This digital credential certifies that the recipient successfully completed the learning components and has met all of the requirements of the Six Sigma Green Belt certification program offered by Arizona State University. The recipient has the ability to use the Define, Measure, Analyze, Improve and Control (DMAIC) methodology; a customer-focused, fact and data-driven approach that guides continuous improvement and operational excellence. The holder of this digital credential is trained on a series of statistical and standard improvement tools to develop solutions to existing problems, processes, services, and products. In addition, a certified Six Sigma Green Belt has successfully completed an implementation project reviewed and supervised by a Master Black Belt. A Six Sigma Green Belt can improve processes within their specific work area and serve as a part-time member of a team contributing to a larger scale Black Belt or Master Black Belt project. A Six Sigma Green Belt is the stepping stone to a Black Belt certification.
Define Measure Analyze Improve And Control (DMAIC)
A participant needs to review and understand the associated Six Sigma Green Belt curriculum, in addition to successfully passing the topic quizzes and executing an applied project to be reviewed and approved by a Master Black Belt and program facilitator.
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This digital credential certifies that the recipient successfully completed the learning components and has met all of the requirements of the Lean Six Sigma Yellow Belt certification program offered by Arizona State University. The holder of this digital credential has the ability to use process maps to model relationships and optimize process flows; apply quality tools to understand processes and make data-driven decisions; use Lean concepts to remove waste from a process; utilize root cause analysis to identify the source of faults or problems; apply basic control methods to monitor stability and process performance. A Lean Six Sigma Yellow Belt, is skilled at the foundational concepts of Lean Six Sigma and equipped with tools to make improvements to the processes on which they work. These practitioners are often responsible for identifying and defining challenges to determine the cause, and for developing solutions to close performance gaps, and implement solutions. A Lean Six Sigma Yellow Belt is the stepping stone to a Lean Six Sigma Green Belt certification.
A participant needs to review and understand the associated Lean Six Sigma Yellow Belt lectures and curriculum, completing the active learning activities in addition to passing completion of knowledge checks and a final exam with a score of 70% or higher.
This digital credential certifies that the recipient successfully completed the learning components and has met all of the requirements of the Lean Six Sigma Green Belt certification program offered by Arizona State University. The recipient has the ability to use the Define, Measure, Analyze, Improve and Control (DMAIC) methodology; a customer-focused, fact and data-driven approach that guides continuous improvement and operational excellence. The holder of this digital credential is trained on a series of statistical and standard improvement tools to develop solutions to existing problems, processes, services and products across multiple industries and domains. A Lean Six Sigma Green Belt is a trained continuous improvement professional taught to measure process factors and provide complete process analyses to implement sound improvement solutions. A Lean Six Sigma Green Belt is the stepping stone to a Black Belt certification.
To earn this badge, the learner demonstrated the ability to define process problems within a real-world context, identify opportunities for improvement, and apply the DMAIC framework to guide their approach. They showed skill in mapping and analyzing workflows to uncover sources of inefficiency and variation, using data to diagnose root causes and inform decision-making. The learner applied relevant Lean and Six Sigma tools to develop, test, and implement solutions, and demonstrated their ability to sustain improvements through appropriate control strategies. Throughout the experience, they communicated findings and recommendations to stakeholders, showing the capacity to apply structured problem-solving methods in a professional environment.
This digital credential certifies that the recipient successfully completed the learning components and has met all of the requirements of the Six Sigma Black Belt certification program offered by Arizona State University. The recipient has a deep understanding of the Six Sigma concepts and the “process improvement triad”. The holder of this digital credential can apply the DMAIC methodology, design for six sigma and lean product development concepts to product/process design projects. In addition, a certified Six Sigma Black Belt uses appropriate analytical, statistical, and lean methods, and a fundamental understanding on how to plan, design and conduct experiments efficiently and effectively. Six Sigma Black Belts analyze the resulting data to obtain objective conclusions. A Six Sigma Black Belt is a full-time, highly trained continuous improvement professional often responsible for leading problem-solving projects, conducting Six Sigma and other continuous improvement training, and coaching project teams. A Six Sigma Black Belt is the stepping stone to a Master Black Belt certification.
A participant needs to review and understand the associated Six Sigma Black Belt lectures and curriculum, in addition to passing completion of the topic quizzes and exams with a score of 70% or higher, and executing an applied project to be reviewed and critiqued by a Master Black Belt.
This digital credential certifies that the recipient has completed substantial service learning experience (at least 80 hours), to enhance their education and provide service to benefit the community. Holders of this micro-credential possess the social consciousness and motivation to use their technical expertise to help solve societal problems and have achieved the GCSP Social Consciousness competency. The Fulton Grand Challenges Scholars Program (GCSP), is a co-curricular program that combines innovative curriculum and cutting-edge research experiences into an intellectual fusion that spans academic disciplines and focuses on addressing global challenges. GCSP students engage in research, interdisciplinary, entrepreneurial, global, and service learning opportunities, and are uniquely prepared to collaborate and succeed in a transdisciplinary and global environment. Students who complete the program receive the distinction of Grand Challenges Scholar, recognized by both ASU and the National Academy of Engineering (NAE).
To earn this credential, Fulton Grand Challenges Scholars must demonstrate sustained involvement in service learning project(s) or experience(s) related to their Grand Challenges theme area and/or engineering for at least 80 hours. This competency may be fulfilled through participation in Engineering Projects in Community Service (EPICS) courses for two semesters. Other service learning experiences eligible for approval may include: - Engineers Without Borders projects - Engineering outreach projects - Providing service as a leader through Fulton Ambassadors or mentorship. Students will also include their experiences in their GCSP digital portfolio.
This digital credential certifies that the recipient successfully completed two semesters of approved mentored research or creative project experience(s) related to their Grand Challenges theme area. The holder of this micro-credential has demonstrated the application of technical and research skills to a real-world problem to gain more in-depth knowledge of work in their chosen focus area (e.g. health, security, sustainability, joy of living). Holders of this credential have achieved the GCSP Talent competency. The Fulton Grand Challenges Scholars Program (GCSP) is a co-curricular program that combines innovative curriculum and cutting-edge research experiences into an intellectual fusion that spans academic disciplines and focuses on addressing global challenges. GCSP students engage in research, interdisciplinary, entrepreneurial, global, and service learning opportunities, and are uniquely prepared to collaborate and succeed in a transdisciplinary and global environment. Students who complete the program receive the distinction of Grand Challenges Scholar, recognized by both ASU and the National Academy of Engineering (NAE).
To earn this credential, Fulton Grand Challenges Scholars will complete two semesters of mentored research or creative project experience related to their chosen Grand Challenges theme in order to gain hands-on experience and more in-depth knowledge of work in their chosen focus area. This may include participation in one or more of the following: - The GCSP Research Stipend program - The Fulton Undergraduate Research Initiative (FURI) program - Research Experience for Undergraduates - Barrett, the Honors College research and thesis - Independent research/creative project with faculty - Senior Capstone Design project - Other research programs Students will also include their experiences in their GCSP digital portfolio.
This digital credential certifies that the recipient successfully completed coursework and/or experiences in fields outside of engineering that complements their technical engineering work in order to prepare them to work at the overlap with public policy, business, law, ethics, human behavior, risk, the arts, and medicine. The holder of this micro-credential is familiar with the grand challenges that face human societies in the 21st century and applies an interdisciplinary perspective and approach when addressing those challenges in order to develop effective solution(s). Holders of this credential have achieved the GCSP Multidisciplinary competency. The Fulton Grand Challenges Scholars Program (GCSP) is a co-curricular program that combines innovative curriculum and cutting-edge research experiences into an intellectual fusion that spans academic disciplines and focuses on addressing global challenges. GCSP students engage in research, interdisciplinary, entrepreneurial, global, and service learning opportunities, and are uniquely prepared to collaborate and succeed in a transdisciplinary and global environment. Students who complete the program receive the distinction of Grand Challenges Scholar, recognized by both ASU and the National Academy of Engineering (NAE).
