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PYTHON PROGRAMMING 1BPLC105B

Module-wise notes, PYQs, and a built-in resource explorer — everything you need to crack 1BPLC105B in one focused page.

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Code1BPLC105B
Credits03
CIE / SEE50 / 50
TypeTheory
Exam3 Hours
Hours / Week2:2:2:0
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Last Updated:  15 March 2026

Syllabus Overview

M1

Module 1: The way of the program

The Python programming language, what is a program? What is debugging? Syntax errors, Runtime errors, Semantic errors, Experimental debugging. Variables, Expressions and Statements: Values and data types, Variables, Variable names and keywords, Statements, Evaluating expressions, Operators and operands, Type converter functions, Order of operations, Operations on strings, Input, Composition, The modulus operator. Iteration: Assignment, Updating variables, the for loop, the while statement, The Collatz 3n + 1 sequence, tables, two-dimensional tables, break statement, continue statement, paired data, Nested Loops for Nested Data. Functions: Functions with arguments and return values. Chapters: 1.1-1.7, 2.1-2.12, 3.3, 4.4, 4.5

M2

Module 2: Strings

Working with strings as single things, working with the parts of a string, Length, Traversal and the for loop, Slices, String comparison, Strings are immutable, the in and not in operators, A find function, Looping and counting, Optional parameters, The built-in find method, The split method, Cleaning up your strings, The string format method. Tuples: Tuples are used for grouping data, Tuple assignment, Tuples as return values, Composability of Data Structures. Lists: List values, accessing elements, List length, List membership, List operations, List slices, Lists are mutable, List deletion, Objects and

M3

Module 3: Dictionaries

Dictionary operations, dictionary methods, aliasing and copying. Numpy: About, Shape, Slicing, masking, Broadcasting, dtype . Files: About files, writing our first file, reading a file line -at-a-time, turning a file into a list of lines, Reading the whole file at once, working with binary files, Directories, fetching something from the Web. Chapter: 5.4, 6.1-6.5, 7.1-7.8

M4

Module 4: IPCC (4 Credits) template 2 2 Modules

Random numbers, the time module, the math module, creating your own modules, Namespaces, Scope and lookup rules, Attributes and the dot Operator, Three import statement variants. Mutable versus immutable and aliasing Object oriented programming: Classes and Objects — The Basics, Attributes, Adding methods to our class, Instances as arguments and parameters, Converting an instance to a string, Instances as return values . Chapter: 8.1-8.8, 9.1, 11.1

M5

Module 5: Object oriented programming

Objects are mutable, Sameness, Copying. Inheritance: Pure functions ,Modifiers, Generalization, Operator Overloading, Polymorphism. Exceptions: Catching Exceptions, Raising your own exceptions. Chapter: 11.2.2-11.2.4, 11.3.2-11.3.9, 12.1, 12.2

Textbooks & Resources

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Frequently Asked Questions

What is 1BPLC105B (PYTHON PROGRAMMING)?

PYTHON PROGRAMMING (1BPLC105B) is a VTU course covered through module-wise syllabus, notes, and PYQ-driven exam practice available on this page.

How many credits is 1BPLC105B?

Credits for 1BPLC105B: 04.

Are notes and previous year question papers available for 1BPLC105B?

Yes. You can access organized notes, PDFs, and PYQ material from the file explorer/resources section on this page.

How should I prepare Mathematics-I 1BPLC105B for VTU exams?

Start with module summaries, solve recent PYQs unit-wise, and finish with complete paper practice under time constraints for SEE readiness.

Is this 1BPLC105B page updated for current VTU scheme?

Yes, this page is maintained with current scheme-oriented materials and practical exam-focused resource curation.

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About Mathematics-I (1BPLC105B)

Mathematics-I (1BPLC105B) is a critical course in the VTU curriculum, essential for any student looking to master the foundations of engineering. It covers key theoretical frameworks and practical concepts that are widely used in the industry today, ensuring students are well-prepared for both exams and their future careers.

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📘 Detailed Syllabus & Topic Breakdown

Detailed Subject Overview

Mathematics-I (1BPLC105B) is designed to provide a comprehensive look into the core methodologies and advanced theories that define this field. Understanding this subject is fundamental for anyone looking to excel in modern technical domains and industrial engineering.

By studying this course, you will learn how to approach complex problems with a structured mindset, optimizing systems for better performance and reliability—skills that are highly valued in both AI research and software architecture.

Module-by-Module Breakdown

Module 1
Core

The way of the program: The Python programming language, what is a program? What is debugging? Syntax errors, Runtime errors, Semantic errors, Experimental debugging. Variables, Expressions and Statements...

Module 2
Core

Strings: Working with strings as single things, working with the parts of a string, Length, Traversal and the for loop, Slices, String comparison, Strings are immutable, the in and not in o...

Module 3
Core

Dictionaries: Dictionary operations, dictionary methods, aliasing and copying. Numpy: About, Shape, Slicing, masking, Broadcasting, dtype . Files: About files, writing our first file, reading a ...

Module 4
Core

IPCC (4 Credits) template 2 2 Modules: Random numbers, the time module, the math module, creating your own modules, Namespaces, Scope and lookup rules, Attributes and the dot Operator, Three import statement variants. M...

Module 5
Core

Object oriented programming: Objects are mutable, Sameness, Copying. Inheritance: Pure functions ,Modifiers, Generalization, Operator Overloading, Polymorphism. Exceptions: Catching Exceptions, Raising your ow...

Professional Career Relevance

This subject provides a strong foundation for various technical roles, emphasizing analytical thinking, system design, and the practical application of engineering principles in the modern industry. Mastering these concepts prepares you for high-demand roles in Data Science, System Architecture, and Technical Leadership in top-tier tech companies.

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