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Lucian Ilea

This course presents a group of elementary and advanced Algorithms and Programming Techniques. It is the result of my own experience as a trainer in the field of Competitive Programming, teacher, author and (many times) competitor. It is based on the most important theoretical issues and knowledge a student should master. The topics that are discussed stretch from Recursion and its different peculiar applications (Backtracking, Divide and Conquer) to the Branch and Bound method. The course has two different lessons dedicated to the Dynamic Programming Technique, due to the importance this method has.

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This course presents a group of elementary and advanced Algorithms and Programming Techniques. It is the result of my own experience as a trainer in the field of Competitive Programming, teacher, author and (many times) competitor. It is based on the most important theoretical issues and knowledge a student should master. The topics that are discussed stretch from Recursion and its different peculiar applications (Backtracking, Divide and Conquer) to the Branch and Bound method. The course has two different lessons dedicated to the Dynamic Programming Technique, due to the importance this method has.

The course contains many well known problems, presents their solutions in a comprehensible way and offers C++ solutions. A clear purpose and objective that the author had in mind was to have neat statements, proper examples, efficient solutions, easy to understand C++ programs. I suppose that the students already have some elementary background in the C++ language, some experience with STL data structures and implemented methods, CodeBlocks Integrated Development Environment, Online Judges .

Each lesson is followed by some quizzes.

The students are advised to try to implement on their own the C++ programs for the problems they encounter in the lessons.

Every time when it was possible, I used some pictures, animations, free templates offered by different sites.

I hope you will enjoy and appreciate this course.

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What's inside

Learning objective

Algorithms and programming techniques

Syllabus

The students will be able to recognize some recursive patterns in several situations
Recursion
The Greatest Common Divisor

The classical Josephus' problem is analyzed. Some less known properties are highlighted.

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This quiz is meant to test your understanding about what we just talked about.

Some questions about Backtracking algorithm

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Read about what's good
what should give you pause
and possible dealbreakers
Offers C++ solutions to well-known problems, which is essential for competitive programming and helps students refine their coding skills and problem-solving abilities
Covers recursion, backtracking, divide and conquer, and dynamic programming, which are fundamental algorithmic techniques taught in computer science curricula
Explores dynamic programming with applications to computational geometry, which may be useful for students interested in graphics, robotics, and other fields
Requires familiarity with C++, STL data structures, and CodeBlocks IDE, which may pose a barrier to entry for students unfamiliar with these tools
Includes quizzes after each lesson, which allows students to test their understanding and reinforce their learning of the material
Presents the traveling salesman problem, which is a classic problem in computer science and operations research and is often used to illustrate advanced algorithmic techniques

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Reviews summary

Advanced algorithms and techniques reviewed

According to students, this course provides deep coverage of advanced algorithms like Dynamic Programming, Backtracking, and Branch and Bound, making it highly relevant for competitive programming and theoretical computer science. However, learners frequently point out that the course assumes a very strong foundation in C++, data structures, and sometimes mathematics, which can make it challenging for those without significant prior experience. While many find the C++ code examples helpful, some reviewers noted that they could benefit from more detailed explanations. Overall, the instructor's knowledge is appreciated, though some find the explanation clarity varies between topics.
Instructor clarity varies by topic.
"Some lectures were incredibly clear and easy to follow."
"Parts of the course felt very dense and abstract, requiring external resources."
"The instructor knows the material, but the teaching style is sometimes uneven."
"Certain algorithms were explained brilliantly, others less so."
Code provided, requires C++ familiarity.
"The C++ solutions provided are correct and efficient if you can follow them."
"Wish the code examples had more step-by-step explanations for understanding."
"The examples are good if you are already comfortable reading complex C++."
"I found implementing the solutions myself was crucial, as suggested."
Explores complex algorithms in detail.
"The sections on Dynamic Programming were incredibly thorough and helpful. A real deep dive."
"Loved the depth the course goes into on topics like Branch and Bound and Meet in the middle."
"This course provides a comprehensive look at several advanced algorithms that are essential."
"I finally grasped Recursion and Backtracking much better after this."
Assumes significant prior knowledge.
"Be warned, you need a very strong background in C++ and data structures before taking this."
"I struggled because my C++ skills weren't as advanced as the course expects."
"This is definitely not for beginners. Make sure your prerequisites are solid."
"Assumes familiarity with STL and competitive programming environments."