To earn this credential, Fulton Grand Challenges Scholars develop an interdisciplinary systems perspective of engineering challenges and solutions through completing the FSE150: Perspectives on Grand Challenges for Engineering course and an additional course or experience exploring fields and topics outside of engineering. Students will also include their experiences in their GCSP digital portfolio.
This digital credential certifies that the recipient has completed experiences and/or courses to develop an understanding of different cultures that is necessary to ensure cultural acceptance of proposed engineering solutions. The holder of this micro-credential possesses the multicultural awareness and global perspective necessary to address the global Grand Challenges and to become leaders of innovation in a global economy. Holders of this credential have achieved the GCSP Multicultural competency. The Fulton Grand Challenges Scholars Program (GCSP) is a co-curricular program that combines innovative curriculum and cutting-edge research experiences into an intellectual fusion that spans academic disciplines and focuses on addressing global challenges. GCSP students engage in research, interdisciplinary, entrepreneurial, global, and service learning opportunities, and are uniquely prepared to collaborate and succeed in a transdisciplinary and global environment. Students who complete the program receive the distinction of Grand Challenges Scholar, recognized by both ASU and the National Academy of Engineering (NAE).
To earn this credential, Fulton Grand Challenges Scholars complete two multicultural courses OR experiences. An approved multicultural experience may include a study abroad program, a global internship, or a service learning project with a multicultural focus (e.g. through Engineers Without Borders (EWB) or Engineering Projects in Community Service (EPICS)). Students will also include their experiences in their GCSP digital portfolio.
This digital credential certifies that the recipient has completed an entrepreneurship course or experience to develop an understanding of the necessity of a viable business model for solution implementation. The holder of this micro-credential has experienced the practical issues typically encountered in starting up and operating a technology venture, can translate invention to innovation, and understands how to develop market ventures that scale to global solutions in the public interest. . Holders of this credential have achieved the GCSP Viable Business/Entrepreneurship competency. The Fulton Grand Challenges Scholars Program (GCSP) is a co-curricular program that combines innovative curriculum and cutting-edge research experiences into an intellectual fusion that spans academic disciplines and focuses on addressing global challenges. GCSP students engage in research, interdisciplinary, entrepreneurial, global, and service learning opportunities, and are uniquely prepared to collaborate and succeed in a transdisciplinary and global environment. Students who complete the program receive the distinction of Grand Challenges Scholar, recognized by both ASU and the National Academy of Engineering (NAE).
To earn this credential, Fulton Grand Challenges Scholars will apply an entrepreneurial mindset to develop a viable business idea by completing the FSE 301: Entrepreneurship & Value Creation course or participating in a substantial entrepreneurship experience, such as ASU Venture Devils. Students will also include their experiences in their GCSP digital portfolio.
The Fulton Grand Challenges Scholars Program (GCSP), endorsed by the National Academy of Engineering (NAE), is a co-curricular program that combines innovative curriculum and cutting-edge research experiences into an intellectual fusion that spans academic disciplines and focuses on addressing global challenges. GCSP students engage in research, interdisciplinary, entrepreneurial, global, and service learning opportunities, and are uniquely prepared to collaborate and succeed in a transdisciplinary and global environment. Holders of this credential have successfully demonstrated the five competencies of the Grand Challenges Scholars Program: Talent, Multidisciplinary, Viable Business/Entrepreneurship, Multicultural, and Social Consciousness. Fulton Engineering students who are holders of this credential have achieved the distinction of Grand Challenges Scholar, recognized by both ASU and the National Academy of Engineering (NAE).
To earn this credential, Fulton Grand Challenges Scholars will have successfully achieved the five competencies of the NAE Grand Challenges Scholars Program: - Talent - Multidisciplinary - Viable Business/Entrepreneurship - Multicultural - Social Consciousness. Each of these competencies is certified by their individual credential. In addition, scholars must create a digital GCSP Portfolio to document and reflect on their experiences in the program. The digital portfolio will contain a representation of the work that the program participant has completed, and will demonstrate how their experiences are interconnected and aligned with their chosen Grand Challenges theme.
This digital credential certifies that the recipient successfully created a digital GCSP Portfolio that includes descriptions, artifacts, and reflections on their experiences in the program. The digital portfolio contains a representation of the work that the program participant has completed for each of the five GCSP Competencies, and demonstrates how their experiences are interconnected and aligned with their chosen Grand Challenges theme. The Fulton Grand Challenges Scholars Program (GCSP) is a co-curricular program that combines innovative curriculum and cutting-edge research experiences into an intellectual fusion that spans academic disciplines and focuses on addressing global challenges. GCSP students engage in research, interdisciplinary, entrepreneurial, global, and service learning opportunities, and are uniquely prepared to collaborate and succeed in a transdisciplinary and global environment. Students who complete the program receive the distinction of Grand Challenges Scholar, recognized by both ASU and the National Academy of Engineering (NAE).
To earn this credential, Fulton Grand Challenges Scholars will submit their final GCSP digital portfolio which includes summaries and reflections on their experiences in GCSP.
Software Engineering Professional Certification
This digital credential certifies that the recipient successfully completed the required Computer Science graduate-level courses in the following areas: Software Verification, Validation, and Testing, Advanced Software Analysis and Design, Engineering Blockchain Applications, and Mobile Computing. The recipient also successfully completed several time-intensive projects modeled from real-world problems to test their comprehension and application of concepts and tools collected from the courses. Through a combination of lectures, live sessions, peer collaboration and applied projects, the recipient demonstrates understanding of how to apply software development concepts to blockchain, testing software to validate sustainability of smart mobile applications, predict software reliability using operational profiles, and practice software architecture and design principles.
A participant needs to complete three Computer Science graduate-level courses (9 graduate credit hours) in software verification, validation, and testing, advanced software analysis and design, engineering blockchain applications, and mobile computing. In addition, participants must complete multiple hands-on applied projects demonstrating their knowledge and comprehension of the course material.
Cybersecurity Professional Certification
This digital credential certifies that the recipient successfully completed the required Computer Science graduate-level courses in the following areas: Information Assurance and Security, Applied Cryptography, Software Security, Advanced Computer Network Security, Distributor & Multiprocessor OS, and Accelerated Applied Security. The recipient also successfully completed a variety of time-intensive projects modeled from real-world problems to test their comprehension and application of concepts and tools collected from the courses. Through a combination of lectures, live sessions, peer collaboration and applied projects, the recipient understands the vast field of cybersecurity through the lens of computer systems and algorithms. The recipient has a deeper understanding of how to protect and defend information by ensuring their availability, integrity, authentication, confidentiality, and non-repudiation through protection, detection, and reaction practices.
A participant needs to complete three Computer Science graduate-level courses (9 graduate credit hours) in information assurance and security, applied cryptography, software security, advanced computer network security, distributor and multiprocessor OS, and accelerated applied security. In addition, participants must complete several hands-on applied projects demonstrating their knowledge and comprehension of the course material.
This digital credential certifies that the recipient successfully completed the required Computer Science graduate-level courses in the following areas: Data Processing at Scale, Data Mining, Statistical Machine Learning, and Data Visualization The recipient also successfully completed a number of projects modeled from real-world problems to test their comprehension and application of concepts and tools collected from the courses. Through a combination of lectures, live sessions, peer collaboration and applied projects, the recipient is equipped to apply mathematical theory and decision making techniques to draw important insights from collected data to drive decisions.
