Recursion and Backtracking (Memoization, D&C, Combinations) from Udemy

What's inside

Learning objectives

You will be able to solve almost any problem involving recursion or at least easily understand the logic behind it.
You will learn backtracking and be able to solve famous backtracking problems that may be asked in the coding interviews.
You will have the sufficient knowledge and skill to easily understand and learn data structures and algorithms.

You will learn how to create and solve problems having to do with recurrence relations.
You will learn the basics of programming paradigms such as dynamic programming, divide and conquer and backtracking.

You will be able to solve almost any problem involving recursion or at least easily understand the logic behind it.
You will learn backtracking and be able to solve famous backtracking problems that may be asked in the coding interviews.
You will have the sufficient knowledge and skill to easily understand and learn data structures and algorithms.
You will learn how to create and solve problems having to do with recurrence relations.
You will learn the basics of programming paradigms such as dynamic programming, divide and conquer and backtracking.

Syllabus

N-queens Problem

The Source Code

This file contains all the codes used in this course translated in Java.

Introduction

The Flood-Fill problem is discussed in this video

Traffic lights

Read about what's good

what should give you pause

and possible dealbreakers

Covers backtracking problems, which are frequently encountered in coding interviews, providing practical skills for job preparation

Explores divide and conquer strategies, which are fundamental algorithm design techniques taught in computer science programs

Teaches how to create and solve problems having to do with recurrence relations, a core concept in discrete mathematics

Provides sufficient knowledge and skill to easily understand and learn data structures and algorithms, which are essential for programming

Examines programming paradigms such as dynamic programming, divide and conquer, and backtracking, which are essential for advanced algorithm design

Includes source code translated in Java, which may be outdated given the rise of Python and other languages in the field

Reviews summary

Foundational algorithms for technical interviews

According to learners, this course provides a positive introduction to fundamental algorithm design techniques, particularly Recursion and Backtracking. Many students found the explanations clear and easy to follow, making complex topics accessible. Reviewers frequently mention its utility for technical interview preparation, stating it offers a solid base. While the core content is generally well-received, some reviews point out areas for improvement, such as occasional audio issues and a desire for more advanced topics or additional practice problems to deepen understanding beyond the basics.

Solid foundation but some want more depth.

"Good for beginners, but maybe not deep enough for advanced learners."

"Provides a solid base, but I wish it went into more detail on complex problems."

"Covers the basics well, but advanced techniques were not explored as much as I hoped."

Examples aid in understanding concepts.

"The examples provided were very practical and helped solidify my understanding."

"I liked the way problems were solved step-by-step."

"The coding examples were clear and easy to follow along with."

Helpful for preparing for coding interviews.

"Great course to prepare for coding interviews, covers key topics."

"This helped me refresh my understanding for upcoming interviews."

"Good foundation for tackling algorithm questions in interviews."

Concepts like recursion are explained clearly.

"The explanation of recursion and backtracking was very clear."

"He explained recursion very well, which was always a confusing topic for me."

"I finally understood the concept of recursion after taking this course. Great explanations."

Some reviews note inconsistent audio quality.

"The audio quality could be improved, sometimes it was hard to hear clearly."

"There were some parts where the audio was a bit muffled."

"Audio could be better but content makes up for it."

Activities

Be better prepared before your course. Deepen your understanding during and after it. Supplement your coursework and achieve mastery of the topics covered in Recursion and Backtracking (Memoization, D&C, Combinations) with these activities:

Review Basic Data Structures

Show steps

Strengthen your understanding of fundamental data structures to better grasp the concepts used in recursion and backtracking.

Browse courses on Arrays

Show steps

Review array and linked list implementations.
Practice implementing stack and queue operations.
Study tree and graph representations.

Solve Basic Recursion Problems

Show steps

Practice solving introductory recursion problems to build a solid foundation before tackling more complex backtracking algorithms.

Show steps

Solve factorial and Fibonacci sequence problems.
Implement recursive functions for string reversal.
Work through simple tree traversal problems.

Review 'Cracking the Coding Interview'

Show steps

Use this book to reinforce your understanding of recursion and backtracking with practice problems.

View Cracking the Coding Interview: 189 Programming... on Amazon

Show steps

Read the chapters on recursion and backtracking.
Solve the practice problems related to these topics.

