Time: 1 hr 30 mins - 2 hrs
By the end of this lesson, participants will be able to:
- 💡 Understand and explain the purpose and importance of data structures and algorithms.
- 📚 Identify and describe common data structures and their characteristics.
- 💪 Feel confident and motivated to continue exploring and learning about data structures and algorithms.
- 🎯 Apply the P.E.D.A.C. problem-solving framework to solve coding problems for CodeWars and technical interviews.
- Introduction to the Lesson and the Importance of DSA (5 minutes)
- Icebreaker Activity: Connecting DSA to Everyday Life (10 minutes)
- Introduction to Data Structures (15 minutes)
- Interactive Activity: Exploring Data Structures (15 minutes)
- Introduction to Algorithms (15 minutes)
- Interactive Activity: Analyzing Algorithms (15 minutes)
- Introduction to P.E.D.A.C. (10 minutes)
- Practice P.E.D.A.C. (15 minutes)
- Overview of Assignment: CodeTrack and Codewars (10 minutes)
- Check for Understanding (5 minutes)
(5 minutes)
💡 Coding Efficiency
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Understanding DSA enables you to optimize code efficiency by selecting appropriate data structures and implementing efficient algorithms.
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Efficient code leads to improved performance, scalability, and reduced resource consumption in real-world applications.
💼 Employers and Technical Interviews
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Employers value DSA proficiency as it demonstrates your ability to solve complex problems and write efficient code.
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Technical interviews often assess candidates' DSA knowledge to evaluate their problem-solving skills and coding efficiency.
📚 Data Structures and Algorithms
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Participants will learn about essential data structures such as arrays, linked lists, stacks, queues, trees, and graphs.
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They will understand the characteristics, operations, and use cases of each data structure.
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Participants will explore common algorithms including searching, sorting, graph traversal, and dynamic programming.
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They will gain insights into algorithmic complexity, time complexity, and space complexity analysis.
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Participants will understand the importance of efficient algorithms in optimizing code performance and solving complex problems.
(10 minutes)
Poll Question:
When organizing your clothes during room cleaning, which approach do you find most effective?
- Baskets: Sorting clothes into different baskets based on categories (e.g., shirts, pants, socks).
- Piles on Bed: Sorting clothes into separate piles on the bed based on color (e.g., all whites, all blacks, all colors).
- Type of Clothing: Sorting clothes into separate piles on the bed based on the type of clothing (e.g., shirts, pants, dresses).
- By Outfit: Organizing clothes by complete outfits, grouping together matching tops and bottoms.
(15 minutes)
♻️ Recap and Connection: Recap the importance of data structures in coding efficiency and problem-solving.
- Emphasize the relevance of the earlier polling activity and its connection to data structures.
🌎 Real-world Examples: Share practical examples of data structures in use.
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Contact List: Discuss how an array or linked list can be used to store and organize contacts in a phone or email application.
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Shopping Cart: Explain how a stack or a linked list can be utilized to maintain and manage items in a shopping cart during online shopping.
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Music Playlist: Highlight the use of a linked list or an array to create and manage a music playlist, allowing users to add, remove, or reorder songs.
📚 Key Data Structures: Introduce arrays, linked lists, stacks, and queues.
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Arrays: Explain that arrays are data structures that store a fixed-size sequence of elements of the same type.
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Linked Lists: Describe linked lists as data structures consisting of nodes, where each node holds a value and a reference to the next node.
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Stacks: Introduce stacks as data structures that follow the Last-In-First-Out (LIFO) principle, where elements are added and removed from one end.
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Queues: Define queues as data structures that follow the First-In-First-Out (FIFO) principle, where elements are added at one end and removed from the other.
(15 minutes)
Activity Details
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Encourage participants to discuss and answer the following guiding questions during their breakout room session:
- What are the main characteristics and properties of the assigned data structure?
- How does the data structure store and organize its elements?
- What are the typical operations that can be performed on this data structure?
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Facilitate group discussions, address questions or clarifications, and promote active participation.
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Bring the participants back together and allow each group to share their findings and insights about their assigned data structure.
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Facilitate a brief discussion to highlight the different data structures and their features.
(15 minutes)
♻️ Recap and Connection: Recap the importance of algorithms in problem-solving and efficient programming.
- Emphasize the relevance of algorithms in optimizing code performance and achieving desired outcomes.
🌎 Real-world Examples: Discuss everyday scenarios where algorithms are used.
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Searching Algorithms: Explore how search algorithms are used in finding information on the internet or searching for a specific item in a store.
