Beginner's guide to Competitive programming using python from Udemy

competitive Programming(CP) is fun, CP is an exercise for your brain, it is a type of mental sport. It helps you to optimize the code in different ways and in a quick and efficient way.

If you want to learn how to write python programs like a pro , code python like a boss , solve real-world programs ,or do you want to build the skills needed to get your first python programming job ,then this course is for you.

This course is for complete beginners and covers some basic competitive problems using popular Python language. You will learn some basic concepts such as:

Big O Notation Concept

Binary Search algorithm

Seive of Erathosthenes algorithm.

frequency count of element in the list

finding the peak element index in a mountain array.

This course is also open to all learners who wish to gain an understanding of the basic concepts of competitive programming .By the end of this course, you guys will be able to write code that not only dramatically increases your productivity but it will be equally efficient and most important thing is that it will be fun . , most importantly start practicing the code regularly so that you guys have a grip of it .

Enroll now and learn how to write python programs like a pro.

Take care and enjoy the learning.

What's inside

Learning objectives

Basic competitive level programming concepts
Different types of algorithms
Time complexity and big o notation

Significance of competitive programming in job placements
How to solve programs in simple and in the most efficient way

Basic competitive level programming concepts
Different types of algorithms
Time complexity and big o notation
Significance of competitive programming in job placements
How to solve programs in simple and in the most efficient way

Syllabus

Introduction

Basic Competitive Programs

Big O Notation

Binary Search Algorithm

Traffic lights

Read about what's good

what should give you pause

and possible dealbreakers

Introduces Big O notation, which is essential for understanding algorithm efficiency and is a core concept in computer science curricula

Covers fundamental algorithms like Binary Search and Sieve of Eratosthenes, which are building blocks for solving more complex problems

Explores frequency counting and peak finding, which are common patterns in data analysis and algorithm design

Focuses on writing efficient code, which is a valuable skill for both competitive programming and real-world software development

Highlights the significance of competitive programming in job placements, suggesting it can improve problem-solving skills sought by employers

Reviews summary

Basic competitive programming concepts in python

According to learners who are absolute beginners, this course offers a positive introduction to basic competitive programming concepts using Python. They appreciate the coverage of foundational algorithms like Binary Search and the early introduction to Big O notation. However, some students found the course content to be too basic for those with prior experience or for serious competitive programming. There were also mentions that the course lacks sufficient practice problems and may not provide enough depth for real-world application or job preparation, despite the course description's claims. Overall, it seems best suited for someone truly starting from scratch.

Covers essential basic CP algorithms.

"The explanation of Binary Search was clear and helpful."

"I finally understand Big O notation after this course."

"The Sieve algorithm was introduced well."

Excellent starting point for novices.

"As a complete beginner, I found the concepts easy to grasp."

"This course is perfect if you're just starting competitive programming."

"It assumes no prior knowledge, which is great."

May not fully prepare for jobs as claimed.

"This course alone won't get you a programming job."

"The content is too basic for most technical interviews."

"Need much more practice and breadth for real-world application."

More practice problems are needed.

"Could use more coding exercises."

"I wish there were more practice problems to solidify understanding."

"Need external resources for sufficient practice."

Content is too introductory for some learners.

"I was hoping for more advanced problems."

"The course is very basic, doesn't go deep enough for real CP contests."

"Felt it only scratched the surface."

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 Beginner's guide to Competitive programming using python with these activities:

Review Python Fundamentals

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Strengthen your understanding of Python fundamentals to better grasp the more advanced concepts used in competitive programming.

Browse courses on Python Basics

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Review data types, operators, and control flow statements.
Practice writing simple Python functions.
Work through basic Python tutorials and exercises.

Review 'Grokking Algorithms'

Show steps

Gain a solid understanding of fundamental algorithms and data structures before tackling competitive programming problems.

View Grokking Algorithms, Second Edition on Amazon

Show steps

Read chapters on binary search, sorting, and graph algorithms.
Work through the examples and exercises in the book.
Implement the algorithms in Python.

Solve Binary Search Problems on LeetCode

Show steps

Improve your binary search skills by solving a variety of problems on LeetCode, a popular platform for competitive programming.

Show steps

Create a LeetCode account.
Search for binary search problems.
Solve at least 5 binary search problems of varying difficulty.

Four other activities

Expand to see all activities and additional details

Show all seven activities

Create a Big O Notation Cheat Sheet

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Solidify your understanding of Big O notation by creating a cheat sheet that summarizes the time complexity of common algorithms and data structures.

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Research the time complexity of common algorithms.
Organize the information into a clear and concise cheat sheet.
Share your cheat sheet with other students.

Implement Sieve of Eratosthenes in Python

Show steps

Deepen your understanding of the Sieve of Eratosthenes algorithm by implementing it in Python and optimizing its performance.