Four other activities

Expand to see all activities and additional details

Show all seven activities

Review 'Algorithms' by Robert Sedgewick and Kevin Wayne

Show steps

Use this book to gain a deeper understanding of the theoretical foundations of recursion and backtracking.

View Introduction to Programming in Java: An... on Amazon

Show steps

Read the chapters on recursion, divide and conquer, and backtracking.
Work through the examples and exercises in the book.

Implement a Maze Solver

Show steps

Apply backtracking techniques learned in the course to create a program that finds a path through a maze.

Show steps

Design a maze representation using a 2D array.
Implement a recursive backtracking algorithm to explore paths.
Visualize the solution path.

Create a Backtracking Tutorial

Show steps

Solidify your understanding of backtracking by creating a tutorial that explains the concept and provides examples.

Show steps

Choose a specific backtracking problem to explain.
Write a clear and concise explanation of the algorithm.
Create illustrative examples and diagrams.
Publish the tutorial on a blog or platform.

Participate in Coding Challenges

Show steps

Test your skills in recursion and backtracking by participating in online coding challenges and competitions.

Show steps

Find coding challenges on platforms like LeetCode or HackerRank.
Select problems that involve recursion or backtracking.
Implement solutions and submit them for evaluation.

Career center

Learners who complete Recursion and Backtracking (Memoization, D&C, Combinations) will develop knowledge and skills that may be useful to these careers:

Algorithm Developer

An algorithm developer specializes in designing and implementing algorithms for various applications. This course provides a deep dive into algorithm design techniques, including divide and conquer, dynamic programming, and backtracking, which are fundamental to the role of an algorithm developer. The coverage of specific problems, such as the N-queens problem and maze problems, helps hone problem-solving skills crucial for algorithm development. Aspiring algorithm developers may find this course particularly valuable due to its focus on core algorithm design principles.

See salaries and explore the career path for Algorithm Developer

Software Engineer

A software engineer designs, develops, and tests software applications. This course helps build a foundation in algorithm design techniques like divide and conquer, dynamic programming, and backtracking, which are essential for solving complex software engineering problems. This course, with its focus on recursion and backtracking, may be useful in optimizing code and designing efficient algorithms. The exploration of the N-queens problem, maze problems, and the magnet chain problem, provides practical experience that translates directly into real-world software development scenarios. Those aspiring to excel as software engineers will find this course particularly beneficial.

See salaries and explore the career path for Software Engineer

Academic Researcher

Academic researchers conduct research in computer science and related fields, often requiring advanced degrees (master's or phd). This course provides a solid foundation in algorithm design and analysis, which are essential for conducting research in areas such as artificial intelligence, machine learning, and theoretical computer science. The skills learned, such as divide and conquer, dynamic programming, and backtracking, may be useful in developing novel algorithms and solving complex computational problems. Aspiring academic researchers will find this course particularly useful.

See salaries and explore the career path for Academic Researcher

Data Scientist

Data scientists analyze large datasets to extract meaningful insights and develop predictive models. The skills taught in this course, particularly in divide and conquer and dynamic programming, help optimize data processing algorithms and improve the efficiency of data analysis pipelines used by data scientists. The ability to understand and implement backtracking algorithms, as covered in this course, may be useful in solving complex optimization problems in machine learning. This course, which covers backtracking, recursion, and other algorithms, helps refine the analytical skills of aspiring data scientists.

See salaries and explore the career path for Data Scientist

Game Developer

A game developer creates and programs video games. This course helps build a strong foundation in algorithm design techniques like backtracking and recursion, which are often used in developing game mechanics, AI, and pathfinding algorithms. The course's exploration of the maze problem and the knight problem directly applies to game development scenarios. This course may be useful for aspiring game developers, as it addresses the complex problem-solving skills required in game programming.

See salaries and explore the career path for Game Developer

Machine Learning Engineer

A machine learning engineer develops and deploys machine learning models. This course helps build a strong foundation in algorithm design, particularly dynamic programming and divide and conquer, which are useful in optimizing machine learning algorithms and improving their performance. The knowledge of backtracking may be useful in solving optimization problems related to model training. Aspiring machine learning engineers can leverage the algorithmic principles taught in this course to refine their machine learning skills.

