado al momento de la inscripción
$ 5000
 
Coste total
$5000
Mes a mes | Paga solo los meses que necesites, hasta 6 meses $ 1,690 / mes Total: hasta $ 10,140
Pagado al momento de la inscripción
Depósito reembolsable de
$ 700
Pagos mensuales durante el curso
$ 0
Pagos mensuales después del curso
$ 383 por 36 meses después de comenzar un nuevo trabajo
 
Coste total
$ 14,500
Plan de matrícula diferida | Pague mensualmente solo después de comenzar un trabajo $ 383 / mes Total: $ 14,500
Pagado al momento de la inscripción
Depósito reembolsable de
$ 700
Pagos mensuales durante el curso
$ 0
Pagos mensuales después del curso
$ 383 por 36 meses después de comenzar un nuevo trabajo
 
Coste total
$ 14,500

Jobs

Results-oriented learning

devnow.org is a partner of Bootcamp AI, a platform with updated job offers.

New

Asynchronous program access

Pay as you go
$
55
Monthly
  • Maximum flexibility to learn at your own pace.
  • Slack Community
  • Access to all sessions
  • Access to all quizzes
  • Access to all projects
  • Access to Laboratories
  • Cancel at any time.
New

+ 50% of your salary for the first month when you get a job

  • If you cannot find a job, we will exempt you from paying 50% of your first salary.
  • You must complete the 4 months of the program
Best rated

4 MONTH ACCESS

Pay in advance and save an additional 15%
$
170
Total
  • 4 months is the average time to complete this program.
  • Save an additional 30% compared to pay-as-you-go.
  • Slack Community
  • Access to all sessions
  • Access to all quizzes
  • Access to all projects
  • Access to Laboratories
  • Cancel at any time.
  • Change to the monthly price later if you need more time.
New

+ 50% of your salary for the first month when you get a job

  • If you cannot find a job, we will exempt you from paying 50% of your first salary.
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Tulio Velásquez
Gerente Arq Tecnología
The mentor has clarity on the material and how the step-by-step for each implementation is explained. The mentor has the knowledge and makes an easy understanding of the course.
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Melani Stefania Ruales
Fellow
I think it has qualified teachers and the topics in the courses are super good. She is a good teacher, who she knows about the topics to be covered. It is also dynamic when teaching the class
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Diana Jaramillo
Fellow
The mentor is experienced. I like that there are labs and that I can review the recorded classes.
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Bryan Xavier Landázuri
Felow
Each class module was interesting and each laboratory that was carried out had its respective guide. It was well explained, I presented many applications of the various topics that were seen during the course

María  Cruz

Mentora

Lead Data Scientist en BAT. Doctora en Control Automático con especialidad en procesamiento de Imágenes. Estancias de investigación en la Universidad de California en EEUU, en la Universidad de Coimbra en Portugal y trabajos de investigación con la Universidad de Yale

Jenny Vega

Mentora

Machine Learning Engineer Rappi Software Engineer con más de 5 años de experiencia en el desarrollo de aplicaciones de big data y machine learning altamente escalables. Con sólidos conocimientos y práctica en lenguajes de programación como Python y Javascript. Arquitecta Asociada de AWS. Autodidacta de nuevas tecnologías y frameworks dentro de machine learning e inteligencia artificial.

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FAQ

Bootcamp AI is an organization that helps reduce the technological gap in the world, we have professional Nanodegrees curated by experts focused on job placement.

Professional program focused on the career you want to pursue.

Exclusive section to improve your professional profile, code test and improve your personal brand.

We work with devnow.org, a platform for jobs and freelance jobs with the best technology companies.

Accompaniment in your selection processes

As you progress through the program according to your performance, you are assigned paid projects from real companies, you can accept or reject.

You can have an ROI (Return on Investment) in the program of 200% return.

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