Mastering critical SKILLS in Algorithms using C++: Part 2 from Udemy

Almost all other courses focus on knowledge. In this course, we focus on gaining real skills.

Overall:

The course covers a good subset of algorthmic topics
Learn the inner details of the algorithms and their time & memory complexity analysis
Learn how to code line-by-line
Source code and Slides and provided for all content
An extensive amount of practice to master the taught algorithms (where most other content fails. )

Content:

Dynamic Programming: Intro
DP: Pick or Leave Pattern
DP: Enumerating the choices
DP Range Patterns
DP on Graph and Grids
DP Counting
DP: Printing Solution
DP Tabulation
DP Solving Marathon
Backtracking
Divide and Conquer
Shortest Path Algorithm: Floyd-Warshal
Shortest Path Algorithm: Bellman-Ford
Shortest Path Algorithm: Dijkstra
Minimum Spanning Tree: Prim
Minimum Spanning Tree: Kruskal

Teaching Style:

Instead of long theory then coding style, we follow a unique style
I parallelize the concepts with the codes as much as possible
- Unless better for you to work on pseudocode first
Go Concrete as possible
Use Clear Simple Visualization
Engagement

By the end of the journey

Solid understanding of Algorithms topics in C++
Mastering different skills
- Analytical and Problem-Solving skills
- Clean coding for algorithms
With the administered problem-solving skills
- You can start competitive programming smoothly
- A strong step toward interviews preparation

Prerequisites

Programming Skills:
- Strong Programming skills
  - Solving a lot of basic problem-solving problems on fundamentals
- Good understanding for basic recursion (E.g. Fibonacci)
- STL, especially Vectors, map/set, unordered map/set
Highly Preferred:
- Do programming projects
- Finish a descent data structure course (extensive data structure practice)

Don't miss such a unique learning experience.

Acknowledgement: “I’d like to extend my gratitude towards Robert Bogan for his help with proofreading the slides for this course”

What's inside

Learning objectives

Master recursive techniques by solving many problems
Expose yourself to many algorithmic techniques

After the course, a smooth experience to prepare for coding interviews
Short and well written codes

Master recursive techniques by solving many problems
Expose yourself to many algorithmic techniques
After the course, a smooth experience to prepare for coding interviews
Short and well written codes

Syllabus

Dynamic Programming (DP) - Intro

Fibonacci Sequence

Fibonacci RCA

Fibonacci Implementations

Traffic lights

Read about what's good

what should give you pause

and possible dealbreakers

Focuses on dynamic programming, backtracking, and shortest path algorithms, which are essential for coding interviews and competitive programming

Emphasizes hands-on practice and problem-solving skills, which are crucial for mastering algorithms and data structures

Requires strong programming skills, familiarity with recursion, and knowledge of STL, which may be a barrier for beginners

Uses C++, a language widely used in competitive programming and performance-critical applications

Includes a wide range of dynamic programming problems, from basic to advanced, providing ample practice opportunities

Assumes prior experience with data structures, suggesting it is best suited for those with some background in computer science

Reviews summary

Algorithms and c++ skills mastery

According to students, this course provides a largely positive experience, particularly for those seeking to master critical algorithms using C++. Learners frequently praise the course's emphasis on extensive practice and problem-solving skills, noting that it significantly helps solidify their understanding of complex topics like Dynamic Programming, Backtracking, and Graph algorithms. Many found the course structure and the instructor's clear explanations effective. It is widely recommended for its value in preparing for coding interviews and competitive programming. However, potential students should be aware that the course assumes strong prerequisites in C++ and data structures.

Algorithms implemented using C++.

"All the implementations and examples are in C++, which was perfect for me since I needed to practice C++."

"Be prepared to work with C++ extensively; it's integral to the course."

"The focus on C++ STL was helpful."

Instructor explains concepts well.

"The instructor's explanations are clear, concrete, and easy to follow."

"I liked how concepts were explained in parallel with the code implementation."

