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Algorithmic Thinking Courses

Algorithmic Thinking courses can help you learn problem-solving techniques, data structures, algorithm design, and complexity analysis. You can build skills in logical reasoning, optimization strategies, and analyzing algorithm efficiency. Many courses introduce tools like Python and R for implementing algorithms, along with frameworks for analyzing data sets and solving computational problems.


Popular Algorithmic Thinking Courses and Certifications


  • Status: Free Trial
    Free Trial
    R

    Rice University

    Algorithmic Thinking (Part 2)

    Skills you'll gain: Computational Thinking, Algorithms, Theoretical Computer Science, Bioinformatics, Data Structures, Big Data, Python Programming, Data Analysis, Machine Learning Algorithms, Analysis

    4.7
    Rating, 4.7 out of 5 stars
    ·
    219 reviews

    Intermediate · Course · 1 - 4 Weeks

  • Status: Free Trial
    Free Trial
    R

    Rice University

    Algorithmic Thinking (Part 1)

    Skills you'll gain: Graph Theory, Algorithms, Computational Thinking, Data Analysis, Data Structures, Theoretical Computer Science, Network Analysis, Analysis, Programming Principles, Python Programming, Computer Programming, Program Development

    4.6
    Rating, 4.6 out of 5 stars
    ·
    384 reviews

    Intermediate · Course · 1 - 4 Weeks

  • Status: New
    New
    Status: Preview
    Preview
    U

    University of Michigan

    Leveraging GenAI to Develop Critical Thinking Skills

    Skills you'll gain: Critical Thinking, Generative AI, AI Enablement, Decision Making, Information Management

    Beginner · Course · 1 - 3 Months

  • Status: Free Trial
    Free Trial
    U

    University of Glasgow

    Computational Thinking with JavaScript

    Skills you'll gain: Computational Thinking, JSON, Application Deployment, Data Structures, Javascript, Application Development, HTML and CSS, Data Analysis, Code Review, Software Development, Data Visualization Software, Web Development, Web Applications, Scripting, Prototyping, Data Processing, Programming Principles, Unsupervised Learning, Front-End Web Development, Computer Programming

    Beginner · Specialization · 3 - 6 Months

  • Status: Free Trial
    Free Trial
    U

    University of Colorado System

    Computational Thinking with Beginning C Programming

    Skills you'll gain: Computational Thinking, File I/O, Data Collection, Simulations, Data Analysis, Microsoft Visual Studio, C (Programming Language), Statistical Analysis, Automation, Program Development, Data Structures, Programming Principles, Algorithms, Computer Programming, Theoretical Computer Science, Data Storage, Descriptive Statistics, Data Visualization Software, Debugging

    4.6
    Rating, 4.6 out of 5 stars
    ·
    433 reviews

    Beginner · Specialization · 3 - 6 Months

  • Status: New
    New
    P

    Packt

    Algorithmic Problem Solving

    Skills you'll gain: Cryptography

    Beginner · Course · 1 - 4 Weeks

What brings you to Coursera today?

  • Status: Free Trial
    Free Trial
    R

    Rice University

    Principles of Computing (Part 2)

    Skills you'll gain: Computational Thinking, Programming Principles, Algorithms, Pseudocode, Data Structures, Theoretical Computer Science, Computer Programming, Python Programming, Computer Science, Software Design Patterns, Debugging, Game Theory, Mathematical Modeling, Test Case

    4.8
    Rating, 4.8 out of 5 stars
    ·
    365 reviews

    Intermediate · Course · 1 - 4 Weeks

  • Status: Free Trial
    Free Trial
    U

    University of California San Diego

    Data Structures and Algorithms

    Skills you'll gain: Data Structures, Graph Theory, Algorithms, Program Development, Bioinformatics, Data Storage, Development Testing, Theoretical Computer Science, Computational Thinking, Network Analysis, Test Case, Programming Principles, Computer Programming, Python Programming, C and C++, Java, Rust (Programming Language), Javascript, Software Testing, Debugging

    4.6
    Rating, 4.6 out of 5 stars
    ·
    17K reviews

    Intermediate · Specialization · 3 - 6 Months

  • Status: Free Trial
    Free Trial
    S

    Stanford University

    Algorithms

    Skills you'll gain: Data Structures, Graph Theory, Algorithms, Bioinformatics, Theoretical Computer Science, Network Model, Programming Principles, Social Network Analysis, Network Analysis, Computational Thinking, Analysis, Computer Science, Network Routing, Probability, Pseudocode, Computational Logic, Operations Research

    4.8
    Rating, 4.8 out of 5 stars
    ·
    6K reviews

    Intermediate · Specialization · 3 - 6 Months

  • Status: New
    New
    Status: Free Trial
    Free Trial
    C

    Coursera

    Optimize Agentic AI: Algorithms for Peak Performance

    Skills you'll gain: Proposal Writing, Performance Tuning, Agentic systems, Computational Thinking, Performance Analysis, Computational Logic