A participant needs to complete three Computer Science graduate-level courses (9 graduate credit hours) in data processing, data mining, statistical machine learning, and data visualization, in addition to completing hands-on applied projects demonstrating their knowledge and comprehension of the course material.
This digital credential certifies that the recipient successfully completed the required Computer Science graduate-level courses in the following areas: Statistical Machine Learning, Artificial Intelligence, Knowledge Representation and Reasoning, and Intro to Deep Learning in Visual Computing The recipient also successfully completed 5 time-intensive projects modeled from real-world problems to test their comprehension and application of concepts and tools collected from the courses. Through a combination of lectures, live sessions, peer collaboration and applied projects, the recipient understands how machines learn through learning paradigms, how to create autonomous agents, and how to train and optimize deep neural networks. The recipient has a deeper understanding in mathematics foundational skills, the AI techniques used by skilled practitioners, working effectively on machine learning projects, and how to identify opportunities for direct application of AI.
A participant needs to complete three Computer Science graduate-level courses (9 graduate credit hours) in statistical machine learning, artificial intelligence, knowledge representation and reasoning, and deep learning in visual computing. In addition, participants must complete hands-on applied projects demonstrating their knowledge and comprehension of the course material.
This digital credential certifies that the recipient successfully completed the learning components and has met all of the requirements of the Lean Six Sigma Black Belt certification program offered by Arizona State University. The recipient is capable of managing and leading complex and transformative projects designed to increase efficiency and remove obstacles from an organization’s processes and workflows. The holder of this digital credential can apply the DMAIC methodology, design for six sigma and lean product development concepts to product/process design projects. In addition, a certified Lean Six Sigma Black Belt uses appropriate analytical, statistical, and lean methods, and a fundamental understanding on how to plan, design and conduct experiments efficiently and effectively. Lean Six Sigma Black Belts oversee tactical and strategic projects as well as various operational functions in their organizations. Other characteristics of a Lean Six Sigma Black Belt professional include demonstration of team leadership, understanding of all aspects of the so called Define-Measure- Analyze-Improve-Control (DMAIC) improvement process, and basic knowledge of lean enterprise concepts that allows identification of the non-value-added elements and activities.
The Lean Six Sigma Black Belt graduate certificate awards the Lean Six Sigma Black Belt certification for participants who successfully complete 5 graduate-level courses, including a LSS capstone course. The required IEE 585 Six Sigma Capstone course involves a real-life six sigma project, conducted under the supervision of the course instructor. The project involves all of the usual and necessary components of the DMAIC (Define, Measure, Analyze, Improve, Control) process of the Six Sigma approach, in addition to the demonstration of a deep understanding of the problem and solution approach by the participant.
Introduction to Analytics for Intelligent Manufacturing
This microcredential certifies that the recipient successfully completed ten hours of instruction, including lab-based assignments, covering the basis of simulation and data driven methods for analysis and improvement of manufacturing systems. The course features engaging hands on experiments to understand the use of data for process improvement and incorporates an industry talk by collaborators from the largest companies in Arizona to demonstrate the application of concepts learned in the courses in the workplace.
This ten-hour course introduces the earner to simulation and data driven methods for analysis and improvement of manufacturing systems. The course modules offer a lecture and hands-on lab training in simulation and computer design of experiments, fundamental topics in quality control, and an overview to operations, modeling, and optimization in industry. The earner has successfully completed all required portions of this course.
This digital credential certifies that the recipient successfully completed the learning components and has met all of the requirements of the IIoT: Raspberry Pi with MQTT Level 2 Micro-badge offered by Arizona State University. The holder of this digital credential has the ability to develop a functional backend-middleware-frontend working solution with raspberry pi4 and showcase a solution with basic analysis with data contained within the database historian.
This micro-badge is offered at Level 2. Level 2 micro-badges empower learners to apply their foundational knowledge through hands-on practice, allowing them to demonstrate their skills with tangible evidence. To earn this badge, learners must demonstrate their ability to develop a functional backend-middleware-frontend working solution with raspberry pi4 and showcase a solution with basic analysis with data contained within the database historian.
This digital credential certifies that the recipient successfully completed the learning components and has met all of the requirements of the IIoT: MQTT Protocol Level 2 Micro-badge offered by Arizona State University. The holder of this digital credential has the demonstrated proficiency in implementing MQTT communication and developing dashboards using Node-red.
This micro-badge is offered at Level 2. Level 2 micro-badges empower learners to apply their foundational knowledge through hands-on practice, allowing them to demonstrate their skills with tangible evidence. To earn this micro-badge, individuals must simulate publishing and subscribing to machine data via MQTT in Node-red as well as create a node-red dashboard for simulated machine monitoring.
This digital credential certifies that the recipient successfully completed the learning components and has met all of the requirements of the IIoT: Industrial Data Flow Level 2 Micro-badge offered by Arizona State University. The holder of this digital credential has the demonstrated an understanding of the foundational principles of smart manufacturing and how data flow contributes to smart manufacturing initiatives.
This micro-badge is offered at Level 2. Level 2 micro-badges empower learners to apply their foundational knowledge through hands-on practice, allowing them to demonstrate their skills with tangible evidence. To earn this micro-badge, individuals must give contemporary examples of the applications of Smart Manufacturng, and perform a case study for a small manufacturer profile in the context of industrial data flow.
This digital credential certifies that the recipient successfully completed the learning components and has met all of the requirements of the IIoT: Factory Dashboard with MQTT Level 2 Micro-badge offered by Arizona State University. The holder of this digital credential has the demonstrated an their ability to analyze simulated machine-generated data via MQTT and create a Grafana Canvas UI dashboard to visualize data on a web framework.
This micro-badge is offered at Level 2. Level 2 micro-badges empower learners to apply their foundational knowledge through hands-on practice, allowing them to demonstrate their skills with tangible evidence.
Industrial Internet of Things (IIoT) with MQTT Protocol Badge
This digital credential certifies that the recipient successfully completed the learning components and has met all of the requirements of the Industrial Internet of Things Badge offered by Arizona State University. The holder of this digital credential has completed all four of the related micro-badge: Industrial Data Flow, MQTT Protocol, Factory Dashboard with MQTT, and Raspberry Pi with MQTT. This recipient has demonstrated skills in IIoT technology stack management, MQTT protocol implementation, front-end UI development, middleware deployment, and smart manufacturing integration.
Each micro badge part of this sequence is offered at Level 2. Level 2 micro-badges empower learners to apply their foundational knowledge through hands-on practice, allowing them to demonstrate their skills with tangible evidence. To earn this badge, individuals must complete all four micro-badges in the sequence: Industrial Data Flow, MQTT Protocol, Factory Dashboard with MQTT, Raspberry Pi with MQTT. Through this sequence, recipients must demonstrate their mastery of skills like describing how data flows from the machine asset to the factory information system, identifying, interpreting , and applying the publish-subscribe (Pub-Sub) based MQTT communication protocol, and deploying middleware services that connect the backend and frontent of an IIoT hardware-software stack.
Engineering Project Management Certificate
This digital credential certifies that the recipient successfully completed the learning components and has met all of the requirements of the Engineering Project Management Certificate program offered by Arizona State University. The recipient holds a deep grasp of engineering project management principles, including project life cycle, key deliverables, and budget adherence. Certificate holders excel in defining project requirements, applying Work Breakdown Structure (WBS), and using Project Evaluation and Review Technique (PERT)/Critical Path Method (CPM) for effective scheduling. They are also proficient in Earned Value Management (EVM) and Agile methodologies, ensuring adaptability and efficiency. This certification validates the recipient's skill in enhancing project execution and delivering significant organizational value, making it a testament to their capability to manage and navigate complex engineering projects efficiently.
