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    Results for "algorithms"

    • U

      University of Washington

      Machine Learning

      Skills you'll gain: Regression Analysis, Applied Machine Learning, Feature Engineering, Machine Learning, Image Analysis, Unsupervised Learning, Artificial Intelligence and Machine Learning (AI/ML), Predictive Modeling, Classification And Regression Tree (CART), Supervised Learning, Bayesian Statistics, Statistical Modeling, Artificial Intelligence, Deep Learning, Data Mining, Computer Vision, Statistical Machine Learning, Predictive Analytics, Text Mining, Machine Learning Algorithms

      4.6
      Rating, 4.6 out of 5 stars
      ·
      16K reviews

      Intermediate · Specialization · 3 - 6 Months

    • V

      Vanderbilt University

      MATLAB Programming for Engineers and Scientists

      Skills you'll gain: Data Visualization, Image Analysis, Data Visualization Software, Matlab, Algorithms, Machine Learning Methods, User Interface (UI), Applied Machine Learning, Object Oriented Programming (OOP), Statistical Methods, Mathematical Software, Engineering Calculations, Data Analysis, Data Processing, Engineering Analysis, Computer Programming, Programming Principles, UI Components, Software Design, Debugging

      4.8
      Rating, 4.8 out of 5 stars
      ·
      18K reviews

      Beginner · Specialization · 3 - 6 Months

    • I

      IBM

      Machine Learning with Python

      Skills you'll gain: Supervised Learning, Feature Engineering, Jupyter, Unsupervised Learning, Scikit Learn (Machine Learning Library), Python Programming, Predictive Modeling, Machine Learning, Dimensionality Reduction, Classification And Regression Tree (CART), Matplotlib, NumPy, Regression Analysis, Statistical Modeling

      4.7
      Rating, 4.7 out of 5 stars
      ·
      17K reviews

      Intermediate · Course · 1 - 3 Months

    • U

      University of California San Diego

      Introduction to Discrete Mathematics for Computer Science

      Skills you'll gain: Graph Theory, Logical Reasoning, Combinatorics, Computational Logic, Deductive Reasoning, Cryptography, Probability, Key Management, Computational Thinking, Encryption, Network Analysis, Public Key Cryptography Standards (PKCS), Algorithms, Theoretical Computer Science, Python Programming, Data Structures, Cybersecurity, Arithmetic, Computer Programming, Mathematical Modeling

      4.5
      Rating, 4.5 out of 5 stars
      ·
      3.6K reviews

      Beginner · Specialization · 3 - 6 Months

    • D

      DeepLearning.AI

      Linear Algebra for Machine Learning and Data Science

      Skills you'll gain: Linear Algebra, NumPy, Dimensionality Reduction, Machine Learning Methods, Jupyter, Data Manipulation, Data Science, Applied Mathematics, Python Programming, Artificial Intelligence

      4.6
      Rating, 4.6 out of 5 stars
      ·
      2K reviews

      Intermediate · Course · 1 - 4 Weeks

    • H

      Hebrew University of Jerusalem

      Build a Modern Computer from First Principles: From Nand to Tetris (Project-Centered Course)

      Skills you'll gain: Computer Architecture, Computer Hardware, Computational Logic, Computer Programming, System Design and Implementation, Technical Design, Software Design, Program Development, Debugging, Verification And Validation, Development Environment

      4.9
      Rating, 4.9 out of 5 stars
      ·
      3.7K reviews

      Mixed · Course · 1 - 3 Months

    • I

      Imperial College London

      Mathematics for Machine Learning: Linear Algebra

      Skills you'll gain: Linear Algebra, NumPy, Applied Mathematics, Jupyter, Machine Learning Methods, Algorithms, Data Manipulation, Python Programming

      4.7
      Rating, 4.7 out of 5 stars
      ·
      12K reviews

      Beginner · Course · 1 - 3 Months

    • L

      LearnQuest

      Ethics in the Age of AI

      Skills you'll gain: Data Ethics, Predictive Modeling, OpenAI, Algorithms, Data Collection, Machine Learning, Predictive Analytics, Artificial Intelligence, Information Privacy, Game Theory, Large Language Modeling, Ethical Standards And Conduct, Personally Identifiable Information, Statistical Modeling, Machine Learning Algorithms, Analytical Skills, Artificial Intelligence and Machine Learning (AI/ML), Analysis, Data Security, Business Ethics