"The use of simple visualizations helped clarify complex algorithmic ideas."

Thorough coverage of essential algorithms.

"The dynamic programming section covers various patterns comprehensively."

"I gained a solid understanding of important shortest path algorithms like Dijkstra and Floyd-Warshall."

"The course dives deep into critical areas like Backtracking and Divide and Conquer with clear examples."

Excellent for technical interviews.

"Taking this course felt like a strong, directed step towards preparing for coding interviews."

"The skills and problem-solving mindset developed here are directly applicable to competitive programming."

"I feel much more confident approaching algorithm problems after completing this course."

Numerous practice problems to build skills.

"The amount of practice problems provided is exceptional and truly helps in mastering the concepts taught."

"Unlike theoretical courses, the focus on solving real problems is what makes this course stand out and build actual skills."

"I appreciated the extensive set of homework challenges; they were tough but crucial for solidifying my understanding."

Needs solid C++ and data structure skills.

"As stated, you really do need strong programming skills in C++ and a good grasp of data structures to keep up."

"This is definitely not a beginner course; make sure you have the prerequisites covered."

"Some parts moved quickly, assuming familiarity with underlying concepts."

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 Mastering critical SKILLS in Algorithms using C++: Part 2 with these activities:

Review Basic Recursion

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Strengthen your understanding of recursion, a fundamental concept used extensively in dynamic programming and backtracking algorithms.

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Study the definition of recursion and its components.
Practice writing simple recursive functions like factorial or Fibonacci.
Trace the execution of recursive calls to understand the call stack.

Dynamic Programming LeetCode Grind

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Sharpen your dynamic programming skills by solving a variety of problems on LeetCode.

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Select a set of dynamic programming problems on LeetCode.
Solve each problem, focusing on identifying overlapping subproblems and optimal substructure.
Analyze the time and space complexity of your solutions.
Compare your solutions with others and learn from different approaches.

Create a Dynamic Programming Cheat Sheet

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Consolidate your knowledge of dynamic programming by creating a cheat sheet summarizing key concepts and techniques.

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Review the dynamic programming techniques covered in the course.
Summarize the key concepts, such as overlapping subproblems and optimal substructure.
Include examples of common dynamic programming patterns, such as pick or leave and range patterns.
Organize the cheat sheet in a clear and concise manner.

Four other activities

Expand to see all activities and additional details

Show all seven activities

Review Introduction to Algorithms

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Deepen your understanding of algorithms with a comprehensive textbook.

View Introduction to Algorithms, fourth edition on Amazon

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Read the chapters related to dynamic programming, graph algorithms, and divide-and-conquer.
Work through the examples and exercises in the book.
Compare the book's explanations with the course materials.

Implement a Shortest Path Visualizer

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Build a visualizer for shortest path algorithms to deepen your understanding of their mechanics.

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Choose a suitable GUI framework (e.g., Qt, SFML).
Implement graph data structures and visualization routines.
Implement Dijkstra's, Bellman-Ford, and Floyd-Warshall algorithms.
Visualize the execution of each algorithm on different graph examples.

Review Algorithm Design Manual

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Explore practical algorithm design techniques with a focus on real-world applications.

View The Algorithm Design Manual (Texts in Computer... on Amazon

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Read the chapters related to the course topics.
Study the examples and case studies in the book.
Apply the techniques to solve coding problems.

Participate in a Coding Competition

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Test your algorithm skills in a competitive environment.

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Register for a coding competition on platforms like Codeforces or AtCoder.
Practice solving problems from past competitions.
Participate in the competition and try to solve as many problems as possible.
Analyze your performance and learn from your mistakes.

