Industrial Artificial Intelligence (AI) and Robotics Engineer

Program Description

Industrial Artificial Intelligence (AI) and Robotics Engineers research, design, develop, or test robotic application, frequently in research or medical labs, hospital, manufacturing, and industrial settings. Their responsibilities involve building, maintaining, and troubleshooting the physical hardware (“body”) of robots and intelligent machines, assembling robots, repairing broken components, performing preventative maintenance on manufacturing equipment, and setting up robotic arms. If you are interested in physical hardware, automation, and industrial maintenance, especially with foundational knowledge in AI, machine learning, and PC technician skills, then you are ready to take the next step to advance in your career journey as an Industrial AI and Robotics Engineer.

Job titles related to Industrial AI and Robotics Engineers include Robotic Systems Engineer, AI and Machine Learning Engineer, Data Scientist, Research Engineer, Automation Engineer, Autonomous Vehicle Design Engineer, Design Engineer, Factory Automations Engineer, Software Engineer, and Systems Engineer.

This program prepares students to take the Nvidia® Certified Associate Generative AI Multimodal (NCA-GENM) certification exam and a career as an Industrial AI and Robotics Engineer.  Students learn both hardware and software aspects of robotics to design intelligent and adaptable systems.

The successful candidate must be self-driven, an analytical thinker, and a problem solver as well as have exceptional planning and project management skills and can work both independently and as a team member. This career requires continued training and education.

According to the U.S. Department of Labor, overall employment of a Robotics Engineer is projected to grow 6% from 2022 to 2032 in Maryland. Projected annual job openings in Maryland are 440.  The salary range in Maryland is $50,320 - $191,880 with a median wage of $135,990.  Additional career information may be found in Career Coach: https://ccbcmd.lightcastcc.com/.

Program Objectives/Outcomes

Upon successful completion of this Continuing Education Workforce Certificate, students will be able to:

1. prepare to pass the Nvidia® Certified Associate Generative AI Multimodal (NCA-GENM) certification exam;
2. develop a comprehensive understanding of advanced computer science concepts that form the foundation of robotics software with artificial intelligence and machine learning (AI/ML), embedded systems, and execution models that govern how code is processed and run on hardware;
3. gain a strong understanding of data structures and algorithms, focusing on how to store, organize, and process data efficiently in robotics and AI applications while evaluating the performance of algorithms and learning to select the most suitable data structures for specific tasks;
4. design, implement, analyze, and optimize algorithms and code performance that improve the speed, memory usage, and reliability of robotics software systems;
5. strengthen their Python programming skills with a focus on object-oriented programming (OOP) concepts, efficient data handling techniques, and robust Python code for robotics automation, simulation control for robotics, and AI/ML integration workflows;
6. design modular programs, apply advanced coding patterns, and streamline data processing in robotics applications;
7. build a solid foundation in C/ C++ programming tailored for Arduino-based robotics application design, implement and troubleshoot programs that directly control sensors, actuators, and other robotic components through the Arduino platform;
8. gain an understanding of electronic interfacing, signal processing, and real-time control in robotics, building confidence in applying Arduino-based solutions to real-world automation challenges;
9. gain an advanced understanding of machine learning concepts, techniques, and their applications in robotics, explain the core principles of ML, differentiate between various learning types, and select appropriate strategies for different scenarios;
10. demonstrate the capability for implementing and evaluating both supervised and unsupervised learning algorithms using key metrics and performance measures, understand how to address common ML challenges, and work with industry-standard tools and frameworks such as Scikit-learn, TensorFlow, and PyTorch.
11. integrate ML into robotic systems for tasks such as predictive maintenance, path planning, and object recognition;
12. design, train, and deploy machine learning models tailored to advanced robotics applications;
13. gain a comprehensive understanding of deep learning concepts, neural network architectures, and their applications in robotics, explain the principles of deep learning, distinguish it from traditional machine learning, and describe the structure and function of neural networks including input, hidden, and output layers with activation functions;
14. apply convolutional neural networks for vision-based robotics tasks and recurrent neural networks for sequence and time-series data, including the use of LSTM models, gain practical experience in selecting loss functions, apply optimization techniques, preventing overfitting and underfitting, and managing dataset;
15. utilize frameworks such as TensorFlow and PyTorch, and deploy deep learning models for robotic applications including object detection, motion prediction, and reinforcement learning;
16. design and implement computer vision solutions for autonomous navigation, robotic inspection, quality control, and human–robot interaction, enabling them to integrate advanced vision systems into robotics applications effectively;
17. gain a strong understanding of Fusion 360 as a CAD tool for mechanical design in robotics, navigate the workspace, manage design history, maintain file version control, proficiency in creating and editing 2D sketches, applying constraints, and using dimensioning to achieve precise design;
18. conduct static stress analysis, motion studies, material selection, and prepare designs for manufacturing through technical drawings, 3D printing, and CNC machining to design, assemble, and evaluate complete robotic mechanisms in Fusion 360;
19. gain advanced expertise in mechanical engineering principles tailored for robotics applications to design and optimize structural systems with high strength-to-weight efficiency, integrate complex chassis and linkage assemblies, and apply advanced kinematics and dynamics for precise motion control;
20. demonstrate skill in selecting and working with high-performance materials, implementing vibration, noise, thermal management strategies, and using precision fastening and additive manufacturing techniques;
21. demonstrate the ability to analyze force, torque, load, and fatigue to ensure mechanical reliability and safety, incorporating redundancy and fail-safe mechanisms for high-precision motion mechanisms; and
22. conceptualize, design, and evaluate robotic arms, mobile platforms, and structural systems to meet industrial-grade performance, durability, and safety standards with the capability of engineering mechanically optimized, reliable, and production-ready robotic systems.

