NobleProg delivers tailored AI for Robotics training courses across the diverse landscape of Florida, catering to professionals in bustling metropolitan hubs and remote communities alike. Our experts provide flexible learning solutions designed to meet the unique workforce development needs of this dynamic state. Whether in Miami, Orlando, or Tampa, organizations can enhance their teams' capabilities with our comprehensive AI for Robotics programs.
Artificial Intelligence for Robotics defines the intersection of cognitive processing and mechanical movement — where computational models process information, sensor arrays gather environmental data, and autonomous systems execute targeted actions. This field represents the critical domain where raw information translates into physical capability, enabling the development of advanced automated solutions, manufacturing robotics, and sophisticated operational machinery.
Through these instructor-led live training programs, participants examine how artificial intelligence integrates with robotic platforms to create adaptive and continuously improving systems. Via practical application exercises, attendees engage with perception algorithms, trajectory planning, reinforcement learning methodologies, and AI-centric control frameworks that enhance machine responsiveness and precision.
Remote participants access a simulated laboratory environment that replicates the tempo of professional research facilities — progressing methodically through real-time demonstrations and collaborative coding activities via an interactive remote desktop. Each module functions as a collaborative analysis of logic and dynamics, rather than a passive presentation.
For organizations seeking to develop and validate systems collaboratively, on-site live training in Florida — conducted at client facilities or within NobleProg corporate learning centers — shifts the educational focus toward applied experimentation. In these practical settings, theoretical concepts are integrated with physical hardware and coding frameworks.
Also referred to as Robotics AI or Intelligent Robotics, our curriculum supports professionals in integrating software engineering with mechanical systems — developing platforms that sense environments, make determinations, and execute actions with growing autonomy and accuracy for government and enterprise applications.
NobleProg — Your Local Training Provider
Jacksonville, FL – Deerwood Park
10151 Deerwood Park Blvd 200, Suite 250, Jacksonville, United States, 32256
The venue is nestled in the Deerwood Park campus at 10151 Deerwood Park Boulevard, just off J. Turner Butler Boulevard (JTB) and I‑295, with free on-site parking and adjacent lots. From Jacksonville International Airport (JAX), approximately 18 miles north, a taxi or rideshare takes about 25 minutes via I‑95 South and JTB West. Public transit is available via Jacksonville’s JTA bus routes stopping within walking distance, making the landscaped campus—complete with fountains, cafes, and scenic walkways—easily accessible for attendees without a car.
Miami, FL – Regus at Waterford at Blue Lagoon
6303 Blue Lagoon Drive, Suite 400, Miami, United States, 33126
The venue is set within the Waterford business park at 6303 Blue Lagoon Drive, just minutes from Miami International Airport. It’s accessible by car via I‑95, Florida Turnpike, 826, or Dolphin Expressway, with abundant covered and surface parking on-site. From Miami International Airport (MIA), a taxi or rideshare takes approximately 10 minutes via the Dolphin Expressway. Public transit options include TheBus routes and nearby Tri-Rail stations, with the property a short walk from bus stops—making it convenient even for attendees without a car.
Tampa, FL – Regus at Wells Fargo Center
100 S. Ashley Drive, Suite 600, Tampa, United States, 33602
The venue is located in the 22-story Wells Fargo Center in downtown Tampa, easily accessible by car via I‑275, I‑4, I‑75, or the Selmon Expressway, with covered garage parking (610+ spaces) directly connected to the building. From Tampa International Airport (TPA), a taxi or rideshare takes about 15 minutes via I‑275 East and Ashley Drive. Public transit is excellent with the Downtown Tampa Station (NFTA Metro Rail) just a block away and several bus routes running along Ashley and Brorein Streets, making it ideal for attendees arriving without cars.
FL, Orlando – GAI Building
618 E. South Street Suite 500, Orlando, United States, 32801
The venue is located in the GAI Building with the CNS Healthcare logo at the front.
