Build a Movie Tracking API with FastAPI and Python

Build a Restful API with FastAPI. Learn the FastAPI framework. Use MongoDB. Learn about middleware. Deploy on Kubernetes

What you'll learn
Learn to build APIs with FastAPI and Python and organize your projects.
Learn to use MongoDD as a database.
Learn to apply advanced development techniques.
Learn to improve development workflow using Docker and Python specific tools.
Learn about FastAPI's middleware and authentication.
Learn to write unit-tests.
Learn to deploy your application on Kubernetes.

Requirements
Python programming experience recommended but not necessary. It can be picked while working on the course.
General knowledge about how the web works is recommended to have.

Description
Statistics and Data Analysis for Business using MS Excel tries to expose students to the statistical concepts that are used to solve business problems. In this course students will learn statistical concepts and techniques through a mix of lectures on theoretical concepts and intuitions behind statistical techniques, and practical application of statistical methods in solving real world business problems. The course is meant for beginners to statistics and also for people who have had previous exposure to statistics. The course covers basics to advanced level concepts, and allows students to learn both concepts and applications. After finishing this course students will learn how to use data to solve business problems, how to study trends in data and use these trends to infer about the business setting they are studying. The course will also allow students to gain a better understanding of key concepts and the nuances in statistical methods. The course covers the following topics:

1. Descriptive Statistics.

2. Data Visualisation.

3. Different types of data and variables.

4. Sampling strategies and how to infer from samples.

5. Inferential Statistics.

6. Hypothesis Testing.

7. T tests

8. Analysis of variance.

9. Linear Regression and regression techniques.

10. Logistic Regression

11. Non linear regression and distributions.

12. Practical Application of statistics.

13. Data Analysis method and process.

14. Microsoft Excel for Data Analysis.

Who this course is for:
Beginners in statistics who want to learn statistical concepts
Beginners in statistics who want to gain data analysis skills
People with intermediate knowledge of statistics who want to refresh concepts and learn business statistics
People who want to learn the concepts and tools that are used in solving most business problems
Business Managers who want to learn implementation of statistics for solving business problems
People who want to learn statistics and data analysis to solve business problems
People who want to learn how to identify trends in data and use data to answer business problems