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Course Detail

Course Name Advanced Computer Programming Lab
Course Code 26CSC182
Semester 2
Credits 1
Campus Coimbatore

Syllabus

Syllabus

List of Exercises:

  1. Develop programs using classes, objects, and methods.
  2. Apply inheritance and encapsulation concepts in program design.
  3. Implement polymorphism techniques, including method overloading.
  4. Install external packages and utilize them in Python scripts.
  5. Create programs to import and use user-defined packages.
  6. Apply NumPy and SciPy to solve basic mathematical problems.
  7. Implement data handling operations in Pandas for working with CSV data.
  8. Read noisy datasets and perform data preprocessing using Pandas.
  9. Implement various plotting and charting techniques using Matplotlib.
  10. Analyze datasets and identify suitable features for visualization using Seaborn.
  11. Develop Python scripts to retrieve and process web data, including parsing, searching, and formatting, using Beautiful Soup, urllib, and Regular Expressions.
  12. Implement database access and manipulation using Python scripts.
  13. Design a graphical user interface to capture input and store data in database tables, performing insert, update, delete, and select operations through the GUI.
Text Books / References
  1. Allen B. Downey,Think Python: How to Think Like a Computer Scientist,O’Reilly Media, 2024.
  2. William McKinney, Python for Data Analysis: Data Wrangling with Pandas, NumPy, and Ipython, Second edition (27 October 2017), Shroff/O’Reilly, ISBN-10: 9789352136414,ISBN-13: 978-9352136414.
  3. Michael Urban and Joel Murach, Python Programming, Shroff/Murach, 2016.
  4. Mark Lutz, Programming Python, O`Reilly, 4th Edition, 2010.
  5. Adi Adhikari and John DeNero, “Computational and Inferential Thinking: The Foundations of Data Science”, e-book.

Objectives and Outcomes

Course Outcomes:

  • Apply object-oriented programming principles to design and implementation.
  • Utilize predefined Python packages and develop user-defined packagesfor computational tasks.
  • Perform data preprocessing operations and visualize data effectively using Matplotlib and Seaborn.
  • Extract and process web data using BeautifulSoup, and apply regular expressions for pattern matching.
  • Develop Python applications that integrate MySQL database operations and design graphical user interfaces using Tkinter widgets.

CO–PO Mapping:

CO’s PO1 PO2 PO3 PO4 PO5 PO6 PO7 PO8 PO9 PO10 PO11 PO12
CO1 3 3 2     1     2 2    
CO2 3 2 2   1 3           2
CO3 3 2 3 2 2 3       1    
CO4 2 2 3 2   3       2    
CO5 2   3 1 1 3     2 3 2  

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