See salaries and explore the career path for Machine Learning Engineer

Quantitative Analyst

A quantitative analyst, often working in finance, develops and implements mathematical models for financial analysis and risk management. This course helps hone problem-solving and algorithmic thinking, which are essential for designing efficient and accurate quantitative models. The techniques covered, such as dynamic programming and divide and conquer, help optimize complex calculations and improve the performance of financial algorithms. Individuals aiming to become quantitative analysts may find this course helpful in enhancing their computational skills.

See salaries and explore the career path for Quantitative Analyst

Robotics Engineer

Robotics engineers design, build, and program robots for various applications. The knowledge of algorithm design techniques, particularly backtracking and dynamic programming, helps in developing efficient robot control and navigation algorithms. The maze problem and gold collector problem covered in this course may be useful in teaching robots to navigate complex environments and optimize resource collection. Aspiring robotics engineers can leverage the principles taught in this course to enhance their robot programming skills.

See salaries and explore the career path for Robotics Engineer

Bioinformatician

A bioinformatician analyzes biological data using computational tools and techniques. This course's coverage of algorithm design techniques, such as dynamic programming and divide and conquer, helps in optimizing algorithms for sequence alignment, phylogenetic analysis, and other bioinformatics tasks. The skills developed in this course are useful in processing and analyzing large biological datasets efficiently. Aspiring bioinformaticians may find this course beneficial for enhancing their computational biology skills.

See salaries and explore the career path for Bioinformatician

Data Engineer

A data engineer is responsible for designing, building, and maintaining the infrastructure that supports data storage and processing. While this course may not directly cover data engineering tools, the course's focus on divide and conquer and dynamic programming helps in optimizing data processing pipelines and improving the efficiency of data handling. The algorithmic problem-solving skills developed in this course help in designing robust and scalable data infrastructure. Data engineers can benefit from understanding the algorithmic principles covered in this course.

See salaries and explore the career path for Data Engineer

Cybersecurity Analyst

Cybersecurity analysts protect computer systems and networks from cyber threats. This course helps develop problem-solving and algorithmic thinking skills, which are essential for identifying and mitigating security vulnerabilities. The backtracking techniques covered may be useful in analyzing potential attack paths and developing effective defense strategies. This course may be useful for cybersecurity analysts in enhancing their threat analysis capabilities.

See salaries and explore the career path for Cybersecurity Analyst

High Performance Computing Specialist

High performance computing specialists develop and optimize software for supercomputers and other high-performance computing systems. This course directly supports the development of efficient, parallelizable algorithms. Divide and conquer strategies are foundational here, as well as dynamic programming approaches that allow for efficient memory use. The algorithm design techniques covered in this course may be helpful to those aiming to maximize computational throughput.

See salaries and explore the career path for High Performance Computing Specialist

Operations Research Analyst

Operations research analysts use mathematical and analytical methods to help organizations make better decisions. This course contributes to a deeper understanding of optimization techniques and algorithm efficiency. Backtracking, dynamic programming, and divide and conquer (all covered in this course) help in solving complex operational problems. Those wishing to pursue a career as an operations research analyst may appreciate the foundations laid by this course.

See salaries and explore the career path for Operations Research Analyst

Database Administrator

Database administrators manage and maintain databases to ensure data availability and integrity. This course may not directly cover database management systems, but the focus on divide and conquer and dynamic programming helps in optimizing database queries and improving data retrieval performance. The algorithmic problem-solving skills developed in this course may be helpful in designing efficient database schemas and optimizing database operations.

See salaries and explore the career path for Database Administrator

Technical Consultant

Technical consultants provide expert advice and guidance to clients on technology-related issues. While this course isn't directly about consulting, the problem-solving and algorithmic thinking skills it fosters are broadly applicable. The ability to quickly analyze complex situations and develop efficient solutions, informed by techniques like dynamic programming and divide and conquer, are valuable assets in consulting. This course may be useful for technical consultants who need strong analytical abilities.

See salaries and explore the career path for Technical Consultant

Recursion and Backtracking (Memoization, D&C, Combinations)

Here's a deal for you

What's inside

Learning objectives

Syllabus

Traffic lights

Save this course

Reviews summary

Foundational algorithms for technical interviews

Activities

Career center

Reading list

Share

Similar courses