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Sorting Algorithms: Explain how sorting algorithms can be seen in organizing items in a to-do list or arranging files in a computer directory.
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Recommendation Algorithms: Highlight the use of algorithms in suggesting movies, music, or products based on user preferences.
📚 Key Algorithms: Introduce fundamental algorithms used in problem-solving.
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Linear Search: Demonstrate how linear search is used in finding a specific element in an unordered list by checking each element one by one.
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Binary Search: Explain binary search as a more efficient algorithm for finding a specific element in a sorted list by repeatedly dividing the search space in half.
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Bubble Sort: Introduce bubble sort as a simple algorithm for arranging a list of numbers in ascending order by repeatedly swapping adjacent elements.
Zoom Poll Questions: Algorithm Identification
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Given the algorithm that repeatedly swaps adjacent elements to arrange a list of numbers in ascending order, which algorithm is this?
- A. Linear Search
- B. Binary Search
- C. Bubble Sort
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When searching for a specific element in an unordered list by checking each element one by one, which algorithm is commonly used?
- A. Linear Search
- B. Binary Search
- C. Bubble Sort
(10 minutes)
💡 Purpose of P.E.D.A.C
- Explain the purpose of P.E.D.A.C (Problem, Examples, Data Structure, Algorithm, Code) as a problem-solving framework.
- Emphasize its importance in breaking down and approaching coding problems systematically.
✏️ Overview of P.E.D.A.C Process
- Provide a high-level overview of each step in the P.E.D.A.C process:
- Problem: Understand and define the problem.
- Examples: Work through examples and gather requirements.
- Data Structure: Determine appropriate data structures to use.
- Algorithm: Design an algorithm to solve the problem.
- Code: Implement the algorithm in code.
✅ Walkthrough Example
- Choose a simple coding problem that can be easily solved using P.E.D.A.C.
- Walk through each step of the P.E.D.A.C process for the selected problem, explaining the thought process and decisions made at each stage.
Given a list of numbers, find the sum of all the numbers. Inputs: List of numbers Output: Sum of the numbers in the list Constraints: The list may contain both positive and negative numbers.
♻️ Recap and Key Takeaways
- Summarize the main points covered during the P.E.D.A.C introduction and example walkthrough.
- Emphasize the importance of practicing the P.E.D.A.C process for problem-solving in coding.
Click to Expand Details
(5 minutes)
- Explain that the participants will engage in a collective class activity to practice the P.E.D.A.C process for a coding problem.
- Emphasize that each participant will contribute their thoughts and ideas in the chat for each step of P.E.D.A.C.
Problem: Given an array of integers, write a function to find the maximum element in the array.
P.E.D.A.C Process
### 1. Problem
- Define the problem: Find the maximum element in an array of integers.
- Requirements: The function should take an array of integers as input and return the maximum element.
### 2. Examples
- Examples:
- Input: [1, 5, 3, 9, 2]
Output: 9
- Input: [-2, 0, -5, -1]
Output: 0
### 3. Data Structure
- Data Structure: No specific data structure is needed for this problem.
### 4. Algorithm
- Algorithm:
- Initialize a variable `max` to store the maximum element.
- Iterate through the array:
- If the current element is greater than `max`, update `max` with the current element.
- Return `max`.
### 5. Code
function findMax(arr) {
let max = arr[0];
for (let i = 1; i < arr.length; i++) {
if (arr[i] > max) {
max = arr[i];
}
}
return max;
}## Sharing and Discussion
- Allow participants to share their thoughts, approaches, and code snippets in the chat for each step.
- Facilitate a discussion to compare different approaches and code implementations.
- Address any questions or doubts raised by participants.
## Wrap-up
- Summarize the key takeaways from the practice activity, emphasizing the importance of using the P.E.D.A.C process for problem-solving in coding.
- Encourage participants to continue practicing P.E.D.A.C and exploring more coding problems.
(10 minutes)
Click to expand details
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Direct the participants to the CodeTrack and Codewars platforms where they will find a collection of coding problems.
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Emphasize the importance of practicing problem-solving skills and applying the concepts learned in this lesson.
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Spark the drive for participants to challenge themselves and solve as many problems as possible, just like training to improve their skills.
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Encourage participants to track their progress, set goals, and engage in the coding community to learn from others and share their solutions.
Questions
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What is the importance of learning data structures and algorithms in coding?
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Name two real-world examples where data structures are commonly used.
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Briefly explain the difference between linear search and binary search algorithms.
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What are the steps involved in the P.E.D.A.C process for problem-solving?