Enroll Course: https://www.udemy.com/course/data-science-avec-python-sql-fastapi-streamlit-docker/
In the ever-evolving field of data science, staying ahead of the curve is paramount. If you aspire to become a versatile Data Consultant capable of managing projects from start to finish, the course “Data Science avec Python, SQL, FastAPI, Streamlit & Docker” on Udemy is tailor-made for you. This immersive, hands-on course allows you to step into the shoes of a consultant for a fictitious company, CineData Insights, on a mission to transform raw movie data into a smart platform.
### Course Overview
The course is structured around three key stages:
1. **Data Modeling and Centralization**: You will learn how to design a relational database using SQLite, ensuring that you can effectively manage and centralize data.
2. **API Development**: You will construct a robust RESTful API using FastAPI and SQLAlchemy. This API will be secure, well-documented, and containerized with Docker, ready for deployment in the cloud.
3. **Real-Time Visualization**: Finally, you will create a Streamlit application that connects to your API, providing real-time data visualization and insights for end-users.
This course not only equips you with theoretical knowledge but also emphasizes practical skills. By the end, you will have a significant project to showcase in your portfolio, making you stand out in interviews or freelance opportunities.
### What You Will Learn
– Design a relational database from CSV files.
– Create a robust RESTful API with FastAPI and SQLAlchemy.
– Deploy your API using Docker on Render or locally.
– Develop a Python SDK to interact with your API and publish it on PyPI.
– Analyze data from your API using a Python notebook.
– Build a Streamlit web application connected to your API.
– Present interactive cinema insights to end-users.
– Manage a complete data project like a true professional.
### Why Take This Course?
– Tired of tutorials that scratch the surface? This course offers a comprehensive system-building experience.
– Gain in-demand skills in FastAPI, SQLAlchemy, SQLite, Streamlit, Docker, and more.
– Add a strong project to your portfolio that will impress potential employers.
– Learn through a fun and practical case study.
### Prerequisites
While a good foundation in Python is necessary (file manipulation, functions, classes), prior knowledge of SQL and REST APIs is beneficial but not mandatory as everything is explained step-by-step. Comfort with development environments like Jupyter and VSCode is also required.
### Who Is This Course For?
– Python developers looking to advance beyond traditional data analysis.
– Data analysts or engineers wanting to learn API construction.
– Freelancers and consultants aiming to deliver complete projects.
– Anyone seeking a modern, realistic project to enhance their portfolio.
### Conclusion
If you are serious about stepping into the world of data science and want to build a project that showcases your skills, I highly recommend enrolling in “Data Science avec Python, SQL, FastAPI, Streamlit & Docker” on Udemy. With its practical approach and comprehensive content, this course is an excellent investment in your future as a data professional.
Enroll Course: https://www.udemy.com/course/data-science-avec-python-sql-fastapi-streamlit-docker/