Welcome to the channel if you are new to the world of data structures and algorithms! C949 Data Structures and Algorithms I is one of the foundation courses at WGU for anyone aspiring to be a software developer or computer scientist. This course is aimed at explaining to you the key notions that are necessary for creating effective and easily scalable applications.
C949 is quite a popular course, in this article, I am going to review every aspect that will enable you to pass that course. This post will give an overview of what to expect from this module, a detailed guide on how to succeed in the OA (Objective Assessment), and some great links to what we like to refer to as ‘The Fun Stuff’ that will ensure your learning of these concepts is as easy as possible. We will also divide according to the various areas of concentration that you should apply in your preparation to be able to handle the most contentious areas of the course appropriately. Last of all, coming to the next and final segment, let us dispel any uncertainty you might still harbor as we pose and collectively address some common questions.
Ready to tackle C949? Let’s get started on this journey to mastering data structures and algorithms!
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What to expect from the module C949📖
The C949: Data Structures and Algorithms I course is an intensive look at systems such as dynamic data structures and the algorithms behind them. The modules you will learn include generic programming basics and components of efficient software development where you will learn about bags, lists, Stacks, Queues, Trees, Hash Tables, and Graphs.
The material of this course is based on the principles of object-oriented design and abstract data types – the two key characteristics of modern programming. Not only will you be taught these concepts, but they will be put to use in simple problems so that at least you can have some practical experience in those ideas when you start your job.
Here’s a breakdown of what the course covers:
- Introduction to Data Structures & Algorithms: You will be beginning with fundamentals on which subsequent tactics sought to be constructed will rest.
- Lists, Stacks, and Queues: These are perhaps one of the most basic structures of data. The primary focus lies in comprehending when to twist, bend, and deploy these conceptualizations in an efficient way, as these discourses are certain to feature in your tests.
- Hash Tables and Trees: Hash tables perform search/insertion in constant time, trees of different types and forms, balanced trees, heaps, etc. are used to understand hierarchal data and better performance data structures.
- Advanced Data Structures: You’ll delve into more specialized structures like sets, graphs, and B-trees. These are crucial for tackling complex problems, particularly those involving networks or database indexing.
- Algorithm Analysis: A significant part of this course is understanding how to analyze algorithms for efficiency. This includes concepts like time complexity, which will help you determine the most efficient approach to solving problems.
- Introduction to Python: Therefore, Python programming language is used all throughout this course. You will be fine with simple Python programming such as variables, expressions, data types, and also loops and functions among other control structures.
By the end of this course, you’ll have a solid foundation in both the theory and practice of data structures and algorithms. This knowledge is not only critical for passing the course but also for succeeding in the field of software development. The topics covered will challenge you to think critically and solve problems efficiently, preparing you for more advanced coursework and real-world applications.
Study Guide to Pass the WGU C949 OA📝
It is a disciplined course and therefore planning and organization are important success factors for Data Structures and Algorithms I (C949). The following guide provides detailed weekly schedules of what to learn and do in order to excel in the OA, abbreviated from Objective Assessment.
Week 1: Read the Textbook
It is imperative that to start your learning in this course you acquire the textbook as it’s the foundation of learning here. Let us first install Python 3 and PyCharm IDE which will be the means by which the concepts they come across will be implemented. While you go through the chapters ensure you undertake all the quizzes as well as try all the labs that are offered. Such activities will assist in the reinforcement of the material and provide practical experience with the forms.
Action Steps:
- Install Python 3 and PyCharm IDE.
- Begin reading the textbook, chapter by chapter.
- Complete all quizzes and labs as you go. These are not optional—they’re essential for understanding the material.
Location (Textbook) – Log onto the Student Portal of WGU > Go to the module C949 > Click on “Go to Course Materials”
Week 2: Watch the Recorded Cohorts
In the second week, focus on watching the recorded cohorts. These video sessions are invaluable because they provide insights and explanations that might not be fully covered in the textbook. The instructors often share tips and tricks that can help you grasp complex topics more easily.
Action Steps:
- Schedule time each day to watch the recorded cohorts.
- Take notes as you watch, especially on topics you find challenging.
- Review the sections of the textbook that correspond with the cohort material to reinforce your understanding.
Location (Recorded Cohorts) – Log onto the Student Portal of WGU > Go to the module C949 > Click on “Course Search” > Open “C949 Youngblood Cohorts”
Week 3: Read the Supplemental Material
I would like to continue the main thing to focus on – learning the content of the lessons in more detail this week. The Study Guide and the Terms and Definitions are two side materials that are meant to be used while reading the textbooks. They give more information from which comprehension increases and contain clarification of concepts which are hard to grasp.
