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Mo Rebaie
In this 1-hour long project-based course, you'll step into the exciting field of Computer Vision and Generative AI using the LandingLens platform. We'll start by exploring the concept of visual prompting, and initiating a visual prompting project. LandingLens simplifies the model creation, training, and deployment process, making it a user-friendly platform for this endeavor.
Read more
In this 1-hour long project-based course, you'll step into the exciting field of Computer Vision and Generative AI using the LandingLens platform. We'll start by exploring the concept of visual prompting, and initiating a visual prompting project. LandingLens simplifies the model creation, training, and deployment process, making it a user-friendly platform for this endeavor.
Read more
In this 1-hour long project-based course, you'll step into the exciting field of Computer Vision and Generative AI using the LandingLens platform. We'll start by exploring the concept of visual prompting, and initiating a visual prompting project. LandingLens simplifies the model creation, training, and deployment process, making it a user-friendly platform for this endeavor.
This project will lead you to build and deploy various models like object detection, segmentation, and classification, with hands-on tasks guiding you through the steps of uploading data, labeling, training, and deploying your models both on the cloud and an edge device. It's tailored for a broad audience - students, professionals, freelancers, and business leaders keen on exploring the combined power of Computer Vision and Generative AI. With no stringent prerequisites, anyone comfortable with online platforms can navigate through this project successfully, gaining practical insights into visual prompting and model deployment.
Register for this course and see more details by visiting:
OpenCourser.com/course/m4cwbj/landing
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What's inside
Syllabus
Work with LandingLens on Visual Prompting and Computer Vision
By the end of this project, learners will be able to create, train, and deploy computer vision models using LandingLens for object detection, segmentation, classification, and visual prompting, both on cloud platforms and edge devices.
Good to know
Good to know
Know what's good ,
what to watch for , and
possible dealbreakers
Well-aligned to the interests of professionals, freelancers, and business leaders who wish to explore visual prompting for computer vision applications
Suitable for students looking to gain practical experience in deploying vision models on cloud platforms and edge devices
Utilizes the LandingLens platform, simplifying the model creation and deployment process for learners
Projects are hands-on and task-based, guiding learners through each step of the model building and deployment process
No strict prerequisites, making it accessible to those with varying backgrounds
Save this course
Save Landing.AI for Beginners: Build Data Visualization AI Models to your list so you can find it easily later:
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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 Landing.AI for Beginners: Build Data Visualization AI Models with these
activities:
Refresher on Python Basics
Show steps
Review the basics of Python to ensure you're ready to tackle this course's challenges.
Browse courses on
Python
Show steps
-
Review basic data structures (e.g., lists, tuples, dictionaries)
-
Practice writing simple functions and methods
-
Experiment with different Python libraries (e.g., NumPy, Pandas)
Follow along with the LandingLens tutorial series
Show steps
Gain hands-on experience with LandingLens through their guided tutorials, familiarizing yourself with the platform's features.
Show steps
-
Access the LandingLens tutorial series
-
Follow the step-by-step instructions to create and deploy a basic model
-
Experiment with different model configurations and parameters
Build a portfolio of example projects
Show steps
Showcase your skills and demonstrate your understanding of visual prompting and model deployment by creating a portfolio of projects.
Show steps
-
Choose a variety of project ideas that demonstrate different aspects of your skillset
-
Develop and train models for each project
-
Deploy your models on both cloud platforms and edge devices
Three other activities
Expand to see all activities and additional details
Show all six activities
Collaborate with peers on a group project
Show steps
Team up with other students to tackle a challenging project, leveraging diverse perspectives and fostering collaboration.
Show steps
-
Form a team with complementary skills
-
Brainstorm project ideas and select one to work on
-
Divide responsibilities and work together to develop and deploy the model
Attend a workshop on advanced computer vision techniques
Show steps
Deepen your understanding of computer vision by attending a workshop that explores advanced techniques and applications.
Show steps
-
Research and identify a relevant workshop
-
Register and attend the workshop
-
Actively participate in discussions and demonstrations
Seek guidance from industry experts
Show steps
Connect with experienced professionals in the field to gain valuable insights and expand your knowledge.
