Algorithmic Interview Seminar (Java Version)
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This course does not talk about the basic knowledge of algorithm, specializing in algorithm problem solving. The lecturer, as a question maker for many algorithms and related websites, has many years of experience in question setting and interview. He will comprehensively classify and sort out the mainstream and classic interview questions of Dachai, leading you to master efficient problem-solving ideas and get rid of the questions. It only takes 20 hours to complete interview preparation.
Q: What are the basics of the course and what languages are used
Dear, the language is Java, learning this course requires you to master the basic knowledge of algorithms and data structures, the whole course explains algorithm problem solving, practice oriented. Enjoy your study
Q: What is the difference between this course and the previous algorithm course and system course?
Dear, this course does not focus on explaining basic knowledge, but on solving problems and putting algorithm thinking into practice. The content of the course also brings together frequently tested algorithm questions and the teacher’s own questions, so as to do the problems of high quality and try to understand a class of problems, rather than just do one. Therefore, learning this course requires you to master the basic algorithm and data structure foundation first, and learning sequence requires you to master The algorithm system class of Teacher Bobo first. Enjoy your study
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Chapter Contents:
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Chapter 1 Algorithm problem solving – Course introduction and Trial
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Course Description: this course does not cover the basic knowledge of algorithms, but focuses on algorithm problem solving. Comprehensive classification of the mainstream classic interview questions, take you to master efficient problem-solving ideas, get rid of the tactics of the sea of questions, so that you can master the algorithm interview system in a short time, in-depth understanding of the algorithm design ideas through multi-question practice algorithm ideas into practice.
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There are two sections (19 minutes)
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1-1 Algorithm Interview seminar (Java Version) – Course Guide (18:43) Trial
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1-2 Course guide – illustrated teaching AIDS
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Chapter 2 Algorithms are not hard. Algorithms are fun
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All things are difficult before they are easy. When it comes to computer algorithms, many students may think it is mysterious, difficult and mathematical. In fact, the algorithm comes from life, which can be vividly understood as the specific process of doing one thing in our daily life. In this chapter, we set up the impression that “algorithms are not difficult to learn” and cultivate the interest in learning algorithms through practical examples. .
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A total of 2 periods (16 minutes)
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2-1 Interesting and Simple Algorithm Problems (15:21)
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2-2 Interesting and simple questions – Text and text analysis
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Chapter 3 mathematical problems: Classical mathematical algorithms
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This chapter uses common mathematical algorithms to help you understand common mathematical algorithm-related questions in interviews and written tests.
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There are 8 sessions (95 minutes)
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Maximum Common Divisor Algorithm (24:20)
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3-2 Maximum Common Divisor algorithm – Graphic analysis
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3-3 Fast Modular Exponentiation Algorithm (19:08)
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3-4 fast modular power algorithm – graphic analysis
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3-5 Combinatorial Counting Algorithm (27:01)
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3-6 Combination counting – Graphic analysis
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Probability correlation Algorithm (24:26)
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3-8 probability problems – Text and text analysis
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Chapter 4 arrays related issues
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Arrays are by far the most familiar data structure, and we don’t even think of them as a data structure — since almost every programming language has array types built in, we tend to use them unconsciously. Although its structure is simple, we can not look down on it, involving the array of topics is a kaleidoscope, emerge in endlessly. However, we will use typical examples to help you understand the solution of array problems. .
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There are 11 sessions (122 minutes)
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4-1 Arrays as Storage units (15:46)
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4-2 array as storage unit – Graphic parsing
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4-3 Dutch Flag Question (10:47)
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4-4 arrays as special maps (17:26)
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4-5 Solving the widest Empty Rectangular Region by Bucket Principle (17:32)
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4-6 arrays – as special maps – graphic parsing
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4-7 Double Pointers in Arrays (23:47)
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4-8 array – double pointer – text parsing
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4-9 Array Sliding Window (20:55)
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4-10 Replacing substrings makes string balancing a problem (15:33)
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4-11 array – Sliding window – Text parsing
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Chapter 5 issues related to linked lists
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Linked lists are the cousin of arrays, and they don’t get a lot of questions in written interviews — they’re also simpler data structures. Like arrays, we probably don’t usually think of linked lists as data structures. Until then we also can not despise it, related to the list of topics are not too difficult, but more cumbersome, we will talk about the list in this chapter and you the most basic add, delete, check, change and other operations. .
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A total of 12 sections (129 minutes) fold up the list
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5-1 Familiar with the most basic linked list operations (09:20)
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5-2 Linked lists – Basic operations – Graphic analysis
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5-3 Delete continuous nodes with sum = 0 (16:55)
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5-4 List lazy Deletion (13:49)
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5-5 lazy deletion of linked lists – Illustrated
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5-6 List Flipping (21:44)
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5-7 Flip list – graphic analysis
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List Sliding Window 1 (18:12)
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5-9 Linked list slide window 1- Graphic analysis
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5-10 Sliding Windows for Linked Lists 2 (19:57)
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5-11 Linked list sliding window 2- Graphic parsing
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5-12 Linked List Replication (28:54)
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Chapter 6. Stack-related issues
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A stack is a simple data structure. When we wash dishes in daily life, we stack them together, which is the embodiment of a natural stack. The stack in a computer is an abstraction of these everyday examples, and in this chapter we will summarize and explore stack-related issues.