Action Steps:
- Read through the Study Guide carefully.
- Review the Terms and Definitions, ensuring you understand each concept.
- Revisit any textbook chapters where you feel uncertain, using these supplemental materials to clarify your doubts.
Location (Study Guide Document) – Log onto the Student Portal of WGU > Go to the module C949 > Click on “Course Search” > Open “C949 v3 Study Guide”
Location (Terms and Definitions)– Log onto the Student Portal of WGU > Go to the module C949 > Click on “Course Search” > Open “C949 Combined Terms List.pdf”
Week 4: Do the Pre-Assessment (Pre-A)
About the time you are done preparing it is important to gauge your preparedness level. The Pre-A is one of the full-length paper-based practice tests that simulate the actual OA. From this assessment, you shall be able to know which of these areas you need to revise deeply.
Action Steps:
- Set aside uninterrupted time to complete the Pre-A.
- Review your results, focusing on any sections where you scored lower.
- Revisit the relevant textbook chapters, cohorts, and supplemental materials to strengthen your understanding in those areas.
Week 5: Do the Objective Assessment (OA)
At the end of the week, it is time to take the OA after having revised all the necessary material and having worked on the weak spots. This is where all your work begins to pay off, or where it all goes wrong Either way, it is the very essence of what the competition needs.
Action Steps:
- Ensure you’re well-rested and prepared on the day of the OA.
- Review your notes and key concepts one last time.
- Take the OA with confidence, knowing that you’ve followed a comprehensive study plan.
The following is a week-by-week breakdown of what you need to do; this way, there will be no chance of missing anything important by accident. C949 will be as good as won if you stay true to the schedule!
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Key Topics to Focus On👨🏻🏫
In Data Structures and Algorithms I (C949), there are a few key topics that you’ll need to master to excel in this course. These concepts are not only foundational to the subject but are also heavily tested in the OA. Here’s a breakdown of the four crucial areas you should focus on, along with explanations and comparisons to help you understand them better.
- Pop(), Push(), Remove(), Enumerate(), Enqueue, Dequeue
These are fundamental operations associated with different data structures. Understanding how each of these works and where they are applied is essential for mastering the course.
| Operation | Data Structure | Function | Real-World Example |
|---|---|---|---|
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Pop()
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Stack
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Removes the last element (LIFO)
|
Undo operation in the text editor
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Push()
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Stack
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Adds an element to the end
|
Adding items to a to-do list
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|
Remove()
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List
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Deletes a specified element
|
Removing an item from a shopping cart
|
|
Enumerate()
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List
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Iterates over elements with an index
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Numbering items in a list
|
|
Enqueue
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Queue
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Adds an element to the end (FIFO)
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Lining up for a queue in a bank
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|
Dequeue
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Queue
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Removes the first element
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Serving the first person in a queue
|
These operations are the building blocks of manipulating data in different structures. For example, Pop() and Push() are core to stack operations, which follow a Last In, First Out (LIFO) principle. Meanwhile, Enqueue and Dequeue are used in queues, following the First In, First Out (FIFO) principle, making them ideal for scenarios like task scheduling.
- Big O Notation
Big O Notation is a mathematical concept used to describe the efficiency of an algorithm in terms of time and space complexity. It’s a way to quantify how the performance of an algorithm scales with the size of the input data.
| Big O Notation | Description | Example |
|---|---|---|
|
O(1)
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Constant time complexity
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Accessing an element in an array
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|
O(n)
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Linear time complexity
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Traversing a list
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O(log n)
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Logarithmic time complexity
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Binary search
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|
O(n log n)
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Linearithmic time complexity
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Merge sort
|
|
O(n^2)
|
Quadratic time complexity
|
Bubble sort
|
Understanding Big O Notation is crucial because it allows you to evaluate the efficiency of different algorithms. For instance, an algorithm with O(1) complexity is incredibly efficient, as its performance remains constant regardless of the input size. On the other hand, O(n^2) represents a much less efficient algorithm, where performance degrades significantly as the input size grows.