The Engineering Project Management course consists of 15 hours of instruction, and an applied project. Participants will have 30 days after completing the 5-week training to submit complete their project consisting of a scope statement, Work Breakdown Structure and PERT/CPM diagram, a Monitor and Control Logbook, and a final report. During this time, the course instructors will provide coaching and advising to participants after specific phases of the project. For successful completion, participants must attend the 3-hour weekly sessions and successfully complete an Engineering Project Management applied project.
Fundamentals Geometric Dimensioning and Tolerancing
Fundamentals of Geometric Dimensioning and Tolerancing (GD&T) This Level 2 micro-badge recognizes participants who have successfully completed a 10-hour introductory course on Geometric Dimensioning and Tolerancing (GD&T). The program equips learners with foundational knowledge of GD&T symbols, their meanings, and applications in interpreting prints and 3D models. Participants demonstrated their skills through hands-on practice, showcasing their ability to apply this international design standard for precise part feature control and tolerance analysis.
To earn this micro-badge, participants must successfully complete the 10-hour GD&T course and pass the final exam with a score of 70% or higher.
Introduction to Semiconductor Packaging and Design
This digital credential certifies that the recipient successfully completed the learning components and has met all of the requirements of the Introduction to Semiconductor Packaging and Design Micro-badge offered by Arizona State University.
This micro-badge is offered at Level 1, focusing on foundational knowledge in semiconductor packaging and design. Level 1 Micro-badges cover essential concepts, key terms, and industry-specific examples that provide a comprehensive understanding of the subject matter. To earn this micro-badge, participants must complete all course sessions and achieve a score of 70% or higher on the assessments. The assessments will evaluate your understanding of semiconductor packaging types, the role of packaging in technological advancements, and the latest trends in the field.
Introduction to Electrical Concepts in Semiconductor Packaging
This digital credential certifies that the recipient successfully completed the learning components and has met all of the requirements of the Introduction to Electrical Concepts in Semiconductor Packaging Micro-badge offered by Arizona State University.
This micro-badge is offered at Level 1, focusing on foundational knowledge in electrical concepts related to semiconductor packaging. Level 1 Micro-badges cover essential theories, key terminology, and practical examples that are crucial for understanding the electrical aspects of semiconductor packaging. To earn this micro-badge, participants must complete all course sessions and achieve a score of 70% or higher on the assessments. These assessments will test your grasp of power delivery network design, signal integrity principles, and the implementation of voltage regulation and noise reduction techniques in semiconductor packaging.
Introduction to Thermal Management and Mechanical Properties of Packages
This digital credential certifies that the recipient successfully completed the learning components and has met all of the requirements of the Introduction to Thermal Management and Mechanical Properties of Packages Micro-badge offered by Arizona State University.
This micro-badge is offered at Level 1, focusing on foundational knowledge in thermal management and mechanical properties of semiconductor packages. Level 1 Micro-badges cover essential principles, key concepts, and practical applications that are crucial for understanding the thermal and mechanical integrity of electronic packages. To earn this micro-badge, participants must complete all course sessions and achieve a score of 70% or higher on the assessments. These assessments will test your understanding of thermal resistance, heat transfer methods, and the mechanical behavior of materials in semiconductor packaging, ensuring you can apply these concepts to real-world scenarios.
Introduction to Packaging Materials, Manufacturing, Test, and Reliability
This digital credential certifies that the recipient successfully completed the learning components and has met all of the requirements of theIntroduction to Packaging Materials, Manufacturing, Test, and Reliability Micro-badge offered by Arizona State University.
This micro-badge is offered at Level 1, focusing on foundational knowledge in packaging materials, manufacturing processes, testing, and reliability in the semiconductor industry. Level 1 Micro-badges provide a broad overview of essential concepts, key terminology, and practical examples in these areas. To earn this micro-badge, participants must complete all course sessions and achieve a score of 70% or higher on the assessments. These assessments will evaluate your grasp of material selection, manufacturing techniques, and reliability testing in semiconductor packaging, along with process control systems and statistical analysis.
Semiconductor Packaging: Fundamental Concepts and Drivers
This digital credential certifies that the recipient successfully completed the learning components and has met all of the requirements of the Semiconductor Packaging: Fundamental Concepts and Drivers Badge offered by Arizona State University. The holder of this digital credential has completed all four of the related micro-badge: Introduction to Semiconductor Packaging and Design, Introduction to Electrical Concepts in Semiconductor Packaging, Introduction to Thermal Management and Mechanical Properties of Packages and Introduction to Packaging Materials, Manufacturing, Test, and Reliability.
To earn this badge, individuals must complete all four micro-badges in the sequenceThis full badge is offered at Level 1, encompassing a comprehensive understanding of semiconductor packaging across four key areas: design, electrical concepts, thermal management, and materials/manufacturing processes. To earn the full badge, participants must complete all four micro-badges within the approved sequence, achieving a score of 70% or higher on each assessment. This ensures a solid grasp of semiconductor packaging principles, from design and electrical concepts to thermal management and reliability testing. Completing this full badge also qualifies participants for Continuing Education Units (CEU).
Introduction to Microcontrollers and Electronics
This digital credential certifies that the recipient successfully completed the learning components and has met all of the requirements of the Introduction to Microcontrollers and Electronics Level 1 Micro-badge offered by Arizona State University. The holder of this digital credential has the demonstrated and ability to simulate basic electrical circuits , understand the usages of microcontrollers and integrate them into electrical circuits.
Level 1 Micro-badges are associated with foundational knowledge, broader picture, key terms, explanations around a specific topic and examples of the use across the technology sector. This micro-badge is offered at Level 1, providing foundational knowledge on the topics of electricity, circuits, and microcontrollers. To earn this micro-badge, participants must successfully complete in-class exercises and activities that demonstrate knowledge and their ability to integrate a microcontroller in a circuit to complete a specific function.
This digital credential certifies that the recipient successfully completed the "Robotic Arm Programming and Control" Level 1 Micro-badge offered by Arizona State University. The holder of this digital credential has demonstrated foundational knowledge in robotic arm components, programming, and control (ie: integrating sensors, implementing control algorithms, and understanding the essential principles of kinematics and actuation.)
This micro-badge is offered at Level 1, providing foundational knowledge on the components and control of robotic arms, as well as their applications in various industries. To earn this micro-badge, participants must successfully complete hands-on activities and in-class exercises that demonstrate their understanding of robotic arm assembly, integration of sensors, and the ability to implement a basic control algorithm for arm manipulation.
This digital credential certifies that the recipient successfully completed the "Introduction to Autonomous Robots" Level 1 Micro-badge offered by Arizona State University. The holder of this digital credential has demonstrated foundational knowledge in autonomous robotic systems, including design, sensing, and control, as well as an understanding of basic programming concepts and levels of autonomy in robotics.
This micro-badge is offered at Level 1, providing foundational knowledge on the components, control, and autonomy of robotic systems. To earn this micro-badge, participants must demonstrate their understanding of basic robotic components such as sensors, actuators, and controllers through in-class activities and an interactive case study, as well as present key control components necessary for developing a real-world autonomous system.
Import Pretrained Deep Learning in TensorFlow
This digital credential certifies that the recipient successfully completed the "Import Pretrained Deep Learning Models in TensorFlow" Level 2 Micro-badge offered by Arizona State University. The holder of this digital credential has demonstrated intermediate knowledge of deep learning and TensorFlow, and can access, import, and work with pretrained deep learning models in a Python programming environment.
This micro-badge is offered at Level 2, providing knowledge of deep learning concepts, TensorFlow fundamentals, and pretrained models. To earn this micro-badge, participants must demonstrate their understanding of deep learning and neural networks, as well as their ability to code, debug, and solve problems using TensorFlow. This includes successfully importing and working with pretrained models in a Python programming environment.
