Programming Languages

Course objectives
1. Write, compile, and run programs in C and Python 2. Use variables, operators, and control flow to solve simple problems 3. Write and use functions; understand arrays and basic string operations 4. Get familiar with Python built-in data types 5. Apply Python to a small task in an emerging domain — data, automation, or IoT

Course content
Unit Language Topics Weightage Programming Basics (C): 1. Structure of a C program; compilation and execution 2. Data types, variables, constants, operators (arithmetic, relational, logical) 1. C 3. Input/output — scanf/printf in C 4. Type conversion; simple expressions Real connect: C powers embedded systems, microcontrollers, and OS kernels. Decision Making and Control Flow (C): 1. Control Statements 2. Loops — for, while, do-while; break and continue 2. C 3. Functions — definition, call, return; call by value 4. Recursion — factorial and Fibonacci (simple examples only) Real connect: Control flow is the brain of every program — from traffic signal logic to drone autopilot decision-making. Advanced Programming Concepts (C): 1. 1D array — declaration, input, output, traversal 2. Simple operations — find max, min, sum, average 3. Strings in C — gets/puts, strlen, strcpy, strcmp 4. Pointer — concept of address and pointer 3. C variable (concept only, not deep) 5. Structures, 6. File Handling Real connect: Arrays store sensor readings, image pixels, and stock prices. Pointers are the foundation of memory management in embedded systems. Python Introduction: 1. Why Python — where it is used (AI, Data Science, Web, Automation) 2. Python basics — variables, data types, print, input, operators 3. Python control flow — if/else, for loop, 4. Python while loop 4. Python functions — def, return, default arguments Real connect: Python is #1 in AI/ML, Data Science, and automation — same syntax, more power, less boilerplate. Python Data Structures and Emerging Applications 1. Python list, tuple, dictionary, set — basic operations only 2. File handling — read and write a text file; read a CSV (2–3 lines) 5. Python 3. Introduction to NumPy — array, mean, simple arithmetic (5 lines) 4. Introduction to Matplotlib — plot a simple line graph (5 lines) 5. One mini-demo — IoT sensor simulation Real connect: Python lists power NumPy which powers TensorFlow. Matplotlib plots are used in every engineering report and data science notebook. This unit opens the door to AI, IoT, and Data Science using the same Python basics learnt in Unit IV. Tutorial Hour — Week-by-Week Practice Problems One tutorial hour per week. Students write and run programs. Problems below are the minimum set — teacher may add variants. Week Language Tutorial Problems 1. Print your name and branch. 2. Add two numbers 1 C entered by user. 3. Find area of a rectangle. 1. Swap two numbers. 2. Check if a number is even or odd. 2 C 3. Simple calculator (+, –, ×, ÷) using if-else. 1. Find the largest of three numbers. 2. Grade calculator 3 C (marks → A/B/C/D/F). 3. Day name using switch-case. 1. Print multiplication table of N. 2. Sum of first N natural 4 C numbers using loop. 3. Count digits in a number. 1. Print prime numbers from 1 to 50. 2. Fibonacci series 5 C (first 10 terms). 3. Reverse a number. 1. Factorial using function. 2. Check palindrome number 6 C using function. 3. Find GCD of two numbers. 1. Recursive factorial. 2. Recursive Fibonacci. 3. Sum of 7 C digits using recursion. 1. Input array of N numbers; find max and min. 2. 8 C Compute average of array. 3. Linear search in array. 1. Count vowels in a string. 2. Reverse a string. 3. Check 9 C if string is palindrome. 1. Write a C program to store 5 numbers in an array and print them in reverse order. 2. Write a C program to 10 C perform basic string operations such as finding string length, copying and concatenation. 1. Hello World in Python. 2. BMI calculator. 3. 11 Python Temperature converter (°C ↔ °F). Compare C vs Python syntax. 1. Grade calculator in Python. 2. Fibonacci using Python 12 Python loop. 3. Simple calculator using functions in Python. 1. List: marks of 5 students — max, min, average. 2. 13 Python Dictionary: store name and marks of 3 students. 3. Count word frequency in a sentence. 1. Write student records to a text file. 2. Read and display 14 Python the file. 3. Read a small CSV and print rows. 1. NumPy: create array, compute mean. 2. Matplotlib: plot 15 Python a line graph of marks. 3. Mini-demo: simulate 5 IoT temperature readings and plot.