Full Stack Web App Development Project
Build and deploy a real-world full stack web application on the cloud in this 2-week practical course.
Build and deploy a real-world full stack web application on the cloud in this 2-week practical course.
Master full stack development by creating a real-world web application in this hands-on project course. Over two weeks, you'll apply your front-end and back-end skills to build and deploy a cloud-based application. The project showcases your proficiency in user experience and interface design, coupled with technical expertise in Django, Python, Node.js, and Containers. You'll work with cutting-edge cloud services like Watson AI, Cloudant, and Cloud Object Storage. The course covers the entire development lifecycle, from creating static pages to implementing user management, integrating back-end services, and deploying containerized applications to Kubernetes. By completing this project, you'll gain practical experience that demonstrates your full stack capabilities to potential employers, enhancing your career prospects in web development.
4.3
(54 ratings)
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What you'll learn
Build a real-world web application using front-end and back-end technologies
Deploy a Django full stack web application on the cloud
Integrate cloud services including Watson AI, Cloudant, and Cloud Object Storage
Implement user management and CI/CD pipelines in web applications
Develop dynamic pages using React.js for enhanced user interfaces
Containerize and deploy web applications to Kubernetes environments
Skills you'll gain
This course includes:
PreRecorded video
Graded assignments, exams
Access on Mobile, Tablet, Desktop
Limited Access access
Shareable certificate
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Top companies offer this course to their employees
Top companies provide this course to enhance their employees' skills, ensuring they excel in handling complex projects and drive organizational success.
There are 6 modules in this course
This project-based course allows students to apply their full stack development knowledge to build and deploy a real-world web application on the cloud. The curriculum covers the entire development process, from creating static pages to implementing dynamic features with React.js, setting up back-end services, and containerizing the application for deployment on Kubernetes. Students will work with various technologies including JavaScript, React.js, Python, Django, Node.js, and Express. The course also introduces cloud services such as Watson AI, Cloudant, and Cloud Object Storage. By the end of the project, participants will have hands-on experience with a complete web application development lifecycle, enhancing their practical skills and employability in the field of full stack development.
Application – Static Pages
Module 1
Application – User Management and CI/CD
Module 2
Back End Services
Module 3
Application – Dynamic Pages (React.js)
Module 4
Containerize and Deploy to K8S
Module 5
Share Your Project
Module 6
Fee Structure
Instructors
65 Courses
Full Stack Developer and Machine Learning Expert at IBM
Upkar Lidder serves as a senior software engineer at IBM, bringing over a decade of experience in IT development, including significant roles in team management and technical leadership. His expertise spans full-stack technology, with a current focus on Machine Learning and Artificial Intelligence. As an active member of the tech community, he regularly shares his knowledge through speaking engagements at conferences and participation in local tech groups and meetups. His technical portfolio includes extensive work with serverless applications, Apache OpenWhisk platform, and various aspects of cloud-native development. After completing his graduate studies in Canada, he now resides in the United States, where he contributes to IBM's developer initiatives while also serving as an instructor for numerous courses in web development, DevOps, and mobile application development using Flutter and Dart.
87 Courses
AI and Machine Learning Expert at IBM Canada
Yan Luo serves as a Data Scientist and Developer at IBM Canada, where he applies his expertise in machine learning and artificial intelligence to develop innovative cognitive applications across diverse domains including software repository mining, personalized health management, wireless networks, and digital banking. After earning his Ph.D. in Machine Learning from the University of Western Ontario, he has contributed significantly to technical education through developing and teaching multiple data science courses, including Applied Data Science Capstone, Machine Learning Capstone, and Introduction to R Programming for Data Science. His work focuses on practical applications of AI and cognitive computing, bridging the gap between theoretical machine learning concepts and real-world business solutions.
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4.3 course rating
54 ratings
Frequently asked questions
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