This micro-badge is offered at Level 2, focusing on advanced knowledge of 2D packaging and assembly within the semiconductor industry. Level 2 Micro-badges provide in-depth coverage of complex concepts, key terminology, and practical applications, enabling participants to gain a deeper understanding of the subject matter.
To earn this micro-badge, participants must complete all course sessions and achieve a score of 70% or higher on the assessments. These assessments will evaluate your expertise in lead frame assembly, advanced wire bonding techniques, flip chip technology, and PCB assembly processes, including detailed inspection and quality control methodologies essential to 2D semiconductor packaging.
Materials Selection for Thermo-Mechanical and Electrical Performance
This micro-badge is offered at Level 2, focusing on advanced knowledge of materials selection for optimizing thermo-mechanical and electrical performance in semiconductor packaging. Level 2 Micro-badges provide in-depth exploration of complex concepts, key terminology, and practical applications in this critical area.
To earn this micro-badge, participants must complete all course sessions and achieve a score of 70% or higher on the assessments. These assessments will test your ability to evaluate material properties such as thermal conductivity, electrical conductivity, and mechanical strength, and apply these principles to solve thermo-mechanical and electrical challenges in semiconductor packaging.
Application of Electrical & Thermo-Mechanical Modeling
This micro-badge is offered at Level 2, focusing on advanced modeling techniques for electrical and thermo-mechanical properties in semiconductor packaging. Level 2 Micro-badges provide comprehensive coverage of complex modeling concepts, essential terminology, and practical examples critical for mastering semiconductor package modeling.
To earn this micro-badge, participants must complete all course sessions and achieve a score of 70% or higher on the assessments. These assessments will evaluate your expertise in electrical, thermal, and thermo-mechanical analysis, optimization techniques, and the application of simulation tools to solve real-world packaging challenges in the semiconductor industry.
Test and Data Analysis for Quality and Reliability
This micro-badge is offered at Level 2, focusing on testing methodologies and data analysis for ensuring quality and reliability in semiconductor packaging. Level 2 Micro-badges provide in-depth coverage of key concepts, analytical tools, and practical applications critical for evaluating package performance. To earn this micro-badge, participants must complete all course sessions and achieve a score of 70% or higher on the assessments. These assessments will test your understanding of reliability testing techniques, data analysis methods, and statistical tools used to assess product quality and predict failure modes in semiconductor packaging.
This micro-badge is offered at Level 2, focusing on advanced testing methodologies and data analysis for ensuring quality and reliability in semiconductor packaging. Level 2 Micro-badges provide in-depth coverage of key concepts, analytical tools, and practical applications critical for evaluating package performance. To earn this micro-badge, participants must complete all course sessions and achieve a score of 70% or higher on the assessments. These assessments will test your understanding of reliability testing techniques, data analysis methods, and statistical tools used to assess product quality and predict failure modes in semiconductor packaging.
Semiconductor Packaging, Assembly, and Test
This digital credential certifies that the recipient successfully completed the learning components and has met all the requirements of the Semiconductor Packaging, Assembly, and Test Badge offered by Arizona State University. The holder of this digital credential has completed all four related micro-badges: 2D Packaging and Assembly, Materials Selection for Thermo-Mechanical and Electrical Performance, Application of Electrical and Thermo-Mechanical Modeling, and Test and Data Analysis for Quality and Reliability.
This full badge is offered at Level 2 and requires the completion of all four micro-badges: 2D Packaging and Assembly, Materials Selection for Thermo-Mechanical and Electrical Performance, Application of Electrical and Thermo-Mechanical Modeling, and Test and Data Analysis for Quality and Reliability. Each micro-badge focuses on advanced concepts, essential terminology, and practical applications relevant to semiconductor packaging and manufacturing. To earn this full badge, participants must complete all course sessions for each micro-badge and achieve a score of 70% or higher on the assessments associated with each. These assessments will evaluate your comprehensive understanding of semiconductor packaging processes, material properties, modeling techniques, and testing methodologies, ensuring you are well-equipped to excel in the semiconductor industry.
Utilize Pretrained DL Models in TensorFlow
This digital credential certifies that the recipient successfully completed the "Utilize Pretrained Deep Learning Models in TensorFlow" Level 2 Micro-badge offered by Arizona State University. The holder of this digital credential has demonstrated intermediate knowledge of feature extraction and decision-making using pretrained deep learning models in TensorFlow, along with hands-on experience in applying these techniques in a Python programming environment.
This micro-badge is offered at Level 2, providing knowledge of deep learning-based feature extraction and decision-making using pretrained models. To earn this micro-badge, participants must demonstrate their ability to code, debug, and solve problems using TensorFlow, particularly in the context of feature extraction and decision-making with pretrained deep learning models. This includes completing activities involving the transfer and update of pretrained models.
Develop Convolutional Neural Networks with TensorFlow
This digital credential certifies that the recipient successfully completed the "Develop Convolutional Neural Networks in TensorFlow" Level 2 Micro-badge offered by Arizona State University. The holder of this digital credential has demonstrated an understanding of CNN model architecture, coding CNNs in TensorFlow, and applying these models to process image data.
To earn this Level 2 micro-badge, recipients demonstrated foundational skills in building and implementing Convolutional Neural Networks (CNNs) using TensorFlow. They completed hands-on activities, including coding CNNs from scratch, designing model architecture, and training models on image data. Additionally, they showed a thorough understanding of image convolution processes, the unique strengths and weaknesses of CNNs, and their application to different types of imaging data. Their work evidenced their ability to apply CNN knowledge to practical problem-solving in a Python programming environment.
The Microcontroller Programming Basics micro-badge covers essential skills for beginners in microcontroller programming. Students explore basic program structure, syntax, and key logic concepts, such as if-statements, for-loops, and functions. They also practice using flowcharts to plan code and apply debugging techniques with tools like breakpoints and the serial monitor. Ideal for those interested in engineering or tech, this course provides hands-on experience with microcontroller applications, building foundational skills to understand and troubleshoot code effectively.
To earn this Level 1 micro-badge, recipients demonstrated a foundational understanding of microcontroller programming concepts, such as setup and loop functions, variables, and logic structures. They applied basic programming logic and structures, including if-statements, for-loops, and while-loops, to design and troubleshoot microcontroller programs. Additionally, recipients showcased their ability to plan and represent processes using flowcharts, and effectively used debugging tools, such as breakpoints and the serial monitor, to identify and resolve code issues.
Develop Recurrent Neural Networks with TensorFlow
This digital credential certifies that the recipient successfully completed the "Develop Recurrent Neural Networks in TensorFlow" Level 2 Micro-badge offered by Arizona State University. The holder of this digital credential has demonstrated an intermediate understanding of recurrent neural networks (RNNs) and their applications to time-series data. They have showcased the ability to design, code, and debug RNN models using TensorFlow in a Python programming environment. Additionally, the recipient has analyzed the strengths, weaknesses, and practical uses of RNNs compared to other deep learning models such as CNNs.
This Level 2 micro-badge builds on foundational deep learning knowledge. To earn it, participants must demonstrate an understanding of time-series data, RNN architecture, and training. They must compare RNNs to other models like CNNs, highlighting strengths and applications, and successfully design, code, and debug RNN models using TensorFlow. Proficiency is validated through coding tasks and real-world use case applications.
This digital credential certifies that the recipient successfully completed the Deep Learning with TensorFlow Badge offered by Arizona State University. The holder of this credential has demonstrated proficiency in using TensorFlow to develop and deploy deep learning models, gaining both foundational and applied knowledge in neural network design and implementation. By completing four related micro-badges, the recipient has acquired skills in importing and utilizing pretrained models, creating custom CNNs for image classification, and designing RNNs for sequential and temporal data processing. These skills enable the recipient to apply TensorFlow to solve real-world artificial intelligence and machine learning challenges.