FL, Jacksonville - Bank of America Tower
50 N. Laura Street Suite 2500, Jacksonville, United States, 32202
The office is located in a premier office tower in Downtown Jacksonville on the 42nd floor. This Class A LEED Certified building is situated in the Northbank Office Market Preeminent location that provides commanding views. Downtown Trolley and Bus stops are located just across the street on Forsyth with easy access to I-95 leading to I-10 and I-295. Convenient to Jacksonville International Airport, the building is also just minutes to Everbank Field, Jacksonville Landing, Times Union Performing Arts Center, Jacksonville Veterans Memorial Arena and Jacksonville Public Library. Spectacular views of the St John's River in Jacksonville, Florida are one of many features that make the Bank of America Tower office space stand out. The office space occupies a blue granite tower in the heart of the city's central business district. The iconic tower is one of the best-known business premises in the southeastern United States and includes a statement lobby and class-A workspace. Businesses of all kinds appreciate Jacksonville's location at the crossroads of three major railroads and three interstates, and its international airport.
FL, Tallahassee – Alliance Center
113 South Monroe Street 1st Floor, Tallahassee, united states, 32301
The venue is located in the Alliance Center across the street from FUBA and the Florida Optometric Association.
FL, West Palm Beach - Philips Point
777 South Flagler Drive, West Palm Beach, United States, 33401
The venue is located in the Philips Point building just off the Royal Park Bridge.
FL, Aventura - Corporate Center
20801 Biscayne Blvd., Miami, united states, 33180
The venue is located in the Grove Bank & Trust building just off Biscayne Blvd.
FL, Fort Lauderdale - Corporate Center
Corporate Center, 110 East Broward Blvd., Fort Lauderdale, United States, 33301
The venue is located in the Corporate Center across the street from the Uniform Advantage Corporate Office and just next door to Colliers International.
Miami Beach, FL – Regus at Meridian Center
1688 Meridian Avenue, Suites 600/700, Miami Beach, United States, 33139
The venue is located on the corner of Meridian Avenue and 17th Street in Miami Beach’s vibrant City Center district, accessible by car via I‑195 and the MacArthur Causeway with underground and street parking nearby. From Miami International Airport (MIA), taxis or rideshares typically take 15–20 minutes via I‑195 East and Biscayne Boulevard. Public transit is seamless: several Metrobus routes serve Meridian Avenue, and the nearby 17th Street trolley stop makes it easy to reach without a car. The central location places the venue steps from the Miami Beach Convention Center, Lincoln Road Mall, restaurants, galleries, and retail.
Tampa, FL - Regus - One Urban Centre at Westshore
4830 W Kennedy Blvd #600, Tampa, United States, 33609
The venue is located in the Westshore business district at 4830 West Kennedy Boulevard, seamlessly accessible by car via I‑275 or I‑75 with secure underground and surface parking on-site. From Tampa International Airport (TPA), take Memorial Highway to I‑275 South and exit at West Kennedy Boulevard—taxi or rideshare typically takes about 15–20 minutes. Public transit users can reach the venue via HART bus routes (such as Route 2 or 32) stopping nearby, followed by a short walk into the building lobby.
Practical Rapid Prototyping for Robotics with ROS 2 & Docker is an experiential instructional program designed to equip developers with the competencies necessary to construct, validate, and operationalize robotic solutions effectively. Attendees will acquire skills in containerizing robotics workspaces, integrating ROS 2 components, and engineering modular robotic architectures utilizing Docker to ensure reproducibility and scalability. The curriculum prioritizes agile methodologies, version control protocols, and collaborative frameworks appropriate for innovation teams engaged in early-stage development.
This instructor-led live training, available via online or onsite delivery modes, targets beginner to intermediate professionals seeking to optimize robotics development workflows through the integration of ROS 2 and Docker technologies. The program is tailored for public sector entities requiring specialized technical capabilities for government operations.
Upon completion of this training, participants will demonstrate proficiency in:
Configuring ROS 2 development environments within Docker containers.
Constructing and validating robotic prototypes using modular and reproducible configurations.
Utilizing simulation tools to verify system performance prior to physical deployment.
Facilitating effective collaboration through containerized robotics project management.
Implementing continuous integration and deployment principles within robotic engineering pipelines.
Course Format
Interactive lectures complemented by technical demonstrations.