Show steps
-
Identify potential mentors through professional networks or online platforms
-
Reach out to potential mentors and request guidance
-
Schedule regular meetings and ask for advice on your projects and career
Refresher on Python Basics
Show steps
Review the basics of Python to ensure you're ready to tackle this course's challenges.
Browse courses on
Python
Show steps
Show steps
Show steps
- Review basic data structures (e.g., lists, tuples, dictionaries)
- Practice writing simple functions and methods
- Experiment with different Python libraries (e.g., NumPy, Pandas)
Follow along with the LandingLens tutorial series
Show steps
Gain hands-on experience with LandingLens through their guided tutorials, familiarizing yourself with the platform's features.
Show steps
Show steps
Show steps
- Access the LandingLens tutorial series
- Follow the step-by-step instructions to create and deploy a basic model
- Experiment with different model configurations and parameters
Build a portfolio of example projects
Show steps
Showcase your skills and demonstrate your understanding of visual prompting and model deployment by creating a portfolio of projects.
Show steps
Show steps
Show steps
- Choose a variety of project ideas that demonstrate different aspects of your skillset
- Develop and train models for each project
- Deploy your models on both cloud platforms and edge devices
Three other activities
Expand to see all activities and additional details
Show all six activities
Collaborate with peers on a group project
Show steps
Team up with other students to tackle a challenging project, leveraging diverse perspectives and fostering collaboration.
Show steps
Show steps
Show steps
- Form a team with complementary skills
- Brainstorm project ideas and select one to work on
- Divide responsibilities and work together to develop and deploy the model
Attend a workshop on advanced computer vision techniques
Show steps
Deepen your understanding of computer vision by attending a workshop that explores advanced techniques and applications.
Show steps
Show steps
Show steps
- Research and identify a relevant workshop
- Register and attend the workshop
- Actively participate in discussions and demonstrations
Seek guidance from industry experts
Show steps
Connect with experienced professionals in the field to gain valuable insights and expand your knowledge.
Show steps
Show steps
Show steps
- Identify potential mentors through professional networks or online platforms
- Reach out to potential mentors and request guidance
- Schedule regular meetings and ask for advice on your projects and career
Career center
Learners who complete Landing.AI for Beginners: Build Data Visualization AI Models will develop knowledge and skills
that may be useful to these careers:
Data Scientist
Data Scientist
Data Scientists are responsible for collecting, cleaning, and analyzing data to extract insights and solve business problems. This course will help you develop the skills necessary to become a successful Data Scientist, including how to use LandingLens to build and deploy computer vision models. These models can be used to automate tasks, improve decision-making, and gain a competitive advantage.
Computer Vision Engineer
Computer Vision Engineer
Computer Vision Engineers design and develop computer vision systems that can see and understand the world around them. This course will teach you the fundamentals of computer vision and how to build and deploy computer vision models using LandingLens. With this knowledge, you will be able to develop innovative solutions to real-world problems, such as object detection, segmentation, and classification.
Machine Learning Engineer
Machine Learning Engineer
Machine Learning Engineers build and deploy machine learning models to solve business problems. This course will help you develop the skills necessary to become a successful Machine Learning Engineer, including how to use LandingLens to build and deploy computer vision models. These models can be used to automate tasks, improve decision-making, and gain a competitive advantage.
Software Engineer
Software Engineer
Software Engineers design, develop, and maintain software applications. This course will help you develop the skills necessary to become a successful Software Engineer, including how to use LandingLens to build and deploy computer vision models. These models can be used to enhance the functionality of software applications and create new and innovative solutions.
Data Analyst
Data Analyst
Data Analysts collect, clean, and analyze data to extract insights and solve business problems. This course will teach you the fundamentals of data analysis and how to use LandingLens to build and deploy computer vision models. These models can be used to automate tasks, improve decision-making, and gain a competitive advantage.
Product Manager
Product Manager
Product Managers are responsible for the development and launch of new products. This course will help you develop the skills necessary to become a successful Product Manager, including how to use LandingLens to build and deploy computer vision models. These models can be used to improve product design, optimize marketing campaigns, and gain a competitive advantage.
Business Analyst
Business Analyst
Business Analysts identify and solve business problems. This course will help you develop the skills necessary to become a successful Business Analyst, including how to use LandingLens to build and deploy computer vision models. These models can be used to improve business processes, identify new opportunities, and gain a competitive advantage.