To earn this badge, participants are required to complete four related micro-badges. Learners must demonstrate an ability to import pretrained models from TensorFlow modules, utilize these models for feature extraction and decision-making tasks, and apply foundational concepts of neural network architectures to build and implement Convolutional and Recurrent Neural Networks. Participants are assessed through hands-on coding exercises, ensuring they can use TensorFlow’s library functions and modules effectively for creating, training, and deploying advanced deep learning models.
This digital credential certifies that the recipient completed the Industrial Ultrasonic Testing I Badge from Arizona State University, demonstrating proficiency in Ultrasonic Testing (UT), a key nondestructive testing (NDT) method. By earning four micro-badges—Basic Principles of Materials Processing and Nondestructive Testing, Basic Principles of Ultrasonic Testing, Ultrasonic Testing Techniques, and Practical Training of Straight Beam Testing—the recipient gained expertise in material properties, defect detection, ultrasonic wave principles, and UT system operation. Through hands-on training and simulation tools, the recipient developed skills in calibrating UT equipment, performing straight beam and thickness testing, and analyzing ultrasonic data. This badge qualifies as 40 hours of UT Level 1 training, aligning with ASNT CP105 and SNT-TC-1A certification guidelines, and prepares recipients for roles in oil and gas, aerospace, automotive, and aviation industries. Through hands-on training and simulation tools, the recipient developed skills in calibrating UT equipment, performing straight beam and thickness testing, and analyzing ultrasonic data. This badge qualifies as 40 hours of UT Level 1 training, aligning with ASNT certification guidelines, and prepares recipients for roles in oil and gas, aerospace, automotive, and aviation industries.
To earn this badge, participants are required to complete all four related micro-badges: Basic Principles of Materials Processing and Nondestructive Testing, Basic Principles of Ultrasonic Testing, Ultrasonic Testing Techniques, and Practical Training of Straight Beam Testing. Learners must demonstrate an understanding of material properties, manufacturing processes, and the basic principles of ultrasonic testing. They must also show proficiency in using UT equipment for straight beam testing, performing straight beam calibration, thickness measurements, and simulating ultrasonic testing scenarios using simulation software.
Basic Principles of Materials Processing and Nondestructive Testing
This digital credential certifies that the recipient successfully completed the "Basic Principles of Materials Processing and Nondestructive Testing" ASU Level 1 Micro-badge offered by Arizona State University. The holder of this credential has demonstrated foundational knowledge in traditional and advanced manufacturing processes, material properties, and nondestructive testing (NDT) methods. The recipient is familiar with common defects associated with manufacturing processes and the role of NDT in evaluating materials without causing damage. This micro-badge equips individuals with a general understanding of material testing methods and their applications in various industries.
This micro-badge is offered at ASU Level 1, providing foundational knowledge of materials processing, material properties, and nondestructive testing methods. To earn this micro-badge, participants must demonstrate an understanding of traditional and advanced manufacturing processes, identify defects associated with these processes, and explain the relationship between material properties and destructive testing. Additionally, recipients must show their knowledge of the most common nondestructive testing methods including ultrasonic testing (UT), radiography testing (RT), eddy current testing (ET), acoustic emission (AE), mag-particle testing (MT), and penetrant testing (PT), their applications, and limitations. The micro-badge includes content on casting, forging, welding, and post-processing methods, along with an introduction to over the 6 NDT methods. The categorization of levels follows the ASU badge description and is not associated with the SNT-TC-1A levels.
This digital credential certifies that the recipient successfully completed the "Basic Principles of Ultrasonic Testing (UT)" ASU Level 2 Micro-badge offered by Arizona State University. The holder of this credential has demonstrated foundational knowledge of ultrasonic testing (UT) methods, including the physical theory behind sound wave propagation, the equipment used in UT, and the types of ultrasound waves involved. The recipient is also familiar with the functionality of UT systems, including transducers, amplifiers, and data acquisition systems. This micro-badge equips individuals with essential skills for applying ultrasonic testing in various industries.
This micro-badge is offered at ASU Level 2, providing foundational knowledge of the physical principles behind ultrasonic testing, along with an understanding of the equipment used in UT. To earn this micro-badge, participants must demonstrate their understanding of sound wave theory, the functionality of UT systems, and the ability to identify and utilize different types of ultrasound wave modes. Participants should also be able to simulate an ultrasound beam and explain the principles of various UT methods, including pulse-echo testing and immersion UT using simulation software. This includes an understanding of key concepts such as acoustic impedance, Snell’s law, and the effects of reflection, refraction, and mode conversion. The categorization of levels follows the ASU badge description and is not associated with the SNT-TC-1A levels.
This digital credential certifies that the recipient successfully completed the "Ultrasonic Testing Techniques" ASU Level 2 Micro-badge offered by Arizona State University. The holder of this credential has demonstrated proficiency in various ultrasonic testing techniques, including contact straight beam testing for thickness measurement and corrosion inspection. The recipient has gained expertise in simulating ultrasonic testing using advanced software and has participated in cyber hands-on training, reinforcing their understanding of beam intensity, resolution, sensitivity, and the interaction of ultrasound with discontinuities. This micro-badge prepares individuals to apply ultrasonic testing in real-world scenarios effectively.
This micro-badge is offered at ASU Level 2, providing intermediate knowledge of ultrasonic testing techniques, including straight beam and angle beam testing. To earn this micro-badge, participants must demonstrate their understanding of ultrasound beam parameters, sensitivity, resolution, and the interaction of ultrasound with different discontinuities. This includes successfully identifying and applying test standards, utilizing ultrasonic simulation tools, and performing cyber hands-on training to reinforce practical skills. The categorization of levels follows the ASU badge description and is not associated with the SNT-TC-1A levels.
Practical Training of Straight Beam Testing
This digital credential certifies that the recipient successfully completed the "Practical Training of Straight Beam Testing" ASU Level 2 Micro-badge offered by Arizona State University. The holder of this credential has gained hands-on experience and proficiency in performing contact straight beam ultrasonic testing (UT) for thickness measurement, corrosion inspection, and composite material evaluation. The recipient has demonstrated the ability to calibrate UT equipment, perform tests on metallic and composite materials, and evaluate and report ultrasonic data according to industrial standards. This micro-badge signifies the application of theoretical knowledge into practical skills using both cyber hands-on tools and state-of-the-art UT systems.
This micro-badge is offered at ASU Level 2, emphasizing practical application and hands-on training in ultrasonic testing. To earn this micro-badge, participants must demonstrate the ability to perform calibration on UT equipment, conduct thickness testing on metallic and composite materials, and perform corrosion and composite inspections. Participants will also need to evaluate and report ultrasonic testing data accurately. Successful completion involves using both cyber tools and real-world UT systems to follow industry-standard practices. This includes performing straight beam distance calibration, using DAC and TCG for data analysis, and producing clear reports based on test results. The categorization of levels follows the ASU badge description and is not associated with the SNT-TC-1A levels.
This digital credential certifies that the recipient successfully completed the Industrial Ultrasonic Testing II Badge offered by Arizona State University. The holder of this credential has demonstrated proficiency in advanced Ultrasonic Testing (UT) techniques, focusing on weld inspection, corrosion detection, and thickness measurement across industries such as oil and gas, aerospace, automotive, and aviation. By completing all four micro-badges—Ultrasonic Imaging and Angle Beam Testing, Ultrasonic Testing for Defect Detection, Fundamentals of Amplitude-Based UT Sizing, and Practical Training of Straight and Angle Beam UT Evaluation—the recipient has acquired skills in simulating and performing angle beam UT, detecting defects in welds, applying amplitude-based UT sizing methods, and operating state-of-the-art UT systems for real-world applications. This badge qualifies as 40 hours of UT Level 2 training, recognized by certification guidelines CP105 and SNT-TC-1A from the American Society for Nondestructive Testing (ASNT).
