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Updated in [February 21st, 2023]

Tutorial 1- Why Do We Require MongoDB.
Tutorial 2- MongoDb Installation And Basic CRUD Operations.
Tutorial 3- How To Connect Python With MongoDb- Pymongo Installation.
Tutorial 4- MongoDb With Python- Querying Json Documents|Data Science.
Tutorial 5- MongoDb With Python- Updating Records|Data Science.
Tutorial 6- MongoDb With Python- Aggregate Functions($group,$sum,$avg,$project)- Data Science.
Tutorial 7- Database As A Service- Setting Up MongoDB ATLAS In Cloud With Python.

(Please note that we obtained the following content based on information that users may want to know, such as skills, applicable scenarios, future development, etc., combined with AI tools, and have been manually reviewed)
MongoDB with Python is a comprehensive course that teaches learners how to use MongoDB and Python together to create powerful data-driven applications. Learners will gain an understanding of the fundamentals of MongoDB and how to use it to store and query data. They will also learn how to connect Python with MongoDB using the PyMongo library and how to use MongoDB with Python to query JSON documents and update records. Additionally, learners will learn how to use MongoDB's aggregate functions such as $group, $sum, $avg, and $project to analyze data. Finally, learners will learn how to set up MongoDB Atlas in the cloud with Python. This course is ideal for those who want to learn how to use MongoDB and Python together to create powerful data-driven applications.

[Applications]
Learners can apply their knowledge of MongoDB with Python to develop applications that can store, query, and update data. They can also use the MongoDB Atlas cloud service to set up a MongoDB database in the cloud. Additionally, learners can use the aggregate functions to analyze data and create meaningful insights.

[Career Paths]
1. Data Scientist: Data Scientists use MongoDB with Python to analyze large datasets and uncover insights. They use a variety of techniques such as machine learning, natural language processing, and statistical analysis to uncover patterns and trends in data. They also develop predictive models to forecast future outcomes. With the increasing demand for data-driven decision making, the demand for Data Scientists is expected to grow significantly in the coming years.

2. Database Administrator: Database Administrators are responsible for managing and maintaining MongoDB databases. They are responsible for ensuring the security, performance, and availability of the database. They also develop and implement backup and recovery plans, and monitor the database for any potential issues. With the increasing demand for data-driven decision making, the demand for Database Administrators is expected to grow significantly in the coming years.

3. Data Engineer: Data Engineers are responsible for designing, building, and maintaining data pipelines. They use MongoDB with Python to extract, transform, and load data from various sources into the database. They also develop and maintain data warehouses and data lakes. With the increasing demand for data-driven decision making, the demand for Data Engineers is expected to grow significantly in the coming years.

4. Business Intelligence Analyst: Business Intelligence Analysts use MongoDB with Python to analyze large datasets and uncover insights. They use a variety of techniques such as machine learning, natural language processing, and statistical analysis to uncover patterns and trends in data. They also develop predictive models to forecast future outcomes. With the increasing demand for data-driven decision making, the demand for Business Intelligence Analysts is expected to grow significantly in the coming years.