Practical exercises involving ROS 2 and Docker environments.
Agencies seeking tailored instruction for this course are invited to contact the training provider to arrange customized scheduling and content delivery.
The curriculum titled Human-Robot Interaction (HRI): Voice, Gesture & Collaborative Control provides practical instruction on the architecture and deployment of intuitive interfaces for human–robot communication. This educational program synthesizes theoretical frameworks, design standards, and programming application to establish responsive interaction systems utilizing speech recognition, gesture detection, and shared control methodologies. Attendees will acquire proficiency in integrating perception modules, constructing multimodal input architectures, and engineering robotic systems that ensure secure collaboration with personnel. Designed for federal and state agencies seeking advanced capabilities for government
This instructor-led, live training (available online or onsite) targets beginner to intermediate-level practitioners who aim to design and implement human–robot interaction systems to improve usability, safety, and operational efficiency.
Upon completion of this training, participants will be able to:
Comprehend the foundational concepts and design principles governing human–robot interaction.
Engineer voice-based control and response mechanisms for robotic platforms.
Industrial Robotics Automation: ROS-PLC Integration & Digital Twins is an experiential program designed to connect industrial automation practices with contemporary robotic frameworks. Participants will acquire the expertise to synchronize ROS-based robotic systems with PLCs and utilize digital twin environments for simulating, monitoring, and optimizing production workflows. This training prioritizes interoperability, real-time control capabilities, and predictive analysis through the use of digital replicas of physical infrastructure.
Offered as an instructor-led, live session via online or onsite delivery, this program targets intermediate-level professionals seeking to develop practical competencies in linking ROS-controlled robots with PLC environments and deploying digital twins to enhance manufacturing and automation efficiency. Designed specifically for government agencies and public sector entities, the curriculum ensures alignment with federal operational standards.
Upon completion of this training, participants will be able to:
Analyze communication protocols facilitating interaction between ROS and PLC systems.
Deploy real-time data exchange mechanisms between robotic units and industrial controllers.
Construct digital twins for purposes of monitoring, testing, and process simulation.
Integrate sensors, actuators, and robotic manipulators within established industrial workflows.
Design and validate industrial automation systems utilizing hybrid simulation environments.
Format of the Course
Interactive lectures and architectural walkthroughs.
Practical exercises focused on integrating ROS and PLC systems.
Implementation of simulation and digital twin projects.
Course Customization Options
To request customized training for this course, please contact us to arrange.
Deep Learning for Robotic Manipulation and Grasping is an advanced curriculum that integrates robotic control mechanisms with contemporary machine learning methodologies. Participants will examine how deep learning algorithms improve perception, motion planning, and dexterous grasping capabilities within robotic systems. Through a combination of theoretical instruction, simulation, and practical coding assignments, the course facilitates the transition from perception-based control to end-to-end policy learning for manipulation tasks.
This instructor-led live training, available in online or onsite formats, targets advanced professionals seeking to apply deep learning techniques to achieve intelligent, adaptable, and precise robotic manipulation. The content is designed specifically for government applications, ensuring alignment with public sector technology standards and for government operational needs.
Upon completion of this training, participants will be capable of:
Designing perception models for object recognition and pose estimation.
Training neural networks to facilitate grasp detection and motion planning.
Integrating deep learning modules with robotic controllers using ROS 2.
Simulating and evaluating grasping and manipulation strategies within virtual environments.
Deploying and optimizing learned models on physical or simulated robotic arms.
Course Format
Expert-led lectures and algorithmic deep dives.
Hands-on coding and simulation exercises.
Project-based implementation and testing.
Course Customization Options
To request a customized training for this course, please contact us to arrange.
The Multi-Robot Systems and Swarm Intelligence curriculum provides advanced instruction on the architecture, coordination, and control of robotic collectives modeled after biological swarm behaviors. Attendees will acquire skills in modeling agent interactions, executing distributed decision-making processes, and optimizing collaborative performance across multiple nodes. This program integrates theoretical frameworks with practical simulation exercises to prepare personnel for operational deployments within logistics, national defense, search and rescue, and autonomous exploration sectors.