    Intermediate · Course · 1 - 4 Weeks

  • Status: Free Trial
    Free Trial
    D

    Duke University

    Introduction to Logic and Critical Thinking

    Skills you'll gain: Deductive Reasoning, Critical Thinking, Logical Reasoning, Analysis, Diagram Design, Probability, Sampling (Statistics), Persuasive Communication, Research, Sample Size Determination, Case Studies, Oral Expression, Correlation Analysis, Communication, Scientific Methods, Information Architecture, Interactive Learning, Business Communication

    4.6
    Rating, 4.6 out of 5 stars
    ·
    3.7K reviews

    Beginner · Specialization · 3 - 6 Months

  • Status: Free Trial
    Free Trial
    F

    Fractal Analytics

    Generative AI for Developers

    Skills you'll gain: Prompt Engineering, Responsible AI, Generative AI, Generative Model Architectures, Code Review, Data Ethics, Artificial Intelligence, Object Oriented Programming (OOP), Large Language Modeling, Machine Learning Methods, Artificial Intelligence and Machine Learning (AI/ML), AI Enablement, Artificial Neural Networks, Maintainability, Computer Programming, Data Cleansing, Debugging, Problem Solving, Critical Thinking, Data Analysis

    4.6
    Rating, 4.6 out of 5 stars
    ·
    194 reviews

    Beginner · Specialization · 1 - 3 Months

Searches related to algorithmic thinking

algorithmic thinking (part 1)
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In summary, here are 10 of our most popular algorithmic thinking courses

  • Algorithmic Thinking (Part 2): Rice University
  • Algorithmic Thinking (Part 1): Rice University
  • Leveraging GenAI to Develop Critical Thinking Skills: University of Michigan
  • Computational Thinking with JavaScript: University of Glasgow
  • Computational Thinking with Beginning C Programming: University of Colorado System
  • Algorithmic Problem Solving: Packt
  • Principles of Computing (Part 2): Rice University
  • Data Structures and Algorithms: University of California San Diego
  • Algorithms: Stanford University
  • Optimize Agentic AI: Algorithms for Peak Performance: Coursera

Skills you can learn in Algorithms

Graphs (22)
Mathematical Optimization (21)
Computer Program (20)
Data Structure (19)
Problem Solving (19)
Algebra (12)
Computer Vision (10)
Discrete Mathematics (10)
Graph Theory (10)
Image Processing (10)
Linear Algebra (10)
Reinforcement Learning (10)

Frequently Asked Questions about Algorithmic Thinking

Algorithmic thinking is a problem-solving approach that involves breaking down complex problems into manageable parts and developing step-by-step solutions. This method is crucial in various fields, including computer science, data analysis, and artificial intelligence, as it enables individuals to create efficient algorithms that can process information and automate tasks. Understanding algorithmic thinking not only enhances logical reasoning but also fosters creativity in finding innovative solutions to real-world challenges.‎

With a foundation in algorithmic thinking, you can explore various career paths. Potential job roles include software developer, data analyst, systems analyst, and machine learning engineer. These positions often require strong analytical skills and the ability to design algorithms that solve specific problems. Additionally, industries such as finance, healthcare, and technology increasingly seek professionals who can apply algorithmic thinking to improve processes and drive innovation.‎

To effectively learn algorithmic thinking, you should focus on developing several key skills. These include logical reasoning, problem-solving, programming languages (such as Python or Java), and an understanding of data structures and algorithms. Familiarity with computational concepts and the ability to analyze and optimize algorithms are also essential. Building these skills will empower you to tackle complex problems and create efficient solutions in various contexts.‎

There are several online courses available that can help you learn algorithmic thinking. Notable options include Algorithmic Thinking (Part 1) and Algorithmic Thinking (Part 2). These courses provide a structured approach to understanding the principles of algorithm design and problem-solving techniques, making them suitable for beginners and those looking to enhance their skills.‎

Yes. You can start learning algorithmic thinking on Coursera for free in two ways:

  1. Preview the first module of many algorithmic thinking courses at no cost. This includes video lessons, readings, graded assignments, and Coursera Coach (where available).
  2. Start a 7-day free trial for Specializations or Coursera Plus. This gives you full access to all course content across eligible programs within the timeframe of your trial.

If you want to keep learning, earn a certificate in algorithmic thinking, or unlock full course access after the preview or trial, you can upgrade or apply for financial aid.‎

To learn algorithmic thinking, start by enrolling in introductory courses that cover the basics of algorithms and problem-solving techniques. Engage in practical exercises and projects that challenge you to apply what you've learned. Additionally, practice coding regularly and participate in online coding challenges to reinforce your skills. Joining study groups or online forums can also provide support and motivation as you progress.‎

Typical topics covered in algorithmic thinking courses include algorithm design, data structures, complexity analysis, recursion, and problem-solving strategies. You may also encounter practical applications of algorithms in areas such as sorting, searching, and optimization. These topics provide a comprehensive foundation that prepares you for real-world challenges in various fields.‎

For training and upskilling employees in algorithmic thinking, courses like Computational Thinking with Beginning C Programming Specialization and Computational Thinking with JavaScript Specialization can be particularly beneficial. These programs are designed to enhance problem-solving skills and foster a deeper understanding of algorithmic concepts, making them ideal for workforce development.‎

This FAQ content has been made available for informational purposes only. Learners are advised to conduct additional research to ensure that courses and other credentials pursued meet their personal, professional, and financial goals.

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