From Beginner to Advanced | 4 Hands-On Projects
InstructorDr. Alexander Schlee
Free
Free
Free
The curriculum demonstrates how to extract data via APIs and move it into both Excel files and PostgreSQL databases for SQL command execution.
Editorial course preview
These 4 complementary views highlight concrete, legible examples from the course presentation.
The pgAdmin 4 interface displays a SQL query filtering for Mercedes-Benz vehicles priced under 45000, alongside the resulting dataset containing model details.
This image displays a Jupyter Notebook environment configured with a structured Python template that outlines steps for importing libraries, making CURL requests, verifying status codes, and handling JSON data.
The screen displays a web page alongside developer tools, highlighting the Network tab where a JSON response reveals structured data about subjects like Artificial Intelligence.
The browser displays an Autolist car search interface featuring active filters for make, price range, and year alongside a list of vehicle listings.
Instruction covers identifying network traffic to find endpoints, which facilitates practical data extraction from website APIs.
Learner signals indicate a repetitive approach to scraping across modules and a desire for more diverse web examples or depth in tool internals like SQLAlchemy.
One signal suggests the use of in-line code rather than functions, which may impact programming best practices in advanced sections.
The curriculum aligns with the goal of creating datasets for data enthusiasts using Python.