- Sorting Algorithms (Merge, Insertion, Selection, Bubble, Heap)
Sorting algorithms are essential for organizing data in a particular order, and different algorithms have their own strengths and weaknesses depending on the situation.
| Algorithm | Best Case | Worst Case | Average Case | Stable? | In-Place? | Use Case |
|---|---|---|---|---|---|---|
|
Merge Sort
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O(n log n)
|
O(n log n)
|
O(n log n)
|
Yes
|
No
|
Large datasets where stability is important
|
|
Insertion Sort
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O(n)
|
O(n^2)
|
O(n^2)
|
Yes
|
Yes
|
Small or nearly sorted datasets
|
|
Selection Sort
|
O(n^2)
|
O(n^2)
|
O(n^2)
|
No
|
Yes
|
Simple but inefficient for large datasets
|
|
Bubble Sort
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O(n)
|
O(n^2)
|
O(n^2)
|
Yes
|
Yes
|
Educational purposes, rarely used in practice
|
|
Heap Sort
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O(n log n)
|
O(n log n)
|
O(n log n)
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No
|
Yes
|
Situations where in-place sorting is required |
All the sorting algorithms have properties that are different from one another. For instance, the Merge Sort has good time complexity and is stable and therefore appropriate for large data sets while Insertion Sort which is also stable performs well on small or nearly sorted data sets. By knowing the differences of each sorting algorithm, the person will be able to select the right one for the given problem.
- Hash Tables and How Hashing Works
Hash tables are a critical data structure used for fast data retrieval. The concept of hashing involves converting a key into an index in an array, making it possible to access data in constant time.
| Concept | Explanation |
|---|---|
|
Hash Function
|
A function that converts a key into a unique index in an array.
|
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Collision
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When two keys hash to the same index, causing a conflict in the hash table.
|
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Chaining
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A method of handling collisions by storing multiple elements at the same index.
|
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Open Addressing
|
A collision resolution strategy where the next available index is used.
|
It is worth underlining that hash tables are efficient for tasks that imply quick access to some elements, for example, for a dictionary or database. The use of the hash table, in as much as its efficiency, mainly depends entirely on an efficient algorithm known as the hash function to avoid congestion or collisions. Learning when and how to use hash tables, and how to prod them into higher levels of efficiency, is vital to building great apps.
These key topics form the backbone of your understanding in Data Structures and Algorithms I. Mastering them will not only help you pass the OA but also set you up for success in your future studies and career in software development.
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External Resources to Study 📂
YouTube Channels and Playlists
Bro Code on YouTube – Learn Data Structures and Algorithms
- Although this video series uses Java, it’s an excellent resource for understanding the fundamental concepts of data structures and algorithms. The explanations are clear, and the examples are practical, making it easier to transfer the knowledge to Python.
Michael Sambol on YouTube – Short Videos on Data Structures
- This playlist offers concise videos that cover key data structures. The short format makes it perfect for quick reviews or revisiting specific topics you’re struggling with.
Caleb Curry on YouTube – Data Structures and Algorithms Playlist
- Caleb Curry’s playlist is a comprehensive guide to data structures and algorithms. The series is well-organized and easy to follow, making it a great companion to your coursework.
Supplemental Reading
Lucidchart – Data Flow Diagram Tutorial
- While not directly related to data structures, understanding data flow diagrams is crucial for grasping how data moves through systems. This tutorial provides examples, symbols, types, and tips for creating effective data flow diagrams.
Quizlet Flashcards
Flashcards are a fantastic way to reinforce your understanding of key concepts and terminology. Below are some Quizlet sets specifically tailored for the C949 course:
- WGU C949 Data Structures and Algorithms Flash Cards
- C949 Data Structures and Algorithms Preassessment Flash Cards
- WGU C949 Study Guide Flash Cards
- C949 WGU Terminology Flash Cards
These Quizlet sets include definitions, multiple-choice questions, and pre-assessment review cards that can help you prepare for the OA. They’re particularly useful for reinforcing your memory and ensuring that you’re familiar with the course’s critical concepts and terminology.
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WGU C949 FAQ❓
- How difficult is the C949 course?
- It can be challenging, especially if you’re new to programming. Staying consistent with your study plan and using all resources will help.
- What programming language is used?
- Python is the main language used in C949.
- How important is Big O Notation?
- Very important. It’s crucial for analyzing the efficiency of algorithms and will be tested on the OA.
- What are the most tested topics on the OA?
- Sorting algorithms, data structure operations, and implementing structures like hash tables and trees.
- How can I best prepare for the OA?
- Follow the study plan, take the Pre-A seriously, and use external resources for reinforcement.
- How can I get help if I’m stuck?
- Use discussion forums, live cohorts, supplemental materials, and external resources like YouTube and Quizlet.
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Conclusion📄
Compulsory subject Mastering Data Structures and Algorithms I (C949), is a milestone that will give you a great start towards your future coursework and employment within the software development field. The following guide can help you plan your study, effectively use the abundant outside resources, and memorize the key points so that you can prepare well for the OA and learn the course content thoroughly.
Remember, consistency is key. Regularly review the material, practice what you’ve learned, and don’t hesitate to seek help if needed. With the right approach, passing C949 is well within your reach. Good luck, and happy studying!
