CF

Crash Course: Beginner Data Structures And Algorithms Concepts

9h 58m 43s
English
Paid

Are endless and exhausting preparations for LeetCode wearing you down? Many people face difficulties when studying data structures and algorithms (DSA) because they begin by trying to solve problems without the necessary foundational knowledge. This approach often turns interview preparation into a torturous process.

Build a Strong Foundation in DSA

If you aim to land your dream job, it’s crucial to learn correctly: build knowledge step by step to effectively apply it in practice during technical interviews.

About the Course

In this express course, we will help you develop a comprehensive understanding of data structures and algorithms, ensuring that no important concepts are missed. You will master key patterns and concepts that are essential for solving the most commonly encountered interview tasks.

Course Outcomes

By the end of the course, you will be equipped to:

  • Solve interview tasks involving hash tables, linked lists, binary trees, graphs, and dynamic programming.
  • Analyze algorithms using Big-O notation to find optimal solutions.
  • Visualize and understand basic algorithmic concepts to apply them to new problems.

Course Designed for Beginners

This course is tailored for beginners and does not require any prior knowledge in DSA. We start with fundamental concepts and gradually increase the complexity. This approach ensures that you will truly master the material.

Reach Your Career Goals

Upon completing this course, you will acquire all the necessary skills to confidently tackle technical interviews and secure your dream job in the tech industry.

About the Author: Alvin Zablan

Alvin Zablan thumbnail

Alvin Zablan is a US developer and educator focused on practical front-end development and the algorithm / data-structure interview prep that gates entry into well-paying engineering roles. He runs Structy, an interview-prep platform, alongside his independent React tutorial work.

His CourseFlix listing carries two Alvin Zablan courses: React Formula — Learn Frontend Development and Crash Course — Beginner Data Structures And Algorithms Concepts. Material is paid and aimed at developers learning React or preparing for technical interviews.

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#1: Course Welcome
All Course Lessons (87)
#Lesson TitleDurationAccess
1
Course Welcome Demo
03:18
2
Max Value Approach
03:58
3
Max Value Walkthrough
02:09
4
Is Prime Approach
07:41
5
Is Prime Walkthrough
07:14
6
Big-O Basics Lecture
13:49
7
Big-O Examples Lecture
12:09
8
Anagrams Approach
04:04
9
Anagrams Walkthrough
05:20
10
Most Frequent Char Approach
03:50
11
Most Frequent Char Walkthrough
05:50
12
Pair Sum Approach
06:10
13
Pair Sum Walkthrough
06:00
14
Pair Product Approach
03:51
15
Pair Product Walkthrough
02:39
16
Intersection Approach
07:01
17
Intersection Walkthrough
08:47
18
Recursion Intro Lecture
04:31
19
Recursion Warm Up Lecture
09:04
20
Sum Numbers Recursive Approach
12:32
21
Sum Numbers Recursive Walkthrough
05:14
22
Linked List Intro Lecture
10:12
23
Linked List Warm Up Lecture
08:07
24
Linked List Values Approach
03:11
25
Linked List Values Walkthrough
04:20
26
Sum List Approach
03:56
27
Sum List Walkthrough
03:52
28
Linked List Find Approach
05:06
29
Linked List Find Walkthrough
04:27
30
Get Node Value Approach
03:17
31
Get Node Value Walkthrough
04:12
32
Reverse List Approach
03:46
33
Reverse List Walkthrough
06:20
34
Zipper Lists Approach
06:12
35
Zipper Lists Walkthrough
10:29
36
Want To Learn More DSA With Alvin?
00:40
37
Binary Tree Intro Lecture
10:21
38
Binary Tree Warm Up Lecture
03:10
39
Depth First Values Approach
06:37
40
Depth First Values Walkthrough
12:59
41
Breadth First Values Approach
05:58
42
Breadth First Values Walkthrough
08:02
43
Tree Sum Approach
06:40
44
Tree Sum Walkthrough
05:26
45
Tree Includes Approach
09:15
46
Tree Includes Walkthrough
08:24
47
Tree Min Value Approach
05:41
48
Tree Min Value Walkthrough
06:42
49
Max Root to Leaf Path Sum Approach
08:53
50
Max Root to Leaf Path Sum Walkthrough
05:01
51
Graph Intro Lecture
14:47
52
Graph Warm Up Lecture
15:30
53
Has Path Approach
05:48
54
Has Path Walkthrough
06:15
55
Undirected Path Approach
08:39
56
Undirected Path Walkthrough
07:48
57
Connected Components Count Approach
04:51
58
Connected Components Count Walkthrough
06:02
59
Largest Component Approach
04:56
60
Largest Component Walkthrough
06:06
61
Shortest Path Approach
07:24
62
Shortest Path Walkthrough
09:14
63
Island Count Approach
06:09
64
Island Count Walkthrough
09:55
65
Minimum Island Approach
04:16
66
Minimum Island Walkthrough
08:43
67
Fibonacci Approach
23:07
68
Fibonacci Walkthrough
06:14
69
Tribonacci Approach
07:02
70
Tribonacci Walkthrough
04:15
71
Sum Possible Approach
08:31
72
Sum Possible Walkthrough
08:26
73
Minimum Change Approach
08:59
74
Minimum Change Walkthrough
08:30
75
Count Paths Approach
07:51
76
Counts Paths Walkthrough
07:20
77
Max Path Sum Approach
06:16
78
Max Path Sum Walkthrough
05:35
79
Non Adjacent Sum Approach
08:34
80
Non Adjacent Sum Walkthrough
08:01
81
Summing Squares Approach
06:23
82
Summing Squares Walkthrough
05:53
83
Counting Change Approach
06:27
84
Counting Change Walkthrough
06:32
85
Array Stepper Approach
05:40
86
Array Stepper Walkthrough
05:28
87
Outro
00:49
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Frequently asked questions

What prerequisites are required for this course?
This course is designed for beginners and does not require any prior knowledge in data structures and algorithms. The course starts with fundamental concepts and gradually increases in complexity to ensure a solid understanding of the material.
What kinds of projects or exercises will I work on in this course?
Throughout the course, students will engage in a variety of practical exercises such as solving problems involving hash tables, linked lists, binary trees, graphs, and dynamic programming. These exercises are designed to reinforce the key patterns and concepts necessary for technical interviews.
Who is the target audience for this course?
The course is aimed at beginners who are looking to build a strong foundation in data structures and algorithms. It is particularly suited for individuals preparing for technical interviews who want to master key algorithmic concepts and patterns effectively.
How does this course compare in depth and scope to similar courses?
Unlike some courses that may dive into more advanced topics immediately, this course focuses on building foundational knowledge. It covers essential concepts like Big-O notation, recursion, and data structures such as linked lists and binary trees, ensuring that all necessary topics for solving common interview problems are thoroughly understood.
What specific tools or platforms will I learn to use?
The course does not focus on specific tools or platforms but rather on theoretical concepts and problem-solving skills. Students will learn to analyze algorithms using Big-O notation and apply algorithmic techniques to solve problems during technical interviews.
What topics are not covered in this course?
This course does not cover advanced data structures and algorithms such as AVL trees, red-black trees, or advanced graph algorithms. It is focused on building a strong foundation in the most commonly encountered problems and concepts in technical interviews.
How much time should I expect to commit to this course?
The course consists of 87 lessons. While the total runtime is not specified, students should allocate sufficient time to go through the lessons and practice the exercises, ensuring a comprehensive understanding of the material. The time commitment will vary based on individual learning pace.