CCBC Pathway & Track

Technology and Engineering Pathway: Cybersecurity Track - Pathways are designed to help you meet your academic and career goals by aligning related courses and programs.  Pathway students participate in a variety of activities that help explore career opportunities in their field of study.  You can meet with a CCBC advisor to help align — or realign — your educational plan with the Pathway that best supports you and your goals.

Program Credentials

CCBC Credential: Students will be awarded a Continuing Education Workforce Certificate and will have access to a Continuing Education academic record (transcript).

External Credential: Students will be prepared to sit for the following certification exam: Nvidia® Certified Associate Generative AI Multimodal (NCA-GENM).

Certifying Organization: Nvidia® https://www.nvidia.com/

Financial Aid and Payment Options

We offer financial aid by packaging public and private funding options to those who qualify, in select Continuing Education courses and programs. Additional opportunities for financial support include partial payment options through Nelnet Business Solutions and tuition waivers for those who qualify. Resources outside of CCBC may also be available through employer/sponsor paid tuition, the Department of Rehabilitation Services (DORS), and your local office of workforce development.

Some CE Workforce Development Certificate Programs are eligible for early high school funding through Maryland Blueprint for qualifying BCPS high school students.  Please check with your School Counseling Office to determine your eligibility for the BCPS Tuition Benefit Program. 

Program Length

Length of Training: Approximately 15 weeks

Total Program Hours: 400

Instructional Modality(ies): Online, blended remote, blended (hybrid), in-person

Program Requirements

Orientation and/or Information Session: Information sessions – Prior to Fall Term and during Spring Term

Program Requirements: 

• High School Diploma or GED
• Strong computer skills
• Strong analytical skills
• Access to the Internet to complete assignments

Application Process

Provisional Entry: Students must successfully complete the Artificial Intelligence (AI) and Machine Learning (ML) Technician Program before entry.

To apply, go to www.ccbcmd.edu/apply and complete the CCBC Continuing Education Workforce Certificate program application. An email will then be sent with program information and any additional requirements necessary to apply for the program.

Prior Learning Assessment

This program has potential options for the waiver of select courses based on:

• previous coursework or articulated coursework from an approved curriculum
• demonstrated portfolio and/or prior occupational learning

Maximum number of program hours that may be earned from prior learning: 100

Program Course Sequence

General Course Information: Students may complete the first two courses in any order.

Additional Information

Related Courses or Programs: Artificial Intelligence and Machine Learning Technician Program

Certificate of Completion: Students who successfully complete the Industrial Artificial Intelligence (AI) and Robotics Engineer program will receive a certificate of completion from JIO Robotics Academy.

Career Coach

Research your career interests, explore live job postings, take a career assessment, discover which companies in the Baltimore region are hiring, and more.  View a brief tutorial video on how to use Career Coach at https://youtu.be/C7KpznbPYfA.  Explore career and training opportunities at https://ccbcmd.emsicc.com/.

Program Contact Information

Program Coordinator: Katherine Walton | kwalton3@ccbcmd.edu | 443-840-4890 | Catonsville BESS 100L

Administrative Assistant: Sarah Faul | sfaul@ccbcmd.edu | 443-840-3677 | Catonsville BESS 100

Technical Standards

The following is a partial listing of the types of skills typically required for adequate job performance:

Physical Requirements:

A. Sufficient Strength and mobility to:

• Lift and move computer equipment.

B. Fine motor coordination sufficient to perform precise tasks such as:

• Interface with a computer system and related devices.

C. Adequate vision to:

• Work on a computer.

D. Sufficient hearing to:

• Listen to live instruction or videos including in course assignments.

Interpersonal Skills and Professionalism:

A. Have the ability to:

• Collaborate and work well with others.

B. Sufficient communication skills to:

• Effectively use oral, written, and digital skills (i.e., presentations to technical and non-technical audiences).

Intellectual Ability and Emotional Stability to:

• Engage in civil discussions and respectful to others at all times.

Environmental Requirements

• Students are required to engage in course activities during live remote class sessions and should avoid locations with distracting noise in their background. Also required to regularly attend in-person class sessions to engage in hands-on activities and labs.

Program Application Specific Questions - Program ID

Does this program meet state requirements to be considered (choose all that apply):

• High Skill
• high Wage
• In-Demand

At what point should the student have a major code applied? (choose one):

• At initial registration/first class

ONET Code: 17-2199.08

Wage Estimates

• Average Annual Wages in MD: $135,990
• Average Hourly Wages in MD: $65.40
• Typical Starting Hourly Wage Upon Completion/Credential (estimate): $40
• Estimated Median Salary upon completion/credential: $83,200

Potential Audiences, Marketing and Promotional Strategies: NA

Use of External Vendor?

• Yes. JIO Robotics Academy

Is this Credential stackable or does it articulate to a credit program, either internally or externally? (Identify relationship): NA