This instructor-led, live training session, available in online or onsite formats, is designed for senior professionals seeking to develop, simulate, and deploy multi-robot and swarm-based systems utilizing open-source frameworks and algorithms. The content is tailored for government applications and public sector needs.
Upon completion of this training, participants will be able to:
Analyze the principles governing swarm intelligence and cooperative robotics dynamics.
Develop communication protocols and coordination strategies for multi-robot networks.
Execute distributed decision-making mechanisms and consensus algorithms.
Simulate collective behaviors, including formation control, flocking dynamics, and area coverage.
Apply swarm-based methodologies to real-world operational scenarios and optimization challenges.
Format of the Course
Advanced lectures featuring algorithmic analysis.
Practical coding exercises and simulation using ROS 2 and Gazebo environments.
TinyML constitutes a methodology for executing machine learning algorithms on resource-constrained microcontrollers and embedded systems utilized within robotic and autonomous applications.
This instructor-facilitated live training, available via online or onsite delivery, targets advanced professionals seeking to embed TinyML-driven perception and decision-making functions into autonomous robots, unmanned aerial vehicles, and intelligent control architectures tailored for government operations.
Upon successful completion of this curriculum, participants will demonstrate the ability to:
Engineer optimized TinyML models specifically for robotic applications.
Execute on-device perception pipelines to support real-time autonomous functions.
Incorporate TinyML capabilities into established robotic control frameworks.
Deploy and validate lightweight artificial intelligence models on embedded hardware.
Course Delivery Format
Technical instruction integrated with interactive dialogue.
Practical laboratory sessions centered on embedded robotics tasks.
Safe & Explainable Robotics provides a rigorous curriculum centered on the safety protocols, verification processes, and ethical governance frameworks essential for robotic systems. This program integrates theoretical foundations with practical application by examining safety case methodologies, hazard analysis techniques, and explainable AI strategies that enhance transparency and trustworthiness in robotic decision-making. Participants will acquire the skills necessary to ensure regulatory compliance, validate system behaviors, and document safety assurance in accordance with international standards specifically for government applications.
This instructor-led training, available via online or onsite delivery, targets intermediate-level professionals seeking to implement verification, validation, and explainability principles to guarantee the secure and ethical deployment of robotic technologies.
Upon completion of this program, participants will be capable of:
Developing and documenting comprehensive safety cases for robotic and autonomous systems.
Implementing verification and validation methodologies within simulation environments.
Analyzing explainable AI frameworks to inform robotics decision-making processes.
Integrating safety and ethical principles into system design and operational workflows.
Communicating safety and transparency requirements effectively to relevant stakeholders.
Course Structure
Interactive lectures and facilitated discussions.
Practical exercises involving simulation and safety analysis.
Review of case studies derived from real-world robotics implementations.
Customization Availability
To request customized training aligned with specific organizational requirements, please contact the program administration to make arrangements.
Edge AI facilitates the execution of artificial intelligence models directly on embedded or resource-constrained hardware, thereby decreasing latency and energy usage while enhancing operational autonomy and data privacy within robotic systems.
This instructor-led training program, available in online or onsite formats, is designed for intermediate-level embedded developers and robotics engineers seeking to apply machine learning inference and optimization strategies on robotic hardware through TinyML and edge AI frameworks. This specialized instruction is intended for government
Upon completion of this training, participants will be equipped to:
Comprehend the core principles of TinyML and edge AI as applied to robotics.
Transform and deploy artificial intelligence models for on-device inference.
Enhance model performance regarding speed, memory footprint, and energy efficiency.
Integrate edge AI solutions into robotic control systems.
Assess system accuracy and performance in operational environments.
Instructional Format
Interactive lectures and technical discussions.
Practical application of TinyML and edge AI toolchains.
Applied exercises on embedded and robotic hardware platforms.
Customization Opportunities
To arrange customized training for this course, please contact the program administrators.
This guided, live instructional program delivered via Florida (remote or on-site) is designed for mid-level professionals seeking to examine the function of collaborative robotics and human-centered artificial intelligence within contemporary work environments.
