Useful for ISS
Python is the language you will use for the rest of the degree and, most likely, the rest of your career in data science. Data Mining (Sem IV), Python for Data Analysis (Sem IV), Machine Learning, Deep Learning, NLP — all of them assume this course.
Weak Python here means struggling in every later course. Strong Python here makes them comfortable. If you have limited time, spend it on this course.
To introduce the fundamentals of Python programming, including environment setup, syntax and core concepts.
To develop problem-solving skills using control flow, functions and modules.
To provide knowledge of Python data structures, file handling and exception handling for effective programming.
To impart object-oriented programming concepts and GUI development skills for building applications.
Apply control flow constructs, functions and modules to develop structured programs.
Demonstrate the use of sequences, sets and dictionaries for data handling.
Features, programming modes, identifiers, literals, built-in types, operators and precedence.
UNIT 2if-elif-else, loops, for…else; functions, argument types, scope, recursion, lambda; modules and namespaces.
UNIT 3Strings, lists, tuples, sets and dictionaries; slicing, mutability and comprehensions.
UNIT 4Files and CSV; try-except-else-finally; classes, constructors, encapsulation, inheritance and overriding.
UNIT 5Linked lists, stacks, queues, priority queues; Tkinter widgets and event handling.
PRACTICEExam-style questions with fully worked solutions.
LABEvery prescribed lab experiment, with code and expected output.