Show steps

Research the Sieve of Eratosthenes algorithm.
Write a Python function to implement the algorithm.
Test your implementation with different inputs.
Optimize your code for performance.

Review 'Competitive Programming 4'

Show steps

Expand your knowledge of advanced algorithms and data structures to excel in competitive programming contests.

View Competitive Programming 4 - Book 2: The Lower... on Amazon

Show steps

Read chapters on advanced algorithms and data structures.
Work through the examples and exercises in the book.
Implement the algorithms in Python.

Participate in a Codeforces Round

Show steps

Apply your competitive programming skills by participating in a Codeforces round, a popular online programming contest.

Show steps

Create a Codeforces account.
Register for an upcoming Codeforces round.
Solve as many problems as possible during the contest.
Analyze your performance after the contest.

Career center

Learners who complete Beginner's guide to Competitive programming using python will develop knowledge and skills that may be useful to these careers:

Competitive Programmer

The Competitive Programmer participates in programming contests, solving algorithmic challenges under time constraints. This course directly prepares individuals for such competitions, covering fundamental algorithms and data structures. The focus on Big O notation, binary search, and the sieve of Eratosthenes are essential tools in a competitive programmer's arsenal. This course is tailored for those who want to excel in competitive programming, as it hones problem-solving skills and coding efficiency in Python. The aim of the course is to transform a student into a Competitive Programmer that thinks and codes like a pro.

See salaries and explore the career path for Competitive Programmer

Algorithm Developer

The Algorithm Developer designs and implements algorithms for various applications, ranging from search engines to machine learning models. A deep understanding of algorithmic principles and optimization techniques is crucial, and a course focused on competitive programming helps build a foundation for excelling in this area. This course, with its emphasis on algorithms like binary search and the sieve of Eratosthenes, provides practical experience in implementing and optimizing algorithms. Learning about Big O notation in this course is essential for evaluating the efficiency of different algorithmic solutions. Those pursuing a career as an Algorithm Developer should enroll in this course to develop skills in algorithm design and analysis.

See salaries and explore the career path for Algorithm Developer

Software Engineer

A Software Engineer designs, develops, tests, and maintains software applications. This role requires a strong understanding of algorithms and data structures, critical for writing efficient code. A course on competitive programming, which emphasizes problem-solving and code optimization, helps build a foundation for efficiently tackling complex programming challenges faced as a Software Engineer. The course's coverage of Big O notation is invaluable, enabling one to analyze and improve the performance of software solutions. You should consider a course like this to hone your skills in algorithm design and optimization, especially with its focus on Python, a widely used language in software development.

See salaries and explore the career path for Software Engineer

Application Developer

The Application Developer creates software applications for computers or mobile devices. This role requires strong coding skills and knowledge of software development principles. A course focused on competitive programming helps build a foundation for writing efficient and optimized code, essential for creating high-performance applications. Learning about algorithms and data structures, as well as Big O notation, directly translates into better application performance. Pursuing a career as an Application Developer would benefit from improving these skills in Python.

See salaries and explore the career path for Application Developer

Machine Learning Engineer

A Machine Learning Engineer develops and implements machine learning models. This role requires a strong understanding of algorithms, data structures, and software engineering principles. A course focused on competitive programming helps build a foundation for optimizing machine learning algorithms and improving model performance. This course, with its coverage of Big O notation and algorithm design, provides tools for creating efficient machine learning solutions. Machine Learning Engineers may find this course to be essential in improving code.

See salaries and explore the career path for Machine Learning Engineer

Data Scientist

As a Data Scientist, you analyze large datasets to extract meaningful insights and develop predictive models. This often requires efficient data processing and algorithmic thinking. A course focused on competitive programming helps build a foundation for optimizing data manipulation tasks and developing efficient algorithms for data analysis. Learning about Big O notation, binary search, and frequency counting, as covered in this course, are useful for enhancing data processing pipelines. A Data Scientist would benefit from this course to improve their ability to implement efficient data analysis techniques in Python.

See salaries and explore the career path for Data Scientist

Data Engineer

The Data Engineer builds and maintains the infrastructure for data storage and processing. This role requires proficiency in programming, data structures, and algorithms to ensure efficient data pipelines. A course focused on competitive programming helps build a foundation for optimizing data processing and improving the performance of data infrastructure. Learning about Big O notation and algorithm optimization in the course can improve skills in designing scalable data solutions. Aspiring Data Engineers should consider a course to improve their ability to optimize data-related tasks.