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A total of 8 sessions (93 minutes)
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6-1 Basic Stack Implementation and Application (22:37)
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6-2 Basic stack operations – Graphic parsing
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6-3 Heap Implementation of recursive problems — Implicit stack (18:44)
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6-4 Recursive and implicit stack – Graphic parsing
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6-5 Binary Tree traversal and stack (21:33)
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6-6 Binary tree traversal and stack – Graphic parsing
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6-7 Monotone Stack and Applications (30:00)
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6-8 Monotone Stack – Graphic parsing & Jobs
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Chapter 7 queue-related issues
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The queue is a first-in, first-out structure. Queues are the abstraction of queues in daily life. In this chapter we have used examples to understand and understand queues and to learn the application of explicit and implicit queues
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There are 12 sessions (135 minutes)
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7-1 Application and Implementation of Simple Queue (24:13)
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7-2 Application and Implementation of simple queue – Text and text parsing & Jobs
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7-3 Implementation of a double-endian queue (21:12)
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7-4 Example of a double-ended queue – Graphic parsing & Jobs
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7-5 Implementation of ring Queue (20:09)
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7-6 Examples of loop/ring queues – Graphic parsing & Jobs
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7-7 Two queue simulation stacks and two stack simulation queues (23:27)
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Stack and queue simulation to each other – Graphic parsing & Jobs
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Applications of monotonic Queues (25:08)
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7-10 Monotonic Queue – Text parsing & Jobs
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A case of BFS (20:47)
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7-12 BFS example – Text and text analysis & homework
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Chapter 8 special case of divide-and-conquer — binary search
Binary search is a common and important algorithm in computer science. It is based on the idea that it is easier to determine whether a given candidate solution is a real solution to a problem than to find a real solution to the problem. So computers are not so high and powerful. We need to believe that if we don’t know the solution to a problem, computers usually don’t either. So we help the computer “guess” a solution, and then determine whether the solution fits to adjust our thinking. .
There are 8 sessions (76 minutes)
Introduction to 8-1 binary Algorithm (21:54)
8-2 binary search algorithm – Text and text parsing & homework
“Guess first and prove later” (1) (14:17)
“Guess first and prove later” (2)
8-5 Guess first and verify later – Picture and text analysis & homework
8-6 Complex Binary Search (1) (13:17)
8-7 Complex Binary Search (2) (12:36)
8-8 Complex binary search algorithm – text and text analysis & homework
Chapter 9 recursion and Divide and conquer
When we solve a big problem, we often divide it into smaller problems and solve them one by one. This is because small problems are often easier to solve than big ones. That’s the idea of divide and conquer, divide and conquer. In this chapter, we’ll talk about how to implement this simple idea through computer algorithms. At the same time, patterns for solving small problems in computation often appear in the same or similar form, hence recursion. Recursion is not mysterious, divide-and-conquer is simple…
There are 10 sessions (97 minutes)
One example of 9-1 recursion: A “Not so good” example (19:52)
9-2 Fibonacci numbers and factorials
The Problem of eight Queens (I) (13:11)
9-4-2 Recurrence: The Eight Queens Problem (II) (11:38)
9-5 Eight Queens – Text analysis & homework
Understanding recursion: Recursion is implicit graph search, enumeration (23:49)
9-7 Implicit Graph search – Text and text parsing & assignments
Binary Lookup with Recursion framework (DFS) (Part 1)
Binary Lookup with Recursion framework (DFS) (2)
9-10 Recursive Divide-and-conquer framework – Graphic parsing & assignments
Chapter 10 graph correlation algorithm
Graph theory originated from the study of the famous mathematician Euler’s “seven Bridges problem”, also known as the one-stroke problem. Graph theory in computer algorithm interview is usually not too difficult, but it involves more knowledge points, such as binary tree, breadth first, depth first and so on. Graph theory questions are characterized by strong comprehensiveness, which is also one of the elements that people like graph theory questions in the written interview. In this chapter we are going to talk about graph theory questions in job interviews…
There are 15 sessions (154 minutes)
10-1 Breadth-first Search (BFS) (22:23)
10-2 Breadth First Search – Graphic parsing & assignments
10-3 Depth-first search (22:41)
10-4 Depth-first Search – Graphic parsing & assignments
10-5 Several Traversal Methods of binary Tree. Mp4 (20:55)
10-6 Binary tree traversal method – Text and text analysis & homework
Minimum Spanning Tree (I) (14:38)
Minimum Spanning Tree (Part 2)
10-9 Minimum Spanning Tree – Text and text parsing & assignments
10-10 Topology Sorting (PART 1)
10-11 Topology Sorting (Part 2) (14:43)
10-12 Topology Sorting – Text and text parsing & Assignments
An Implementation of the Shortest Circuit Algorithm (I)
An Implementation of the Shortest Circuit Algorithm (PART 2)
10-15 of the most short-circuited implementations
Chapter 11 greedy algorithms
The greedy algorithm is the simplest and most straightforward algorithm. For example, Prim and Krusal algorithms for the minimum spanning tree and Dijkstra algorithm for the shortest path are classic examples of greedy algorithms. Greedy algorithms have a simple, elegant charm. The difficulty of greedy algorithms lies in the proof. In this chapter, we will talk about the classical application of greedy algorithms and give theoretical or perceptual proofs for some problems. .