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 Advanced Algorithms and Programming Techniques with these activities:
Review Data Structures
Reviewing data structures will help you better understand the C++ solutions presented in the course.
Browse courses on Data Structures
Show steps
  • Review array, linked list, stack, and queue implementations.
  • Practice implementing basic operations on each data structure.
Introduction to Algorithms
Referencing this book will provide a deeper understanding of the algorithms discussed in the course.
Show steps
  • Read the chapters related to the algorithms covered in the course.
  • Work through the examples and exercises in the book.
Implement Sorting Algorithms
Practicing sorting algorithms will reinforce your understanding of divide and conquer techniques.
Show steps
  • Implement merge sort, quicksort, and heapsort from scratch.
  • Compare the performance of different sorting algorithms on various datasets.
Four other activities
Expand to see all activities and additional details
Show all seven activities
Create a Blog Post on Dynamic Programming
Writing a blog post will help you consolidate your knowledge of dynamic programming concepts.
Show steps
  • Choose a specific dynamic programming technique or problem.
  • Explain the concept in a clear and concise manner.
  • Provide examples and code snippets to illustrate the concept.
Implement a Pathfinding Algorithm Visualizer
Implementing a pathfinding visualizer will solidify your understanding of graph algorithms and dynamic programming.
Show steps
  • Choose a pathfinding algorithm (e.g., A*, Dijkstra's).
  • Implement the algorithm in C++.
  • Create a visual interface to display the algorithm's progress.
Programming Challenges: The Programming Contest Training Manual
Working through the problems in this book will enhance your problem-solving skills.
Show steps
  • Select problems related to the topics covered in the course.
  • Attempt to solve the problems on your own before looking at the solutions.
Contribute to an Open Source Algorithm Library
Contributing to an open-source project will provide valuable experience in applying your algorithmic knowledge.
Show steps
  • Find an open-source algorithm library on GitHub or GitLab.
  • Identify a bug or missing feature related to the course topics.
  • Implement the fix or feature and submit a pull request.

