Course Summary
This course introduces algorithmic thinking and its importance in solving real-world problems. Students will learn how to apply various algorithms to solve different types of problems and analyze their efficiency.Key Learning Points
- Learn fundamental algorithms and their applications
- Understand the importance of algorithmic thinking in problem-solving
- Analyze the efficiency of different algorithms
- Apply algorithmic thinking to solve real-world problems
Job Positions & Salaries of people who have taken this course might have
- USA: $75,000 - $120,000
- India: ₹400,000 - ₹1,200,000
- Spain: €25,000 - €40,000
- USA: $75,000 - $120,000
- India: ₹400,000 - ₹1,200,000
- Spain: €25,000 - €40,000
- USA: $60,000 - $100,000
- India: ₹300,000 - ₹800,000
- Spain: €20,000 - €35,000
- USA: $75,000 - $120,000
- India: ₹400,000 - ₹1,200,000
- Spain: €25,000 - €40,000
- USA: $60,000 - $100,000
- India: ₹300,000 - ₹800,000
- Spain: €20,000 - €35,000
- USA: $70,000 - $120,000
- India: ₹500,000 - ₹1,500,000
- Spain: €30,000 - €45,000
Related Topics for further study
Learning Outcomes
- Apply various algorithms to solve different types of problems
- Analyze the efficiency of different algorithms
- Develop algorithmic thinking skills to solve real-world problems
Prerequisites or good to have knowledge before taking this course
- Basic programming knowledge in Python
- Understanding of data structures
Course Difficulty Level
IntermediateCourse Format
- Online
- Self-paced
- Video Lectures
Similar Courses
- Algorithmic Toolbox
- Data Structures and Algorithms Specialization
Related Education Paths
Notable People in This Field
- Computer Scientist
- Computer Scientist
Related Books
Description
Experienced Computer Scientists analyze and solve computational problems at a level of abstraction that is beyond that of any particular programming language. This two-part course builds on the principles that you learned in our Principles of Computing course and is designed to train students in the mathematical concepts and process of "Algorithmic Thinking", allowing them to build simpler, more efficient solutions to real-world computational problems.
Outline
- Module 1 - Core Materials
- What is Algorithmic Thinking?
- Class structure
- Pseudo-code
- The small-world problem
- Graphs and representation
- Paths and distances
- Brute force
- What Is algorithm efficiency?
- Measuring efficiency
- Efficiency of brute force distance
- Number of steps of brute force distance
- Coding styles and standards - PoC
- Machine grading - PoC
- Plotting data - PoC
- Peer assessment - "We want a shrubbery!" - IIPP
- Class notes
- Coding notes
- Homework #1
- Modules 1 - Project and Application
- Project #1 Description
- Application #1 Description
- Application #1 Solution
- Module 2 - Core Materials
- Orders of growth
- Asymptotics
- Illustrating "Big O"
- Illustrating BFS
- Queues and boundary cases
- Pseudocode
- BFS running time - loose analysis
- BFS running time - tighter analysis
- BFS-based distance distribution
- Homework #2
- Module 2 - Project and Application
- Project #2 Description
- Application #2 Description
- Application #2 Solution
Summary of User Reviews
Algorithmic Thinking 1 is a well-structured and informative course that provides a strong foundation for learning algorithms and data structures. Many users found the course to be engaging and challenging, with a good balance of theory and practical exercises.Key Aspect Users Liked About This Course
The course content is comprehensive and covers a wide range of algorithms and data structures.Pros from User Reviews
- The instructors are knowledgeable and provide clear explanations.
- The assignments are challenging and help reinforce the concepts learned in the lectures.
- The forum community is helpful and supportive.
- The course provides a strong foundation for further study in computer science and related fields.
Cons from User Reviews
- Some users found the programming assignments to be too difficult or time-consuming.
- The course may be too technical for beginners or those without prior programming experience.
- The course could benefit from more interactive elements or visual aids to help illustrate concepts.
- The lectures can be lengthy and may require multiple viewings to fully understand.
Luay Nakhleh
4.7 Raiting
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