There are 7 sessions (66 minutes)
11-1 The Simplest Greedy Algorithm (15:59)
11-2 Greedy Algorithms – Text analysis & homework
11-3 Advanced Greedy Algorithm (18:48)
11-4 Intermediate Greedy Algorithm text and text analysis & Job analysis
11-5 Advanced Greedy Algorithms and Proof (1) (15:56)
11-6 Advanced Greedy Algorithms and Proof (2) (14:58)
11-7 Advanced Greedy Algorithms – Graphic analysis & assignments
Chapter 12 bit operations
Bitwise operations are unique to computers, which are naturally “good” at bitwise operations because they only know zeros and ones. In this chapter, we will discuss some applications of bit arithmetic in problem solving and lay the foundation for learning dynamic programming. There is a class of dynamic programming problems whose state representation requires bitwise operations. .
There are 7 sessions (67 minutes)
Introduction and Examples of 12-1-bit operations (1) (14:36)
Introduction and Examples of 12-2-bit operations (2) (14:09)
12-3 bit operations – Text and text parsing & assignments
12-4 Numbers that occur only once and two numbers that occur only once (16:22)
12-5 The number of occurrences of 1 – text parsing
12-6 Numbers that occur only twice (21:17)
12-7 Two numbers that occur only once – Graphic analysis & homework
Chapter 13 dynamic programming
Dynamic programming is almost a must in written tests and interviews, which is the most important, and many people may be afraid of it. In this chapter, we summarize the basic ideas of dynamic programming through some problems, and form some “routines” to solve dynamic programming problems, so that we can easily deal with this kind of problems.
There are 16 sessions (155 minutes)
13-1 Introduction and Examples (1)
13-2 Introduction and Examples (2) (13:48)
State Representation of Simple Dynamic Programming (1) (15:52)
State Representation of Simple Dynamic Programming (2) (13:00)
13-5 Getting started with Dynamic Planning – Text and Text parsing
State of More Complex Dynamic Programming (1) (11:36)
13-7 States of More Complex Dynamic Programming (2) (14:40)
13-8 Dynamic Planning – Simple State Representation – Image and Text parsing
13-9 Dynamic Planning – Complex State Representation – Text and text parsing
13-10 Optimization, Using Monotonicity — Longest Monotonic Subsequence (1) (14:57)
13-11 Optimization, Using Monotonicity — Longest Monotonic Subsequence (2) (12:44)
13-12 Dynamic programming – using monotone optimization – text and text analysis
Dynamic Programming and Combinational Counting (21:44)
13-14 Combinatorial counting of dynamic programming – Graphic analysis
13-15 Representation of states by bit operations (21:41)
13-16 Use bit operations to represent state – graphic parsing
Chapter 14 miscellaneous Questions – Questions you wouldn’t think of
Some topics are difficult to classify, but they are real. They require us to integrate knowledge points we have learned and use them flexibly. As the saying goes, “Tricks are different for everyone.” Everyone has learned similar knowledge points, but to achieve flexible use and mastery, it takes time to learn and practice hard. In this chapter, we use some typical examples to help you sort out the knowledge points and discuss some interesting topics. .
A total of 8 sessions (105 minutes)
Some Understandings of the sum of the largest subarray (26:23)
14-2 maximum subarray and the problem of several understanding – graphic parsing
14-3 The idea of “Enumerating half” (22:14)
14-4 half search – text and text analysis
14-5 Hash Thoughts (26:50)
14-6 Hash- Text parsing
14-7 Examples of Miscellaneous Questions (29:09)
14-8 Miscellaneous questions – Text and text analysis
Chapter 15 essential Soft Skills – Preventing blind spots in your thinking
Programmers don’t just write code, they communicate. We say “show me the code,” but code is not the only way we communicate. What’s more, before we implement the code, we usually need to communicate with others simply to prevent blind spots in the idea. In addition, we have a lot of design documents and code comments to complete, which undoubtedly requires good communication skills. The same is true in an interview. The interviewer is a human being.
Two periods (18 minutes)
Resume, Telephone interview, written test and Interview (17:34)
15-2 Soft Skills — Resume, written test, telephone interview, interview — supporting text and text
Chapter 16 summary and prospect
Interview system summary outlook, look to the future.
This course is constantly being updated
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The technical requirements
1. Master basic Java syntax
2. Master basic theoretical knowledge of algorithms and data structures
Environmental parameters
Development language: Java
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