Upon completion of this course, participants will be capable of:
Grasping the foundational concepts of Human-Centric Physical AI and its practical implementations.
Evaluating how collaborative robots contribute to improved workplace efficiency.
Recognizing and mitigating obstacles associated with human-machine interfaces.
Developing operational workflows that enhance cooperation between personnel and automated systems.
Fostering an organizational environment characterized by innovation and responsiveness for government
Reinforcement learning constitutes a computational approach in which autonomous agents acquire optimal decision-making strategies through continuous interaction with their operational environment. Within the robotics sector, this methodology empowers systems to establish adaptive control mechanisms and analytical capabilities by leveraging empirical data and performance feedback.
This guided instruction session, available via remote or on-premises delivery, targets senior machine learning professionals, robotics scientists, and software engineers committed to engineering, executing, and deploying reinforcement learning frameworks for robotic solutions designed specifically for government
Upon completion of this instructional module, participants will possess the capability to:
Articulate the foundational concepts and mathematical theories underpinning reinforcement learning.
Code reinforcement learning architectures, including Q-learning, DDPG, and PPO methodologies.
Facilitate integration between reinforcement learning models and robotic simulation platforms utilizing OpenAI Gym and ROS 2.
Enable robotic systems to execute complex missions autonomously through iterative trial-and-error processes.
Enhance computational efficiency by applying deep learning libraries such as PyTorch.
Instructional Format
Participatory lectures and technical discussions.
Practical application of concepts using Python, PyTorch, and OpenAI Gym.
Applied exercises within simulated or tangible robotic testbeds.
Customization Availability
Organizations seeking tailored training curricula should contact the administration to coordinate arrangements.
OpenCV serves as an open-source computer vision library facilitating real-time image processing, whereas deep learning frameworks like TensorFlow supply the necessary tools for intelligent perception and decision-making capabilities within robotic systems.
This instructor-led, live training course, available online or onsite, targets robotics engineers, computer vision specialists, and machine learning professionals at the intermediate level who seek to apply computer vision and deep learning methodologies to enhance robotic perception and autonomy. This curriculum is designed for government agencies seeking advanced technical capabilities.
Upon completion of this training, participants will be able to:
This instructor-led, live training in Florida (delivered online or onsite) is designed for advanced robotics engineers and AI researchers who intend to leverage Multimodal AI to integrate diverse sensory inputs, thereby developing more autonomous and efficient robotic systems capable of visual, auditory, and tactile interaction. This program provides essential resources for government agencies seeking to enhance their technological capabilities for government applications.
Upon completion of this training, participants will be equipped to:
Deploy multimodal sensing architectures within robotic platforms.
Engineer artificial intelligence algorithms for sensor fusion and strategic decision-making.
Design robotic systems capable of executing complex operations in dynamic environments.
Resolve challenges related to real-time data processing and actuation mechanisms.
Smart Robotics involves the incorporation of artificial intelligence into robotic frameworks to enhance perceptual capabilities, decision-making processes, and autonomous operational control.
This instructor-led training program, available in online or onsite formats, is designed for advanced robotics engineers, systems integrators, and automation directors seeking to deploy AI-driven perception, planning, and control mechanisms within smart manufacturing settings tailored for government operations.
Upon completion of this curriculum, participants will be able to:
Analyze and implement artificial intelligence methodologies for robotic perception and sensor data fusion.
Engineer motion planning algorithms suitable for both collaborative and industrial robotic applications.
Implement learning-based control strategies to facilitate real-time decision-making capabilities.
Integrate intelligent robotic systems into established smart factory operational workflows.
Course Structure and Delivery
Facilitated lectures accompanied by structured discussion.
Comprehensive exercises and practical application sessions.
Practical implementation within a live laboratory environment.
Training Customization Availability
For inquiries regarding customized training arrangements for this program, please contact the provider directly to coordinate schedules and requirements.
ROS 2 (Robot Operating System 2) serves as an open-source framework engineered to facilitate the creation of complex and scalable robotic systems. These capabilities are specifically designed to meet the rigorous requirements of government applications for government.