      4.6
      Rating, 4.6 out of 5 stars
      ·
      754 reviews

      Beginner · Specialization · 3 - 6 Months

    • G

      Google Cloud

      Digital Transformation Using AI/ML with Google Cloud

      Skills you'll gain: Serverless Computing, Digital Transformation, Cloud Services, Data Ethics, Cloud Infrastructure, Google Cloud Platform, Application Programming Interface (API), Applied Machine Learning, Hybrid Cloud Computing, Infrastructure As A Service (IaaS), Cloud Computing, Public Cloud, Technical Management, Business Transformation, Containerization, Cloud-Native Computing, Multi-Cloud, IT Management, Machine Learning, Software As A Service

      4.7
      Rating, 4.7 out of 5 stars
      ·
      7.3K reviews

      Beginner · Specialization · 1 - 3 Months

    • Status: Free
      Free
      S

      Stanford University

      Cryptography I

      Skills you'll gain: Cryptography, Data Encryption Standard, Encryption, Key Management, Advanced Encryption Standard (AES), Public Key Cryptography Standards (PKCS), Cybersecurity, Authentications, Data Integrity, Secure Coding, Algorithms

      4.8
      Rating, 4.8 out of 5 stars
      ·
      4.4K reviews

      Mixed · Course · 1 - 3 Months

    • U

      University of Pennsylvania

      AI For Business

      Skills you'll gain: AI Personalization, Generative AI, Data Ethics, HR Tech, Data Governance, Big Data, Machine Learning, Personally Identifiable Information, Data Security, Governance, Business Strategy, Human Resources, Organizational Strategy, Customer Data Management, Credit Risk, Risk Management, Tensorflow, Personalized Service, Data-Driven Decision-Making, People Management

      4.7
      Rating, 4.7 out of 5 stars
      ·
      1.3K reviews

      Beginner · Specialization · 3 - 6 Months

    • D

      Duke University

      Introductory C Programming

      Skills you'll gain: Debugging, Maintainability, Programming Principles, Algorithms, Software Testing, Program Development, C (Programming Language), Pseudocode, Computational Thinking, Software Engineering, Simulations, System Programming, Data Structures, Software Development, Computer Programming, Command-Line Interface, Operating Systems, Development Environment, User Interface (UI), Data Import/Export

      4.6
      Rating, 4.6 out of 5 stars
      ·
      7.3K reviews

      Beginner · Specialization · 3 - 6 Months

    Searches related to algorithms

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    algorithms, part i
    algorithms for searching, sorting, and indexing
    algorithms, data collection, and starting to code
    algorithms, part ii
    algorithms for dna sequencing
    algorithms for battery management systems
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    1…101112…118

    In summary, here are 10 of our most popular algorithms courses

    • Machine Learning: University of Washington
    • MATLAB Programming for Engineers and Scientists: Vanderbilt University
    • Machine Learning with Python: IBM
    • Introduction to Discrete Mathematics for Computer Science: University of California San Diego
    • Linear Algebra for Machine Learning and Data Science: DeepLearning.AI
    • Build a Modern Computer from First Principles: From Nand to Tetris (Project-Centered Course): Hebrew University of Jerusalem
    • Mathematics for Machine Learning: Linear Algebra: Imperial College London
    • Ethics in the Age of AI: LearnQuest
    • Digital Transformation Using AI/ML with Google Cloud: Google Cloud
    • Cryptography I: Stanford University

    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 Algorithms

    Coursera's algorithms courses offer valuable skills that are foundational in computer science:

    • Understanding and implementing basic and advanced algorithms
    • Analyzing algorithm efficiency and complexity
    • Designing data structures to optimize software applications
    • Problem-solving techniques for tackling computational challenges
    • Application of algorithms in real-world scenarios, like sorting, searching, and graph operations
    • Hands-on programming skills to implement algorithms in various programming languages ‎

    Algorithm courses on Coursera are suitable for all experience levels:

    • Beginners can start with courses that introduce basic concepts and simple algorithms.
    • Those with some background might choose intermediate courses focusing on more complex algorithms and their applications.
    • Advanced courses are suitable for those who have a strong foundation in computer science and want to deepen their understanding of algorithmic theory and applications.‎

    Coursera offers several ways to validate your skills in algorithms:

    • Professional certificates designed to help build and showcase your analytical skills in technical roles.
    • Specialized course certificates that document your learning in particular aspects of algorithms, such as cryptographic methods or data structures.
    • Credentials developed in partnership with respected computer science institutions, adding recognized value to your educational achievements.‎

    Skills in algorithms are crucial for a variety of technical careers:

    • Software Engineer, developing efficient, scalable software
    • Data Analyst, using algorithms to process and analyze large data sets
    • Machine Learning Engineer, applying algorithms to build and train intelligent systems
    • Operations Research Analyst, optimizing and improving business processes
    • Academic Researcher, contributing to the advancement of computational theories and practices‎
    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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