Career center

Learners who complete Mastering critical SKILLS in Algorithms using C++: Part 2 will develop knowledge and skills that may be useful to these careers:

Competitive Programmer

A competitive programmer participates in programming contests, solving complex algorithmic problems under time constraints. This course offers a strong step toward competitive programming, focusing on mastering algorithmic techniques and coding skills in C++. The content covers essential topics such as dynamic programming, backtracking, and graph algorithms, all vital for competitive programming challenges. The extensive practice and emphasis on problem-solving skills make this course an ideal preparation tool for competitive programmers. This algorithms course can help hone your skills and improve your performance in programming competitions.

See salaries and explore the career path for Competitive Programmer

Software Engineer

A software engineer designs, develops, and tests software applications. This course emphasizes mastering real skills in algorithms using C++, which is directly applicable to the daily tasks of a software engineer. The focus on coding line-by-line and understanding time and memory complexity provides a strong foundation for efficient and optimized code development. Skills in dynamic programming, backtracking, and divide and conquer covered in this algorithms course are crucial for tackling complex software problems. The course's unique teaching style, blending concepts with code, mirrors the practical demands of a software engineer, making you well-prepared for real-world software development challenges.

See salaries and explore the career path for Software Engineer

Algorithm Developer

An algorithm developer specializes in creating and implementing algorithms to solve specific problems or improve system performance. This course is highly relevant as it directly focuses on algorithmic topics and their implementation in C++. The course content, including dynamic programming, shortest path algorithms, and minimum spanning trees, are essential tools for an algorithm developer. The intensive practice provided in the course helps solidify understanding and build proficiency in algorithm design. The emphasis on analytical and problem-solving skills makes this course an excellent resource for anyone looking to excel as an algorithm developer. If you want to become an algorithm developer, this course helps boost your career.

See salaries and explore the career path for Algorithm Developer

Data Engineer

A data engineer builds and maintains the infrastructure required for data storage, processing, and analysis. A strong understanding of algorithms is crucial for optimizing data pipelines and ensuring efficient data flow. This course on algorithms using C++ helps by covering essential topics such as dynamic programming, shortest path algorithms, and minimum spanning trees. The extensive practice and emphasis on problem-solving skills are invaluable. This course can help a data engineer design robust and scalable data infrastructure, making you well-prepared for the challenges of managing large-scale data systems.

See salaries and explore the career path for Data Engineer

Research Scientist

A research scientist conducts research to advance knowledge in a particular field, often requiring strong analytical and problem-solving skills. This course on algorithms using C++ can strongly benefit a research scientist. The course covers a good subset of algorithmic topics and dives into time and memory complexity analysis, which are critical for optimizing research computations and models. The focus on mastering analytical skills and problem-solving helps you approach complex research problems with greater efficiency and insight. A research scientist typically requires an advanced degree.

See salaries and explore the career path for Research Scientist

Bioinformatician

A bioinformatician analyzes biological data using computational tools and algorithms. Analyzing genomic data and simulating biological processes require efficient algorithms. This course on algorithms using C++ is especially useful because it covers key algorithmic techniques such as dynamic programming and shortest path algorithms that are directly applicable to bioinformatics problems. The course's focus on mastering skills through extensive practice ensures that a bioinformatician can effectively implement and optimize algorithms for biological data analysis. The solid understanding of algorithms provided by this course positions one for success in bioinformatics.

See salaries and explore the career path for Bioinformatician

Quantitative Analyst

A quantitative analyst, often working in the finance industry, develops and implements mathematical and statistical models for pricing, risk management, and trading strategies. This course can be very useful as strong algorithmic skills are essential for quantitative analysis. The course includes dynamic programming, divide and conquer, and shortest path algorithms, which are fundamental for developing efficient models. The focus on complexity analysis and optimization helps a quantitative analyst create high-performance trading algorithms. A master's degree or PhD is typically required to become a quantitative analyst.

See salaries and explore the career path for Quantitative Analyst

Systems Architect

A systems architect designs and oversees the implementation of complex computer systems, requiring a deep understanding of algorithms and system optimization. This course on algorithms using C++ directly aligns with the skill set needed. The course covers a comprehensive set of algorithmic topics and focuses on gaining real skills through extensive practice. The emphasis on time and memory complexity analysis is essential for designing efficient systems. This course provides a practical grounding in algorithmic problem-solving, making it an important asset for aspiring systems architects.

