Learn Python Build 24 real-world Python projects - Django, Flask, Data Analysis, OpenCV, automation and more
InstructorAshutosh Pawar
The curriculum moves from basic syntax into specialized domains including web frameworks like Django and Flask, desktop GUI development with Tkinter and PyQt6, and data analysis using Pandas.
Lessons are organized into short segments, which facilitates learning in small portions.
Editorial course preview
These 4 complementary views highlight concrete, legible examples from the course presentation.
The PyCharm editor displays a Python script defining a Student class with methods for initializing attributes and managing user input.
This screenshot shows a Python script in VS Code using Tkinter for the interface and psycopg2 to execute SQL queries against a PostgreSQL database.
This image shows a Jupyter Notebook environment where a dataset named 'sales.csv' has been loaded into a Pandas DataFrame, revealing structured columns such as Date, Gender, Location, City, and Price for data analysis.
This screenshot shows a Jupyter Notebook running locally, featuring a grouped bar chart that visualizes the frequency of three payment methods—Card, Cash, and Gpay—across various time intervals.
Instructional signals suggest a lack of exercises immediately following concept explanations, placing much of the practical application at the end of the course.
One signal from a pre-update review suggests that explanations can lack depth in certain areas, specifically regarding data types and logic building; however, the current update label does not prove these issues were corrected.
The curriculum aligns with the stated goal of teaching beginners, though some signals suggest it may move too quickly for those needing more emphasis on data types.