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Tebogo Nakampe and Thabo Koee
In this 2-hour long project-based course, you will learn how to Build a Crossroad AI Camera: Learning Objective 1: By the end of Task 1, you will be able to explain the OpenVINO™ Toolkit Workflow and OpenVINO™ Toolkit Components Learning Objective 2: By the end of Task 2, you will be able to operationalize models using the Model Downloader utility Learning Objective 3: By the end of Task 3, you will be able to perform Model Preparation, Conversion and Optimization Learning Objective 4: By the end of Task 4, you will be able to Running and Tuning Inference Learning Objective 5: By the end of Task 5, you will be able to create...
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In this 2-hour long project-based course, you will learn how to Build a Crossroad AI Camera: Learning Objective 1: By the end of Task 1, you will be able to explain the OpenVINO™ Toolkit Workflow and OpenVINO™ Toolkit Components Learning Objective 2: By the end of Task 2, you will be able to operationalize models using the Model Downloader utility Learning Objective 3: By the end of Task 3, you will be able to perform Model Preparation, Conversion and Optimization Learning Objective 4: By the end of Task 4, you will be able to Running and Tuning Inference Learning Objective 5: By the end of Task 5, you will be able to create visualization of Person Attributes and Person Re-identification (REID) information for each detected person in an Image/Video/Camera input.
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Good to know

Know what's good
, what to watch for
, and possible dealbreakers
Teaches skills, knowledge, and/or tools that are highly relevant in academic settings
Builds a strong foundation for beginners
Taught by Tebogo Nakampe, Thabo Koee, who are recognized for their work in their respective fields
Examines computer vision techniques, which is highly relevant to industry
Teaches skills, knowledge, and/or tools that are highly relevant to industry
Involves learning the OpenVINO™ Toolkit Workflow, Model Preparation, Conversion and Optimization, Running and Tuning Inference, and creating visualization

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Activities

Be better prepared before your course. Deepen your understanding during and after it. Supplement your coursework and achieve mastery of the topics covered in OpenVINO Beginner: Building a Crossroad AI Camera with these activities:
Offer Support to Fellow Learners
Strengthens understanding through teaching and provides opportunities for practice.
Browse courses on AI
Show steps
  • Connect with other learners through online forums or study groups.
  • Offer assistance on topics you're familiar with.
  • Facilitate discussions and share resources.
Follow Tutorials on Intel's OpenVINO Toolkit
Provides hands-on experience with the tools and techniques used in the course.
Show steps
  • Identify tutorials relevant to the tasks covered in the course.
  • Work through the tutorials, implementing the concepts in your own environment.
  • Experiment with different parameters to understand the impact on performance.
Attend Meetup Groups or Conferences on AI
Connects with professionals in the field and exposes to new ideas.
Browse courses on AI
Show steps
  • Identify relevant meetup groups or conferences.
  • Attend events, participate in discussions, and network with other attendees.
  • Share knowledge and insights with others.
Two other activities
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Show all five activities
Complete Coding Exercises on Model Deployment
Reinforces understanding of concepts and improves coding skills.
Browse courses on Model Deployment
Show steps
  • Find coding exercises or challenges related to deploying AI models.
  • Attempt to solve the exercises using the concepts learned in the course.
  • Review solutions and identify areas for improvement.
Develop a Crossroad AI Camera Prototype
Provides a practical application of the skills learned in the course.
Show steps
  • Gather necessary materials and resources.
  • Design and implement the AI model for object detection.
  • Integrate the model with a camera and display system.
  • Test and evaluate the prototype's performance.