Career center

Learners who complete Advanced Algorithms and Programming Techniques will develop knowledge and skills that may be useful to these careers:
Competitive Programmer
A competitive programmer participates in programming contests, solving algorithmic problems under time constraints. This course, designed by a trainer in competitive programming, directly aligns with the needs of a competitive programmer. The course covers essential algorithms and programming techniques, including recursion, backtracking, divide and conquer, dynamic programming, and branch and bound. The emphasis on efficient C++ solutions and the analysis of well-known problems provides practical experience for solving contest problems. The structure of the course with lessons and quizzes mirrors the contest environment, and the course's focus on problem-solving strategies will benefit competitive programmers of all levels.
Algorithm Developer
An algorithm developer focuses on creating and optimizing algorithms for various applications. This course provides a comprehensive overview of elementary and advanced algorithms and programming techniques, directly relevant to this role. With its coverage of recursion, backtracking, divide and conquer, and dynamic programming, the course equips algorithm developers with the tools to tackle complex problems. The course's detailed analysis of well-known problems, along with efficient C++ solutions, provides practical insights for algorithm design and implementation. The sections on Dynamic Programming and Computational Geometry may be particularly useful to an algorithm developer.
Software Engineer
A software engineer designs, develops, and tests software applications. This course helps build a foundation in algorithms and programming techniques, which are essential for efficient software development. The course's emphasis on recursion, backtracking, divide and conquer, and dynamic programming helps software engineers design and implement complex algorithms effectively. Software engineers planning to work with optimization problems benefit from the Branch and Bound methods covered. The C++ solutions and focus on efficient implementations taught in the course equip software engineers with practical skills for real-world projects.
Game Developer
A game developer designs and develops video games. This course helps a game developer by covering essential algorithms and programming techniques that are fundamental to game development. The course's sections on backtracking, divide and conquer, dynamic programming, and computational geometry provide tools for solving complex problems in game design. The course's examples, such as 'Chess and Backtracking' and 'Chess and Dynamic Programming', directly relate to game development scenarios. A game developer can leverage the knowledge gained from this course to create more efficient and engaging game experiences.
Robotics Engineer
A robotics engineer designs, builds, and programs robots. This course helps a robotics engineer due to its treatment of algorithms and programming techniques, which are essential for robot control and navigation. The course's coverage of recursion, backtracking, divide and conquer, and dynamic programming provides tools for solving complex pathfinding and decision-making problems. The emphasis on efficient C++ solutions enables robotics engineers to implement real-time control algorithms. For example, the material on Computational Geometry would be very applicable to navigation and obstacle detection.
Quantitative Analyst
A quantitative analyst, often requiring a master's degree, develops and implements mathematical models for financial analysis. The course helps quantitative analysts work with algorithms and programming techniques. The course's coverage of dynamic programming, binary search, and matrix exponentiation can be useful for valuing derivatives and managing risk. The focus on efficient C++ implementations will be helpful for developing high-performance trading systems. Quantitative analysts will benefit from this course's focus on core algorithmic problem solving principles.
Firmware Engineer
A firmware engineer develops software embedded in hardware devices. This course helps a firmware engineer because it covers essential algorithms and programming techniques that are crucial for embedded systems programming. The course's coverage of recursion, dynamic programming, and binary search provides tools for optimizing code that runs on limited resources. The emphasis on efficient C++ solutions enables firmware engineers to write code that meets real-time performance requirements. Firmware engineers must be able to work with limited resources so this course may be invaluable.
Data Scientist
A data scientist analyzes large datasets to extract meaningful insights and build predictive models. This course may be useful for a data scientist because it covers essential algorithms and programming techniques. The concepts of dynamic programming, binary search, and sorting algorithms can be applied while manipulating and analyzing data. A data scientist may encounter problems when dealing with large datasets where algorithm optimization is crucial, and the course's focus on efficient implementations will then prove valuable. Overall, the course provides a foundation for a data scientist to enhance their problem-solving skills.
Data Engineer
A data engineer builds and maintains the infrastructure for data storage and processing. This course may be useful for a data engineer, as it covers essential algorithms and programming techniques. Sorting algorithms, searching algorithms, and data structures, can be applied while working with large datasets. The course's emphasis on efficient implementations will be helpful when optimizing data pipelines and storage systems. The material discussed in this course can serve as a guide as one aims to develop systems that are optimized for performance and scalability.
Bioinformatics Scientist
A bioinformatics scientist analyzes biological data using computational techniques, usually requiring a phd. This course may be useful as the course covers essential algorithms and programming techniques. Dynamic programming, sequence alignment algorithms, and graph algorithms can all be applied in bioinformatics. The course's emphasis on efficient implementations is helpful when dealing with large-scale biological datasets. Someone wishing to specialize in Bioinformatics may find this course a good way to get started implementing efficient algorithms.
Systems Architect
A systems architect designs and implements complex computer systems. This course may be useful for a systems architect because it covers essential algorithms and programming techniques. The concepts of recursion, backtracking, and divide and conquer, can be applied while designing scalable and reliable systems. The course's emphasis on efficient implementations will be helpful when optimizing system performance. A systems architect will find the lessons on implementing advanced algorithms useful for system design.
Machine Learning Engineer
A machine learning engineer develops and deploys machine learning models. This course may be helpful for a machine learning engineer because it provides a solid grounding in algorithms and programming techniques. The course's coverage of dynamic programming, sorting algorithms, and binary search can be valuable for optimizing machine learning models. The course's emphasis on efficient C++ solutions contributes to improving the performance of machine learning algorithms. A machine learning engineer can leverage the knowledge gained from this course to better implement and optimize machine learning algorithms for real-world applications. This course will help Machine Learning Engineers write more efficient and effective code.
Database Administrator
A database administrator manages and maintains databases to ensure data integrity and availability. This course may be useful for a database administrator because it covers essential algorithms and programming techniques. Sorting algorithms, searching algorithms, and data structures can be applied while optimizing database queries and performance. This focus on efficient implementations can be helpful when troubleshooting database issues and improving overall system performance. Database Administrators looking to improve the performance of their databases may find this course helpful.
Network Engineer
A network engineer designs, implements, and manages computer networks. Studying this course may be helpful for a network engineer because it covers essential algorithms and programming techniques. Graph algorithms, routing algorithms, and network flow algorithms can be applied while designing and optimizing network protocols. The course's emphasis on efficient implementations can be helpful when building high-performance network systems. A network engineer will find that the knowledge in this course can help them design better networks.
Security Engineer
A security engineer protects computer systems and networks from cyber threats. This course may be useful for a security engineer because it covers essential algorithms and programming techniques. Cryptographic algorithms, hashing algorithms, and security protocols can be applied while developing secure systems. The course's emphasis on efficient implementations can be helpful when analyzing and mitigating security vulnerabilities. A security engineer can greatly benefit from applying the principles of efficient coding taught in this course.

Reading list

We've selected two books that we think will supplement your learning. Use these to develop background knowledge, enrich your coursework, and gain a deeper understanding of the topics covered in Advanced Algorithms and Programming Techniques.
Comprehensive textbook on algorithms, covering a wide range of topics including recursion, dynamic programming, greedy algorithms, and graph algorithms. It provides rigorous analysis and clear explanations, making it suitable as a primary reference for the course. It is commonly used in undergraduate and graduate courses in algorithms at many universities. This book provides a strong theoretical foundation for the practical techniques taught in the course.
Is an excellent resource for practicing competitive programming problems. It covers a wide range of algorithmic techniques and provides numerous examples and exercises. It is particularly useful for students who want to improve their problem-solving skills and prepare for programming contests. This book is more valuable as additional reading and practice than as a current reference.

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