To earn this badge, participants are required to complete all four related micro-badges: Ultrasonic Imaging and Angle Beam Testing, Ultrasonic Testing for Defect Detection, Fundamentals of Amplitude-Based UT Sizing, and Practical Training of Straight and Angle Beam UT Evaluation. Learners must demonstrate their ability to operate advanced UT simulation software, perform calibration on UT equipment, and apply ultrasonic imaging for defect detection and weld inspection. Participants are assessed through both theoretical understanding and practical exercises, where they will simulate and apply amplitude-based UT sizing methods (e.g., DAC or TCG) and evaluate ultrasonic data to meet industry standards. This hands-on training ensures that learners can effectively use UT techniques for real-world industrial applications, including weld testing, corrosion detection, and material thickness measurements.
Ultrasonic Imaging and Angle Beam Testing
This digital credential certifies that the recipient successfully completed the "Ultrasonic Imaging and Angle Beam Testing" ASU Level 3 Micro-badge offered by Arizona State University. The holder of this digital credential has gained foundational knowledge in ultrasonic imaging and scanning techniques, including angle beam ultrasonic testing (UT). The recipient has demonstrated the ability to understand and simulate angle beam UT, a critical skill in assessing internal structures and defects within materials.
This micro-badge is offered at ASU Level 3, providing foundational knowledge in ultrasonic imaging and angle beam ultrasonic testing. To earn this micro-badge, the recipient demonstrated an understanding of ultrasound imaging principles and the use of angle beam UT for evaluating materials. The recipient also successfully simulated angle beam UT in practical scenarios, reinforcing their comprehension of these key techniques. This micro-badge is designed to prepare the recipient for further advanced ultrasonic testing applications. The categorization of levels follows the ASU badge description and is not associated with the SNT-TC-1A levels.
This digital credential certifies that the recipient successfully completed the "Ultrasonic Testing for Defect Detection" ASU Level 3 Micro-badge offered by Arizona State University. The holder of this digital credential has demonstrated foundational knowledge and practical skills in using ultrasonic testing (UT) for defect detection, specifically focusing on applications in welds and shear wave inspections. The recipient is proficient in identifying various defects such as porosity, cracks, lack of fusion, and delamination in composite materials, using advanced simulation software and hands-on tools to evaluate material integrity in real-world scenarios.
This micro-badge is offered at ASU Level 3, providing foundational knowledge and skills in ultrasonic testing for defect detection. To earn this micro-badge, the recipient demonstrated an understanding of the basic principles of angle beam UT and ultrasonic imaging techniques for detecting defects. The recipient successfully completed UT simulations for weld testing, identifying defects such as cracks, porosity, and lack of fusion in simulated scenarios. They applied these concepts to evaluate materials using shear wave inspections and ultrasonic imaging. Successful completion was assessed through hands-on simulations and lab exercises, confirming the recipient’s ability to effectively apply ultrasonic testing for defect detection. The categorization of levels follows the ASU badge description and is not associated with the SNT-TC-1A levels.
Fundamentals of Amplitude-Based UT Sizing
This digital credential certifies that the recipient successfully completed the "Fundamentals of Amplitude-based UT Sizing" ASU Level 3 Micro-badge offered by Arizona State University. The holder of this digital credential has acquired foundational knowledge and practical skills in the widely-used defect sizing methods in ultrasonic testing (UT), including Distance Amplitude Correction (DAC), Time-Corrected Gain (TCG), and Distance Gain Size (DGS). The recipient is proficient in applying these methods in various applications, such as forging, casting, welding, and advanced manufacturing processes, using advanced simulation software and cyber hands-on training to reinforce their understanding.
This micro-badge is offered at ASU Level 3, providing foundational knowledge and skills in amplitude-based ultrasonic testing sizing methods. To earn this micro-badge, the recipient demonstrated a fundamental understanding of DAC, TCG, and DGS methods used in ultrasonic testing. The recipient successfully simulated amplitude-based ultrasound testing, applying these sizing techniques to real-world scenarios through advanced simulation software. Additionally, they showcased their knowledge of relevant test standards, reinforcing their understanding through cyber hands-on training and exercises. This demonstrated the recipient’s ability to effectively utilize these methods in evaluating and sizing defects in materials used in forging, casting, welding, composites, and advanced manufacturing. The categorization of levels follows the ASU badge description and is not associated with the SNT-TC-1A levels.
Practical Training of Straight and Angle Beam UT Evaluation
This digital credential certifies that the recipient successfully completed the "Practical Training of Straight and Angle Beam UT Evaluation" ASU Level 3 Micro-badge offered by Arizona State University. The holder of this digital credential has acquired practical knowledge and skills in performing straight and angle beam ultrasonic testing (UT) evaluations, including weld inspections and shear wave inspections. The recipient has gained the knowledge on Time of Flight Diffraction (TOFD), guided waves, and phased array ultrasonic testing technologies. The recipient has demonstrated the ability to utilize advanced ultrasonic software and testing systems and cyber hands-on tools to evaluate real-world samples containing internal discontinuities, such as cracks, while adhering to industry standards.
This micro-badge is offered at ASU Level 3, providing foundational knowledge and practical skills in performing straight and angle beam ultrasonic testing evaluations. To earn this micro-badge, the recipient demonstrated the ability to simulate TOFD and phased array in UT software as well as calibrate UT equipment, perform weld inspections using angle beam techniques, and evaluate ultrasonic data for internal discontinuities, such as lack of fusion, lack of penetration, porosities as well as cracks. The recipient also successfully reported their findings according to common industry standards. This was achieved through hands-on training using advanced ultrasonic testing systems and cyber tools, reinforcing their practical skills for real-world applications. The categorization of levels follows the ASU badge description and is not associated with the SNT-TC-1A levels.
This digital credential certifies that the recipient successfully completed the "Microcontroller Sensors and Actuators" Level 2 Micro-badge offered by Arizona State University. The holder of this digital credential has demonstrated the ability to integrate sensors and actuators into microcontroller systems, control motors using H-bridges, and differentiate between analog and digital signals. They have applied these skills through hands-on labs to design and implement simple microcontroller-based control systems.
This micro-badge is offered at Level 2. Level 2 micro-badges empower learners to apply their foundational knowledge through hands-on practice, allowing them to demonstrate their skills with tangible evidence. To earn this micro-badge, participants must demonstrate their ability to differentiate between analog and digital sensors and apply appropriate usage techniques for each. They must successfully integrate sensors and actuators into a microcontroller-based system, including selecting, mounting, and controlling various actuators such as DC motors, servos, and linear actuators. Participants must also implement an H-bridge circuit to control motor speed and direction and use a microcontroller to process sensor input, adjusting actuator behavior accordingly. These skills are assessed through hands-on labs and activities that require learners to design, implement, and troubleshoot functional sensor-actuator control systems.
Introduction to Industrial Robotics: Fundamentals
This digital credential certifies that the recipient successfully completed the "I2R: Fundamentals" Level 2 Micro-badge offered by Arizona State University. The holder of this digital credential has demonstrated knowledge of industrial robotics, including robot configurations, motion control, and safety standards. They have also gained hands-on experience in programming and controlling basic industrial robot tasks while applying risk assessment and safety measures in simulated environments.
