Python REST APIs with Flask, Docker, MongoDB, and AWS DevOps

So you know a bit of Python and want to learn about RESTful API's and other cool technologies like Flask, Docker, MongoDB to name just a few?

Or maybe you just want to add web development Python skills to your resume.

Whatever the reason is, you have landed on the right page if you have an interest in taking your Python skills to the next level.

Why use Python for web development?

Coding in Python is simple, and a student with no prior knowledge can easily understand a line of code and its use - this means with only the basics, you can comfortably write a complete program.

Python has a great number of frameworks and tools to get you up and going fast with web development.  

It's a great match - a powerful language with a great range of tools that you can put to use quickly.

Why choose this course?

• You will be able to learn and understand how to design and implement RESTful API’s via the Flask framework.
• Ever wanted to know what a NoSQL database is, and how to use one?  You'll learn how to do that as well, using Python.
• And what is Docker, and what does it mean to "dockerize" your apps?  Yep, you guessed it, you will learn that as well in this course.  
• You'll even learn how to build a machine learning API using TensorFlow for image recognition.
• Another hot topic is DevOps, and you will learn about that and go through the process of deploying a RESTful API on an Amazon EC2 instance.
• In short, this course is designed to take your basic Python skills and take you to the next level in the shortest period of time.

What topics are covered in this course?

Understanding the Basics of the Python Flask Framework

Understanding and Implementing a  REST API

Docker

MongoDB

Project: Database as a Service Restful API

Project: Building a Restful API for similarity check using Natural Language Processing

Project: Building an Image Recognition Restful API using Tensorflow and Deep Learning

Project: Building a Restful API to Handle Bank Transactions

Deploying Restful API into an AWS EC2 Instance

You'll come away with a firm understanding of how all the pieces work individually, and more importantly how they fit together.

This really is an all in one course to get you up to speed with these topics, fast.

What skills do you need?

The ideal student would be someone with a basic knowledge of Python who is eager to improve their skills.  That's it!

Ready to start?

If you're ready to start the course, then click the enroll button to get started. We look forward to seeing you on the inside.o

It seems like the feedback for the Python and Flask course, particularly for the API development part, is quite mixed with several key points mentioned by different learners: 1. **Teaching Style**: The instructor's teaching style was praised for being clear, engaging, and sometimes for using diagrams to explain concepts, which some learners found helpful compared to screen recordings of code writing. 2. **Content Redundancy**: There is a consensus that the course has repetitive content, especially in the projects section. While some learners found this redundancy beneficial for solidifying understanding, others might have preferred a more streamlined approach. 3. **Docker and Deployment Issues**: Some learners reported difficulties with Docker setups and deployment, suggesting that the provided code might not work on local machines or pointing out the need for using tools like YAML validators and Hadolint for Dockerfile syntax checks. 4. **Updates and Consistency**: There were mentions of inconsistencies in variable naming (not following `snake_case`) and updates within the course where some parts were corrected but not consistently across all lectures, which could be confusing. 5. **Course Structure**: The course was described as providing a good introduction to REST APIs, with a comprehensive overview that includes backend support, containerization, and cloud deployment, suggesting it's a starting point for implementing real-world projects. 6. **Modern MLOps Practices**: The course was praised for covering a full picture of a deployable AI application but acknowledged that it might not cover the entirety of modern MLOps practices, implying that additional learning on topics like Swagger/OpenAPI or FastAPI would be beneficial. 7. **Learning Value**: Overall, learners found value in the course for beginners with some Python exposure, emphasizing that the course structure and content delivery were logical and educational despite a few hiccups. 8. **Mistakes in Course**: Some learners pointed out that the instructor made mistakes during lectures but quickly corrected them. They suggested that learners might need to watch videos multiple times to fully grasp the corrections made. 9. **Feedback for Improvement**: The suggestion was made to ensure the use of capital 'F' for Flask in the code and to clarify the usage of single versus double underscores. 10. **Overall Satisfaction**: Despite some issues, the majority of learners reported a positive learning experience, with many indicating that they found the course valuable and believe it will serve them well in their future development endeavors. In summary, while there are some concerns regarding inconsistencies, outdated content, and potential issues with Docker examples, most learners found the course to be a solid introduction to building REST APIs with Python and Flask, with many finding the teaching style, repetition for learning, and overall structure to be beneficial for understanding the broader context of deploying AI applications.