Algorithmic Thinking with Python KTU BTech S1 UCEST 105 2024 scheme - Dr Binu V P

Sample Classroom Exercises:  1. Identify three ill-defined problems and well-defined problems 2. Identify five use cases for Trial and error, Heuristics, backtracking, and Means-ends analysis. 3. Use a diagram to solve the Tower of Hanoi for three pegs with the minimum number of moves. 4. Evaluate different algorithms discussed earlier based on their efficiency by counting the number of steps. 5. A recursive function that takes a number and returns the sum of all the numbers from zero to that number. 6. A recursive function that takes a number as an input and returns the factorial of that number. 7. A recursive function that takes a number ‘n’ and returns the nth Fibonacci number. 8. A recursive function that takes an array of numbers as input and returns the product of all the numbers in the array. 9. A program to reverse the contents of an 1D array without using a second array. 10. To register for the end-semester examination, you need to log into the University portal with your cred

Definition of Problem-Solving Strategies: Problem-solving strategies are systematic methods or approaches used to find solutions to challenges, issues, or complex situations. These strategies guide the process of identifying the problem, exploring possible solutions, and implementing the best course of action. Description of Problem-Solving Strategies: Problem-solving strategies are essential tools that help individuals and groups approach challenges in an organized and effective manner. Different strategies are used depending on the nature of the problem, the available information, and the desired outcome. Here are some common problem-solving strategies: Trial and Error : Description : This strategy involves trying different solutions and learning from mistakes until the correct one is found. It's practical when you have no clear path to the solution and need to explore various options. Heuristics : Description : Heuristics are mental shortcuts or "rules of thumb" that

The Backtracking method is a problem-solving strategy that involves exploring possible solutions to a problem by building them incrementally, step by step. If you reach a point where the current path doesn't lead to a solution, you backtrack—go back to the previous step—and try a different path. It’s particularly useful for solving problems with multiple possible solutions or where the solution involves making a sequence of decisions. What is the Backtracking Method? Definition : Backtracking is a method where you try to solve a problem by exploring all possible options. If you find that a certain option doesn’t lead to a valid solution, you undo (or "backtrack") that choice and try the next option. Purpose : The goal is to find the correct solution by systematically exploring all possibilities, while discarding paths that don’t work. Steps in the Backtracking Method: Identify the Problem and Constraints : Clearly understand the problem and any constraints (rules or limi

The Heuristic Method is a problem-solving strategy that uses practical shortcuts or "rules of thumb" to make decisions and find solutions more quickly and efficiently, even if the solution isn’t perfect. Here’s how it works: What is the Heuristic Method? Definition : A heuristic is a mental shortcut that allows people to solve problems and make judgments quickly and efficiently. It’s a way to simplify complex problems by focusing on the most important factors or by applying general principles that usually lead to a good enough solution. Purpose : Heuristics are used when you need a fast, efficient solution and are willing to accept that it may not be the absolute best or most accurate one. Characteristics of Heuristics: Simplification : Heuristics simplify complex problems, making them easier to tackle. Speed : They provide quicker solutions by cutting down on the time and effort needed. Satisfactory Results : Heuristics aim for a "good enough" solution rather than

 LAB Experiments:  1. Simple desktop calculator using Python. Only the five basic arithmetic operators. 2. Create, concatenate, and print a string and access a sub-string from a given string. 3. Familiarize time and date in various formats (Eg. “Thu Jul 11 10:26:23 IST 2024”). 4. Write a program to create, append, and remove elements in  lists.( using Numpy array also) 5. Program to find the largest of three numbers. 6. Convert temperature values back and forth between Celsius (c), and Fahrenheit (f). [Formula: °C = (°F - 32) × 5/9] 7. Program to construct patterns of stars (*), using a nested for loop. 8. A program that prints prime numbers less than N. 9. Program to find the factorial of a number using Recursion. 10. Recursive function to add two positive numbers. 11. Recursive function to multiply two positive numbers. 12. Recursive function to find the greatest common divisor of two positive numbers. 13. A program that accepts the lengths of three sides of a triangle as inputs. The

The Trial and Error method is a straightforward and practical problem-solving strategy where you try different solutions and learn from mistakes until you find one that works. Let’s break it down: What is the Trial and Error Method? Definition : Trial and Error involves experimenting with various approaches or solutions until you achieve the desired result. If one attempt doesn’t work, you try another, learning from each failure or success along the way. Purpose : This method is used when you don’t have a clear solution in mind and need to explore different possibilities. Steps in the Trial and Error Method: Identify the Problem : Clearly understand what you’re trying to solve. Define the problem and your goal. Try a Possible Solution : Start with one approach or solution. This could be based on your intuition, past experience, or simply a guess. Test the Solution : Implement the solution and observe what happens. Does it solve the problem? Analyze the Results : If the solution works,

 Means-End Analysis is a problem-solving strategy where you break down the problem into a series of steps (means) to reach a desired outcome (end). Here’s how it works: What is Means-End Analysis? Means-End Analysis involves identifying the current state (where you are now) and the goal state (where you want to be). The key idea is to reduce the difference between these two states by applying specific actions or steps (means) that bring you closer to the goal. Steps in Means-End Analysis: Identify the Goal (End): Clearly define what you want to achieve. This is the end state you are aiming for. Assess the Current State: Understand your current position or condition relative to the goal. Identify the gap or difference between where you are and where you want to be. Identify the Differences: Determine the differences between the current state and the goal state. These differences highlight what needs to be changed or achieved to reach the goal. Select and Apply an Action (Means): Choose

The  Trial and Error  method involves trying different solutions until you find one that works. This method is especially useful when you don't have a clear path to the solution and need to experiment with various approaches. Here are some examples: 1.  Learning to Ride a Bicycle : Example : When learning to ride a bike, you might fall several times before figuring out how to balance and steer properly. Each attempt helps you learn what works and what doesn’t, leading to success. 2.  Solving a Puzzle : Example : If you’re putting together a jigsaw puzzle, you might try several pieces in a spot before finding the one that fits. You test each piece until you find the correct one. 3.  Cooking Without a Recipe : Example : If you're cooking a dish without a recipe, you might experiment with adding different amounts of spices or ingredients until you achieve the desired taste. You keep adjusting based on the results of each attempt. 4.  Finding the Right Tool : Example : When assembl

Means-End Analysis  is a problem-solving strategy that involves breaking down a problem into smaller, manageable parts (means) and addressing each part to reduce the difference between the current state and the goal state (end). Here are some examples of how this strategy can be applied: 1.  Planning a Vacation : Example : Goal : Plan a vacation to a tropical island. Means : Determine Budget : Calculate how much you can spend on the trip. Choose Destination : Research and select a suitable tropical island within your budget. Book Flights : Find and book flights to the chosen destination. Book Accommodation : Reserve a hotel or rental property on the island. Plan Activities : Decide on activities and excursions to do during the trip. 2.  Writing a Research Paper : Example : Goal : Complete a research paper on machine learning algorithms. Means : Research Topic : Gather information and review literature on machine learning algorithms. Create an Outline : Organize the main sections of the