Career center

Learners who complete OpenVINO Beginner: Building a Crossroad AI Camera will develop knowledge and skills that may be useful to these careers:
Computer Vision Engineer
The course will provide you with the skills to develop robust and efficient computer vision applications. As a **Computer Vision Engineer**, you will be responsible for designing, developing, and maintaining computer vision algorithms and systems. This course will provide you with the technical foundation to excel in this role by equipping you with knowledge on object detection, image segmentation, and other fundamental concepts in computer vision.
AI Architect
The course will equip you with the knowledge to design and implement end-to-end AI solutions. As an **AI Architect**, you will be responsible for designing, developing, and deploying AI systems. This course will help you gain a comprehensive understanding of the AI development cycle and provide you with the skills to effectively leverage the OpenVINO™ Toolkit to optimize and accelerate your AI solutions for real-world applications.
AI Developer
The course offers practical hands-on experience in developing and deploying AI applications using the OpenVINO™ Toolkit. As an **AI Developer**, you will leverage your expertise in software engineering, machine learning, and deep learning to design, develop, and deploy AI solutions. This course will provide you with the skills to effectively utilize the OpenVINO™ Toolkit to optimize and accelerate your AI applications for real-world applications.
Deep Learning Engineer
The course offers a hands-on approach to deploying deep learning models using the OpenVINO™ Toolkit. As a **Deep Learning Engineer**, you will leverage your expertise in deep learning, machine learning, and software engineering to design, develop, and deploy deep learning solutions. This course will provide you with the skills to effectively utilize the OpenVINO™ Toolkit to optimize and accelerate your deep learning models for real-world applications.
Machine Learning Scientist
The course offers a deep dive into optimizing and deploying machine learning models using the OpenVINO™ Toolkit. As a **Machine Learning Scientist**, you will leverage your expertise in machine learning, deep learning, and statistics to research and develop innovative machine learning solutions. This course will provide you with the skills to effectively utilize the OpenVINO™ Toolkit to optimize and accelerate your machine learning models for real-world applications.
Computer Vision Researcher
The course provides an introduction to the fundamentals of computer vision and object detection. As a **Computer Vision Researcher**, you will leverage your expertise in computer vision, machine learning, and deep learning to research and develop innovative computer vision algorithms and techniques. This course will provide you with the necessary theoretical foundation to excel in this role by equipping you with knowledge on object detection, image segmentation, and other fundamental concepts in computer vision.
Embedded Systems Engineer
The course includes a focus on deploying computer vision models on embedded devices, such as those used in autonomous vehicles and surveillance systems. As an **Embedded Systems Engineer**, you will leverage your expertise in hardware design, software engineering, and computer vision to design, develop, and deploy embedded systems. This course will provide you with the skills to effectively integrate computer vision capabilities into your embedded systems.
Machine Learning Engineer
The course provides a comprehensive introduction to the OpenVINO™ Toolkit, which is essential for deploying machine learning models on various hardware platforms. As a **Machine Learning Engineer**, you will leverage your expertise in machine learning, deep learning, and software engineering to design, develop, and deploy machine learning solutions. This course will provide you with the necessary skills to effectively utilize the OpenVINO™ Toolkit to optimize and accelerate your machine learning models for real-world applications.
Robotics Engineer
The course teaches how to deploy computer vision models on embedded devices. As a **Robotics Engineer**, you will leverage your expertise in robotics, computer vision, and software engineering to design, develop, and deploy autonomous robotic systems. This course will provide you with the skills to integrate computer vision capabilities into your robotic systems and pave the way for the development of more intelligent and autonomous robots.
AI Engineer
The course covers the foundational concepts of computer vision, object detection, and model optimization. As an **AI Engineer**, you will leverage your expertise in machine learning, deep learning, and software engineering to design, develop, and deploy AI solutions. This course will provide you with the necessary technical skills to excel in this role by equipping you with knowledge on object detection, image segmentation, and other fundamental concepts in computer vision.
AI Consultant
The course covers the end-to-end process of deploying AI solutions, including model optimization, performance tuning, and real-world considerations. As an **AI Consultant**, you will leverage your expertise in AI, machine learning, and business to advise clients on the implementation and adoption of AI solutions. This course will provide you with the knowledge and skills to effectively guide clients through the AI adoption journey and help them achieve successful outcomes.
Data Scientist
The course provides foundational knowledge on object detection and recognition, which are essential skills for **Data Scientists**. As a **Data Scientist**, you will leverage your expertise in machine learning, statistics, and programming to analyze and interpret data. This course will provide you with the necessary technical skills to develop and implement AI models for various applications in the field of computer vision.
Product Manager
The course provides insights into the practical considerations and challenges involved in deploying AI solutions. As a **Product Manager**, you will leverage your expertise in product management, market research, and technology to identify, define, and deliver successful AI products. This course will provide you with the knowledge to effectively evaluate and integrate AI technologies into your product roadmap and make informed decisions.
Data Analyst
The course provides a comprehensive overview of the OpenVINO™ Toolkit, which is essential for optimizing and deploying machine learning models on various hardware platforms. As a **Data Analyst**, you will leverage your expertise in data analysis, statistics, and programming to analyze and interpret data. This course will provide you with the necessary technical skills to effectively utilize the OpenVINO™ Toolkit to optimize and accelerate your data analysis pipelines.
Software Engineer
The course provides comprehensive knowledge on optimizing and deploying AI models using the OpenVINO™ Toolkit. As a **Software Engineer**, you will be responsible for designing, developing, and maintaining software systems. This course will provide you with the necessary skills to effectively integrate AI capabilities into your software solutions.

Reading list

We've selected nine books that we think will supplement your learning. Use these to develop background knowledge, enrich your coursework, and gain a deeper understanding of the topics covered in OpenVINO Beginner: Building a Crossroad AI Camera.
Provides a comprehensive introduction to deep learning, covering the underlying theory and algorithms, as well as practical guidance on how to build and train deep learning models. It good resource for anyone who wants to learn more about deep learning and how to use it to solve real-world problems.
Provides a comprehensive introduction to machine learning, covering the underlying theory and algorithms, as well as practical guidance on how to build and train machine learning models. It good resource for anyone who wants to learn more about machine learning and how to use it to solve real-world problems.
Provides a comprehensive guide to deep learning for computer vision, covering the underlying theory and algorithms, as well as practical guidance on how to build and train deep learning models for computer vision tasks. It good resource for anyone who wants to learn more about deep learning for computer vision.
Provides a comprehensive overview of computer vision algorithms and applications. It good resource for anyone who wants to learn more about computer vision and how it is used to solve real-world problems.
Provides a comprehensive overview of pattern recognition and machine learning algorithms. It good resource for anyone who wants to learn more about machine learning and how it is used to solve real-world problems.
Provides a comprehensive overview of statistical learning algorithms. It good resource for anyone who wants to learn more about machine learning and how it is used to solve real-world problems.
Provides a comprehensive overview of deep learning algorithms. It good resource for anyone who wants to learn more about deep learning and how it is used to solve real-world problems.
Provides a comprehensive overview of computer vision algorithms. It good resource for anyone who wants to learn more about computer vision and how it is used to solve real-world problems.
Provides a comprehensive overview of machine learning algorithms. It good resource for anyone who wants to learn more about machine learning and how it is used to solve real-world problems.

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