This micro-badge is offered at Level 2, providing applied knowledge of industrial robotics, robot programming, and safety standards. To earn this micro-badge, participants must demonstrate their ability to program and control basic industrial robot tasks, assess risks in robotic workcells, and apply safety standards in a simulated environment. This includes successfully programming an industrial robot for tasks such as pick-and-place, welding, or material handling, conducting a risk assessment for a robotic workcell by identifying hazards and proposing mitigation strategies, analyzing a case study on industrial robotics applications to evaluate the benefits of automation, and implementing ISO 10218 safety standards in a simulated work environment.
This Level 3 microcredential provides a foundational understanding of semiconductor materials and crystal structures and how they influence device performance. Learners explore charge carrier dynamics, P-N junction behavior, and band diagrams, along with key concepts such as diode operations under various bias conditions. Practical insights into industry applications, fabrication techniques, and metal-semiconductor junctions prepare learners for advanced studies in semiconductor devices.
To earn this micro-badge, participants must complete all course sessions and achieve a score of 70% or higher on the assessments. These assessments will test your ability to analyze crystal structures, charge carrier dynamics, and P-N junction behavior, and apply these concepts to evaluate device performance, fabrication techniques, and industry applications of semiconductor junctions.
This Level 3 microcredential covers foundational concepts in semiconductor device physics, focusing on field-effect transistors (FETs), MOS capacitors, and MOSFETs. Learners will explore device operation, threshold voltage, and advanced effects such as tunneling and oxide breakdown, gaining essential insights into long-channel device characteristics and industry applications.
To earn this micro-badge, participants must complete all course sessions and achieve a score of 70% or higher on the assessments. These assessments will test your ability to analyze FETs, MOS capacitors, and MOSFETs, explain device operation and threshold voltage behavior, interpret band diagrams and C-V curves, and evaluate advanced effects such as tunneling, oxide breakdown, and subthreshold characteristics in long-channel MOSFET devices.
This Level 4 microcredential deepens learners' expertise in MOSFET physics and device behavior through the analysis of I-V curves and their responses to variations in doping, capacitance, and bias conditions. Learners will explore advanced scaling techniques, second-order effects, and concepts such as DIBL and GIDL, applying models to optimize performance and address real-world semiconductor design challenges.
To earn this micro-badge, participants must complete all course sessions and achieve a score of 70% or higher on assessments. These assessments will evaluate the ability to analyze MOSFET I-V curves, model advanced device architectures, assess second-order effects like DIBL and GIDL, and apply scaling techniques to optimize device performance.
This Level 4 microcredential equips learners with a practical understanding of MOSFET reliability, advanced scaling techniques, and innovations like FinFETs and Gate-All-Around architectures. Participants will explore reliability concerns such as hot carrier effects, latch-up, and oxide breakdown, while analyzing memory and logic applications. The course emphasizes strategies to enhance performance and reliability, highlighting design and fabrication trade-offs in modern semiconductor technologies.
To earn this micro-badge, participants must complete all course sessions and achieve a score of 70% or higher on assessments. These assessments will evaluate the ability to analyze MOSFET reliability issues, interpret I-V characteristics for memory and logic applications, compare FinFET and GAA architectures, and apply advanced fabrication techniques to optimize device performance and longevity.
Applied Semiconductor Physics for Device Engineering
The Applied Semiconductor Physics for Device Engineering microcredential is designed for device engineers and semiconductor professionals, providing comprehensive training in semiconductor theory and practical device physics. This program equips participants with the skills needed to analyze and address unexpected device behavior by applying foundational knowledge of device physics to real-world scenarios. Through the completion of four micro-badges, learners will deepen their understanding of semiconductor devices, including MOSFETs and advanced scaling techniques, while strengthening their ability to resolve issues and optimize processes. By integrating theoretical knowledge with hands-on application, this microcredential prepares professionals to meet the challenges of modern semiconductor device engineering.
To earn this full microcredential, participants must complete all course sessions and pass the four associated micro-badges. This includes achieving a score of 70% or higher on all assessments across each micro-badge, covering topics such as semiconductor junctions, MOS devices, and advanced MOSFETs. Participants must demonstrate their ability to apply device physics concepts to real-world challenges and optimize semiconductor processes.
Assistive Technology Microcontroller Applications
This digital credential certifies that the recipient successfully completed the "Assistive Technology Microcontroller Applications" Level 2 Micro-badge offered by Arizona State University. The holder of this digital credential has demonstrated the ability to apply the engineering design process to develop an assistive technology prototype utilizing a microcontroller. Through hands-on activities, they have explored prototyping strategies, material selection, and iterative design to create functional solutions for real-world accessibility challenges.
This micro-badge is offered at Level 2, building on foundational knowledge of microcontrollers, electronics, and programming. To earn this micro-badge, participants must integrate and apply skills from prior coursework to develop a real-world assistive technology project using a microcontroller. They must demonstrate proficiency in prototyping, material selection, and iterative design by successfully designing, building, and presenting a functional prototype.
Microcontroller Applications: Programming and Electrical Basics to Integration
This digital credential certifies that the recipient successfully completed the Microcontroller Applications Badge offered by Arizona State University. The holder of this credential has demonstrated proficiency in applying microcontrollers to real-world engineering challenges, from basic circuit design to advanced assistive technology applications. By completing all four micro-badges—Introduction to Microcontrollers and Electronics, Microcontroller Programming Basics, Microcontroller Sensors and Actuators, and Assistive Technology Microcontroller Applications—the recipient has gained hands-on experience in electrical circuits, microcontroller programming, sensor integration, and prototyping. These skills equip the recipient to develop intelligent, real-world solutions utilizing microcontroller systems.
To earn this badge, participants are required to complete all four related micro-badges: Introduction to Microcontrollers and Electronics, Microcontroller Programming Basics, Microcontroller Sensors and Actuators, and Assistive Technology Microcontroller Applications. Learners must demonstrate their ability to design, program, and integrate microcontroller-based systems, progressing from fundamental electrical and coding concepts to advanced assistive technology applications. Participants are assessed through simulations, hands-on labs, debugging exercises, and prototyping projects, ensuring they can effectively develop and implement microcontroller-driven solutions.
Analyzing the Movement of Industrial Robotic Arms: Kinematics
This digital credential certifies that the recipient successfully completed the “Analyzing the Movement of Industrial Robotic Arms: Kinematics” Level 2 Micro-badge offered by Arizona State University. The holder of this credential has demonstrated applied knowledge of robotic arm motion through kinematic modeling, including forward and inverse kinematics, differential kinematics, and trajectory planning. Using tools like MATLAB and Simulink, the recipient has engaged in both analytical and hands-on exercises to simulate and solve real-world robotic motion problems.
This micro-badge is offered at Level 2, providing applied knowledge of robotic arm motion through the study of kinematics and trajectory planning. To earn this micro-badge, participants must demonstrate their ability to perform forward and inverse kinematics, apply differential kinematics using Jacobian analysis, and model robotic arm motion in simulation. This includes successfully completing a final project involving trajectory planning and obstacle avoidance using MATLAB and Simulink.
Understanding the Forces and Motion in Robotic Arms: Dynamics
This digital credential certifies that the recipient successfully completed the "Understanding the Forces and Motion in Robotic Arms: Dynamics" Level 2 Micro-badge offered by Arizona State University. The holder of this digital credential has demonstrated the ability to apply core concepts of robot dynamics to analyze the forces and motion within serial-link robotic arms. This includes deriving equations of motion using Lagrangian mechanics and utilizing MATLAB and Simulink to evaluate robotic behavior under defined operating conditions.
This micro-badge is offered at Level 2, emphasizing the application of foundational robotics knowledge in practical and structured scenarios. To earn this micro-badge, participants must demonstrate their ability to analyze and model the dynamic behavior of robotic arms using appropriate mathematical tools and software. Learners complete guided lab activities, engage in peer feedback, and apply their skills through a final project involving the computation of joint forces and torques for a robotic arm following a specified trajectory.