Enhance your JavaScript and React skills, build a portfolio project, and understand the pathfinding algorithms on a deeper level in this project-based course!
Master the Pathfinding Algorithms with JavaScript and React
2h 30m 4s
English
Paid
Master the Pathfinding Algorithms with JavaScript and React is a 23-lesson 2 hours 30 minutes self-paced course by Zero To Mastery. Enhance your JavaScript and React skills, build a portfolio project, and understand the pathfinding algorithms on a deeper level in this project-based course!
Course facts
- Lessons
- 23
- Duration
- 2 hours 30 minutes
- Level
- All levels
- Language
- English
- Updated
- Instructor
- Zero To Mastery
- Price
- Premium
Build an Algorithms Visualizer that shows how the Breadth-First Search and Depth-First Search algorithms work and helps you understand them on a deeper level. Plus it'll serve as a standout project in your portfolio that will be a conversation starter in interviews!
Additional
Who teaches Master the Pathfinding Algorithms with JavaScript and React? Zero To Mastery
Zero To Mastery (ZTM) is a Toronto-based online coding academy founded by Andrei Neagoie, originally a senior developer at large Canadian tech firms before turning to teaching full-time. The academy's signature is the cohort-based bootcamp track combined with a deep self-paced course library, all aimed at career-changers and self-taught developers preparing to land software-engineering roles at top companies.
The instructor roster has grown well beyond Andrei to include other senior practitioners: Daniel Bourke (machine learning), Aleksa Tešić (DevOps), Jacinto Wong, and others. Courses cover the full software-engineering career path: web development with React and Next.js, Python, machine learning and deep learning, DevOps and cloud, system design, mobile, and the algorithm / data-structure interview prep that gates engineering jobs.
The CourseFlix listing under this source carries over 120 ZTM courses spanning that full range. Material is paid; ZTM itself runs on a monthly / annual membership model. The teaching style favours long-form, project-based courses where students build complete portfolio-quality applications rather than disconnected feature tutorials.
What lessons are included in Master the Pathfinding Algorithms with JavaScript and React?
0:00
/ #1: Introduction
All Course Lessons (23)
| # | Lesson Title | Duration | Access |
|---|---|---|---|
| 1 | Introduction Demo | 02:29 | |
| 2 | Project Demo | 03:28 | |
| 3 | What Are Pathfinding Algorithms? | 05:28 | |
| 4 | Breadth-First Search (BFS) | 06:41 | |
| 5 | Depth-First Search (DFS) | 05:33 | |
| 6 | BFS vs. DFS | 02:49 | |
| 7 | Setting Up Our REPL | 06:08 | |
| 8 | Creating a Maze Using React | 10:36 | |
| 9 | Creating Maze Rows | 03:42 | |
| 10 | Making It Dynamic | 09:07 | |
| 11 | Adding a Maze Refresh Button | 08:35 | |
| 12 | Generating a Maze Matrix using Javascript | 05:03 | |
| 13 | Combining Maze Generation into Our Button | 05:09 | |
| 14 | Finalizing Our Maze Generation | 12:34 | |
| 15 | Applying BFS and DFS to Our Maze | 05:10 | |
| 16 | Breadth-First Search Implementation - Part 1 | 12:27 | |
| 17 | Breadth-First Search Implementation - Part 2 | 03:36 | |
| 18 | Depth-First Search Implementation | 05:36 | |
| 19 | Adding Buttons and Bug Fixing our Algorithms | 10:41 | |
| 20 | Combining the Algorithms to the Maze | 09:04 | |
| 21 | Delaying the Steps of Our Algorithms | 03:52 | |
| 22 | Fixing Refresh Maze | 06:30 | |
| 23 | The Final Touches | 05:46 |
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Frequently asked questions
What are the prerequisites for enrolling in this course?
Prospective students should have a foundational understanding of JavaScript and basic knowledge of React. Familiarity with these technologies is important as the course involves implementing pathfinding algorithms in a React environment. Students are expected to be comfortable with JavaScript syntax and basic React component structure.
What will I build during this course?
During the course, you will build a maze application using React where you can apply and visualize pathfinding algorithms such as Breadth-First Search (BFS) and Depth-First Search (DFS). The project includes dynamic maze creation, adding functionality to refresh the maze, and implementing algorithm visualization as part of the learning experience.
Who is the target audience for this course?
This course is designed for JavaScript developers looking to enhance their skills by learning pathfinding algorithms and integrating them into a React project. It is particularly suitable for those interested in algorithm visualization, expanding their portfolio with a hands-on project, or preparing for technical interviews that require algorithmic understanding.
How does the depth and scope of this course compare to similar courses?
This course provides a practical approach to understanding and implementing pathfinding algorithms like BFS and DFS within a React application. Unlike theoretical courses, this course emphasizes hands-on experience with project-based learning, allowing students to apply algorithms in real-time applications, which can be more engaging for learners who want to see immediate results.
Does the course cover any specific tools or platforms?
Yes, the course specifically uses JavaScript and React to build and visualize pathfinding algorithms. Students will set up a REPL environment for testing and development purposes. Additionally, the course includes lessons on creating interactive elements such as buttons to manage maze generation and algorithm execution.
What topics or areas are not covered in this course?
The course does not cover advanced pathfinding algorithms beyond Breadth-First Search and Depth-First Search, nor does it delve into non-JavaScript implementations. It also does not include topics related to React beyond the scope of the maze application project, such as state management libraries like Redux or advanced React patterns.
What is the expected time commitment for completing this course?
The course consists of 23 lessons and is project-based, so the time commitment may vary based on individual pace. Students should allocate time for both the instructional content and hands-on exercises, including maze creation and algorithm implementation. A focused learner might complete the course in a few weeks by dedicating several hours per week.