See salaries and explore the career path for Data Engineer

Quantitative Analyst

The Quantitative Analyst, often working in the financial sector, develops mathematical models and algorithms for trading, risk management, and investment strategies. Efficient coding and a strong understanding of algorithms are essential for this role. A course focused on competitive programming helps build a foundation for optimizing computational tasks and implementing complex financial models. Big O notation, as covered in this course, is particularly critical for analyzing the performance of trading algorithms. Aspiring Quantitative Analysts should consider a course that enhances their algorithmic thinking and coding skills in Python.

See salaries and explore the career path for Quantitative Analyst

Game Developer

The Game Developer designs and develops video games, requiring proficiency in programming languages and a strong understanding of game algorithms. Game development involves optimizing performance and creating efficient solutions for complex game mechanics. A course focused on competitive programming helps build a foundation for enhancing problem-solving and algorithmic skills. The course's coverage of binary search and frequency counting can be applied to improve game mechanics and optimize game performance. For an aspiring Game Developer, taking a course can improve your understanding of efficient code implementation.

See salaries and explore the career path for Game Developer

Software Development Engineer in Test

A Software Development Engineer in Test (SDET) develops and executes tests to ensure software quality. A strong understanding of algorithms and problem-solving is valuable for designing effective test cases and identifying potential issues. A course focused on competitive programming helps build a foundation for analytical thinking and code optimization. A course that covers Big O notation and various algorithms helps one to design comprehensive test strategies. For those pursuing this career, this course will help to improve the underlying knowledge needed for this role.

See salaries and explore the career path for Software Development Engineer in Test

FinTech Engineer

The FinTech Engineer develops software and systems for the financial technology industry. This role requires a blend of financial knowledge and technical expertise, especially in areas like algorithmic trading and fraud detection. A course focused on competitive programming may be useful for enhancing problem-solving skills and improving the efficiency of financial algorithms. Concepts such as Big O notation and binary search, covered in this course, can aid in optimizing financial applications. For those pursuing a career in FinTech, they may value the course as it would help them to optimize code.

See salaries and explore the career path for FinTech Engineer

Robotics Engineer

A Robotics Engineer designs, builds, and programs robots for various applications. This role requires a strong understanding of algorithms, control systems, and programming. A course focused on competitive programming may be useful for enhancing problem-solving and algorithmic skills necessary for robot control and navigation. The course's exploration of algorithms can provide insights into efficient path planning and decision-making for robots. Robotics Engineers may find value in bolstering their programming abilities through a course.

See salaries and explore the career path for Robotics Engineer

Web Developer

As a Web Developer, you are responsible for building and maintaining websites and web applications. While not always directly related to competitive programming, optimizing website performance and implementing efficient algorithms for data handling are valuable skills. A course focused on competitive programming may be useful for improving problem-solving skills and enhancing the efficiency of web applications. The concepts of Big O notation and algorithm optimization covered in the course might be useful for optimizing web applications. A web developer may find value in supplementing their knowledge with a course that focuses on Python.

See salaries and explore the career path for Web Developer

Systems Architect

The Systems Architect designs and oversees the implementation of complex computer systems. While a broad understanding of technology and architecture is key, proficiency in algorithmic thinking is beneficial for optimizing system performance. A course focused on competitive programming may be useful for enhancing problem-solving skills and improving the efficiency of system components. The concepts of Big O notation covered in this course are valuable for evaluating system performance. Aspiring Systems Architects may increase their ability to optimize system performance by taking this course.

See salaries and explore the career path for Systems Architect

Platform Engineer

The Platform Engineer designs, develops, and maintains the underlying infrastructure that supports software applications. This role requires expertise in distributed systems, cloud computing, and automation. A course focused on competitive programming may be useful for enhancing problem-solving and algorithmic skills needed to optimize platform performance. This course, with its coverage of Big O notation and efficient algorithms, could assist in designing scalable platform solutions. A Platform Engineer would find value in bolstering their abilities through this course.

See salaries and explore the career path for Platform Engineer

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 Beginner's guide to Competitive programming using python.

Grokking Algorithms, Second Edition

Save

Provides a visual and intuitive introduction to algorithms. It uses diagrams and examples to explain complex concepts in a clear and accessible way. It good resource for beginners who want to develop a basic understanding of algorithms. It is helpful in providing background or prerequisite knowledge.

Grokking Algorithms, Second Edition

Paperback

Grokking Algorithms, Second Edition

Kindle Edition

Competitive Programming 4 - Book 2

Save

Is specifically designed for competitive programming. It covers a wide range of algorithms and techniques commonly used in programming contests. It provides a practical and hands-on approach to problem-solving, making it an excellent resource for students preparing for competitive programming competitions. It is more valuable as additional reading than as a current reference.

Competitive Programming 4 - Book 2: The Lower Bound...

Paperback

Beginner's guide to Competitive programming using python

What's inside

Learning objectives

Syllabus

Traffic lights

Save this course

Reviews summary

Basic competitive programming concepts in python

Activities

Career center

Reading list

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