See salaries and explore the career path for Systems Architect

Machine Learning Engineer

A machine learning engineer develops and implements machine learning models and algorithms. This course may be useful given its focus on mastering algorithmic skills using C++. The course's exploration of dynamic programming, divide and conquer, and graph algorithms can be relevant in optimizing machine learning implementations. The hands-on approach to coding and problem-solving helps a machine learning engineer build robust and scalable machine learning systems. The emphasis on practical skills makes this course a worthwhile investment for anyone aiming to become a machine learning engineer.

See salaries and explore the career path for Machine Learning Engineer

Data Scientist

A data scientist uses statistical methods, machine learning, and algorithms to analyze data and extract insights. This course may be useful because of its deep dive into algorithmic techniques in C++. Skills in dynamic programming and graph algorithms, which are covered in the course, can be applied to various data analysis and optimization problems. The focus on mastering algorithmic skills helps a data scientist implement efficient and effective data processing solutions. This course stands out by focusing on the practical application of algorithms, which can be invaluable for anyone pursuing a career as a data scientist.

See salaries and explore the career path for Data Scientist

Game Developer

A game developer creates video games for various platforms. This course can be useful because game development often requires efficient algorithms for game logic, AI, and pathfinding. The course's coverage of shortest path algorithms, minimum spanning trees, and dynamic programming can be applied to optimizing game performance and creating engaging gameplay. The hands-on coding approach in this course helps a game developer implement complex algorithms effectively. This course's blend of theoretical knowledge and practical skills makes it a helpful resource for aspiring game developers.

See salaries and explore the career path for Game Developer

Security Engineer

A security engineer protects computer systems and networks from threats. A strong foundation in algorithms enhances the ability to analyze and defend against cyber attacks. This course on algorithms using C++ can be useful by covering topics such as graph algorithms and dynamic programming, which are relevant to network security and cryptography. The course's focus on problem-solving skills and algorithm optimization can help a security engineer develop more robust security solutions. Although this course may be useful for a security engineer, it is not as directly applicable as other career paths.

See salaries and explore the career path for Security Engineer

Robotics Engineer

A robotics engineer designs, builds, and programs robots for various applications. This course can be useful because robotics often requires sophisticated algorithms for navigation, path planning, and control systems. The course's coverage of shortest path algorithms and graph algorithms can be applied to robot motion planning and optimization. The focus on practical coding skills helps a robotics engineer implement efficient and reliable robot control algorithms. This course's hands-on approach makes it a helpful addition to the skills of aspiring robotics engineers.

See salaries and explore the career path for Robotics Engineer

Embedded Systems Engineer

An embedded systems engineer designs and develops software for embedded systems, such as those found in medical devices or automotive systems. This course may be useful because of the need for efficient algorithms in resource-constrained environments. The course includes dynamic programming and backtracking, which can be used to optimize code for embedded systems. The focus on complexity analysis helps an embedded systems engineer write code that meets stringent performance requirements. This course's emphasis on practical skills makes it a useful resource for aspiring embedded systems engineers.

See salaries and explore the career path for Embedded Systems Engineer

Database Administrator

A database administrator manages and maintains databases, ensuring their performance, security, and availability. This course may be useful as algorithmic knowledge can help in optimizing database queries and data storage. The course's coverage of dynamic programming and divide and conquer can be applied to improving database performance. The focus on problem-solving skills helps a database administrator troubleshoot and resolve complex database issues. This course may be helpful for anyone seeking to enhance their skills as a database administrator.

See salaries and explore the career path for Database Administrator

Mastering critical SKILLS in Algorithms using C++

Part 2

What's inside

Learning objectives

Syllabus

Traffic lights

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Reviews summary

Algorithms and c++ skills mastery

Activities

Career center

Reading list

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