Sales Manager
Sales Manager
Sales Managers are responsible for the development and execution of sales strategies. This course will help you develop the skills necessary to become a successful Sales Manager, including how to use LandingLens to build and deploy computer vision models. These models can be used to improve sales strategies, optimize targeting, and gain a competitive advantage.
Marketing Manager
Marketing Manager
Marketing Managers are responsible for the development and execution of marketing campaigns. This course will help you develop the skills necessary to become a successful Marketing Manager, including how to use LandingLens to build and deploy computer vision models. These models can be used to improve marketing campaigns, optimize targeting, and gain a competitive advantage.
User Experience Designer
User Experience Designer
User Experience Designers design and evaluate the user experience of products and services. This course will help you develop the skills necessary to become a successful User Experience Designer, including how to use LandingLens to build and deploy computer vision models. These models can be used to improve the user experience of products and services, increase engagement, and gain a competitive advantage.
Operations Manager
Operations Manager
Operations Managers are responsible for the day-to-day operations of a business. This course will help you develop the skills necessary to become a successful Operations Manager, including how to use LandingLens to build and deploy computer vision models. These models can be used to improve operations, optimize processes, and gain a competitive advantage.
Project Manager
Project Manager
Project Managers are responsible for the planning and execution of projects. This course will help you develop the skills necessary to become a successful Project Manager, including how to use LandingLens to build and deploy computer vision models. These models can be used to improve project planning, execution, and monitoring.
Human Resources Manager
Human Resources Manager
Human Resources Managers are responsible for the management of human resources within a company. This course may be useful for Human Resources Managers who want to learn how to use computer vision models to improve recruiting and hiring processes.
Customer Success Manager
Customer Success Manager
Customer Success Managers are responsible for ensuring the satisfaction of customers. This course may be useful for Customer Success Managers who want to learn how to use computer vision models to improve customer support and satisfaction.
Financial Analyst
Financial Analyst
Financial Analysts analyze financial data to make investment recommendations and provide financial advice. This course may be useful for Financial Analysts who want to learn how to use computer vision models to analyze financial data.
For more career information including salaries, visit:
OpenCourser.com/course/m4cwbj/landing
Reading list
We've selected six 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
Landing.AI for Beginners: Build Data Visualization AI Models.
Save
Provides a comprehensive overview of computer vision algorithms and techniques, covering topics such as image formation, feature detection, object recognition, and image segmentation. It valuable resource for anyone interested in learning more about the fundamentals of computer vision.
Provides a practical introduction to deep learning for computer vision tasks, covering topics such as convolutional neural networks, object detection, and image segmentation. It valuable resource for anyone interested in learning how to apply deep learning to computer vision problems.
Save
Provides a comprehensive overview of computer vision using OpenCV, a popular open-source library for computer vision. It valuable resource for anyone interested in learning how to use OpenCV to develop computer vision applications.
Provides a comprehensive overview of computer vision, covering topics such as image formation, feature detection, object recognition, and image segmentation. It valuable resource for anyone interested in learning more about the fundamentals of computer vision.
Provides a comprehensive overview of pattern recognition and machine learning, covering topics such as supervised learning, unsupervised learning, and reinforcement learning. It valuable resource for anyone interested in learning more about the theory and practice of machine learning.
Provides a comprehensive overview of machine learning for computer vision, covering topics such as image classification, object detection, and image segmentation. It valuable resource for anyone interested in learning more about the theory and practice of machine learning for computer vision.
For more information about how these books relate to this course, visit:
OpenCourser.com/course/m4cwbj/landing
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Effort
1 hour
Level
Introductory
Via
Coursera
Institution
Coursera Project Network
Instructor
Mo Rebaie
Language
English
Transcripts
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Good to know
Well-aligned to the interests of professionals, freelancers, and business leaders who wish to explore visual prompting for computer vision applications
Suitable for students looking to gain practical experience in deploying vision models on cloud platforms and edge devices
Utilizes the LandingLens platform, simplifying the model creation and deployment process for learners
Projects are hands-on and task-based, guiding learners through each step of the model building and deployment process
No strict prerequisites, making it accessible to those with varying backgrounds
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