This instructor-led training, available through online or onsite delivery methods, targets robotics engineers and developers at the intermediate proficiency level who seek to implement autonomous navigation and Simultaneous Localization and Mapping (SLAM) utilizing ROS 2.
Upon completion of this instructional program, participants will be equipped to:
Establish and configure ROS 2 infrastructure for autonomous navigation systems.
Deploy SLAM algorithms to enable precise mapping and localization functions.
Integrate sensor inputs, including LiDAR and visual cameras, with the ROS 2 environment.
Execute simulation and testing protocols for autonomous navigation within Gazebo.
This instructor-led, live training in Florida (online or onsite) is aimed at intermediate-level participants who wish to enhance their skills in designing, programming, and deploying intelligent robotic systems for automation and beyond.
By the end of this training, participants will be able to:
Understand the principles of Physical AI and its applications in robotics and automation.
Design and program intelligent robotic systems for dynamic environments.
Implement AI models for autonomous decision-making in robots.
Leverage simulation tools for robotic testing and optimization.
Address challenges such as sensor fusion, real-time processing, and energy efficiency.
The integration of Artificial Intelligence (AI) with robotics leverages machine learning algorithms, control theory, and sensor data fusion to develop autonomous systems capable of environmental perception, cognitive processing, and independent action. By utilizing established frameworks such as ROS 2, TensorFlow, and OpenCV, technical personnel can engineer robotic solutions that effectively navigate, plan trajectories, and engage with complex operational settings.
This instructor-led program, available in online or on-site formats, is designed for intermediate-level engineers seeking to develop, train, and deploy AI-enabled robotic systems using contemporary open-source technologies. The curriculum aligns with for government modernization efforts to enhance technical capacity in automated systems.
Upon completion of this training, participants will be equipped to:
Utilize Python and ROS 2 to construct and simulate robotic behaviors.
Implement Kalman and Particle Filters for precise localization and tracking.
Apply computer vision methodologies via OpenCV for perceptual tasks and object detection.
Employ TensorFlow for motion prediction and learning-based control mechanisms.
Integrate SLAM (Simultaneous Localization and Mapping) protocols to enable autonomous navigation.
Develop reinforcement learning models to enhance robotic decision-making processes.
Course Structure
Interactive lectures and technical discussions.
Practical implementation exercises using ROS 2 and Python.
Applied work within simulated and physical robotic environments.
Customization Opportunities
To arrange customized training aligned with specific agency requirements, please contact the administration team directly.
A bot, or chatbot, functions as an automated digital assistant designed to streamline user interactions across diverse messaging channels. This technology enables efficient task completion without requiring direct human intervention.
This instructor-led live training provides participants with a comprehensive foundation for building bots. Attendees will navigate the development lifecycle by constructing sample chatbots through the application of specialized frameworks and development tools.
Upon completing this course, participants will be able to:
Analyze the distinct applications and use cases for automated bots
Navigate the end-to-end bot development process
Evaluate various tools and platforms utilized in bot construction
Develop a functional sample chatbot for Facebook Messenger
Create a sample chatbot utilizing the Microsoft Bot Framework
Audience
Software developers seeking to build custom bots for government
Format of the course
A structured blend of lectures, interactive discussions, and intensive hands-on exercises
This instructor-led, live training in Florida (online or onsite) is designed for engineers seeking to understand the application of artificial intelligence within mechatronic systems.
Upon completion of this session, participants will be equipped to:
Acquire a comprehensive understanding of artificial intelligence, machine learning, and computational intelligence frameworks.
Comprehend the principles of neural networks and various learning methodologies.
Select appropriate artificial intelligence strategies to address complex practical challenges.
Deploy AI solutions within mechatronic engineering workflows for government and public sector applications.
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Testimonials (2)
Supply of the materials (virtual machine) to get straight into the excersises, and the explanation of the Ros2 core. Why things work a certain way.
Arjan Bakema
Course - Autonomous Navigation & SLAM with ROS 2
its knowledge and utilization of AI for Robotics in the Future.
Ryle - PHILIPPINE MILITARY ACADEMY
Course - Artificial Intelligence (AI) for Robotics
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