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    Results for "algorithms"

    • Status: New
      New
      U

      University of California, Santa Cruz

      Go and C++: Programming in Two Successor Languages of C

      Skills you'll gain: C++ (Programming Language), Go (Programming Language), Data Structures, Object Oriented Programming (OOP), Software Design Patterns, Debugging, Object Oriented Design, Programming Principles, Unit Testing, Algorithms, C (Programming Language), Program Development, Integrated Development Environments, Computer Programming, Software Testing, Computer Science, Graph Theory, File Management, Artificial Intelligence, Integration Testing

      4.4
      Rating, 4.4 out of 5 stars
      ·
      2.5K reviews

      Intermediate · Specialization · 3 - 6 Months

    • D

      DeepLearning.AI

      Mathematics for Machine Learning and Data Science

      Skills you'll gain: Descriptive Statistics, Bayesian Statistics, Statistical Hypothesis Testing, Probability & Statistics, Sampling (Statistics), Probability Distribution, Probability, Linear Algebra, Statistical Inference, Applied Mathematics, NumPy, Calculus, Dimensionality Reduction, Numerical Analysis, Mathematical Modeling, Machine Learning, Machine Learning Methods, Python Programming, Jupyter, Data Manipulation

      4.6
      Rating, 4.6 out of 5 stars
      ·
      2.7K reviews

      Intermediate · Specialization · 1 - 3 Months

    • U

      University of California San Diego

      Advanced Data Structures in Java

      Skills you'll gain: Graph Theory, Data Structures, Java Programming, Java, Object Oriented Design, Software Design, Algorithms, Theoretical Computer Science, Maintainability, Object Oriented Programming (OOP), Network Routing, Computational Thinking, Application Development, Debugging

      4.8
      Rating, 4.8 out of 5 stars
      ·
      1.2K reviews

      Intermediate · Course · 1 - 3 Months

    • Status: Free
      Free
      S

      Stanford University

      Game Theory

      Skills you'll gain: Game Theory, Strategic Decision-Making, Mathematical Modeling, Graph Theory, Bayesian Statistics, Behavioral Economics, Probability, Economics, Markov Model, Algorithms

      4.6
      Rating, 4.6 out of 5 stars
      ·
      4.8K reviews

      Beginner · Course · 1 - 3 Months

    • I

      IBM

      IBM Machine Learning

      Skills you'll gain: Exploratory Data Analysis, Feature Engineering, Unsupervised Learning, Supervised Learning, Generative AI, Regression Analysis, Dimensionality Reduction, Reinforcement Learning, Deep Learning, Data Analysis, Statistical Inference, Applied Machine Learning, Predictive Modeling, Data Processing, Statistical Analysis, Data Access, Anomaly Detection, Machine Learning Algorithms, Classification And Regression Tree (CART), Scikit Learn (Machine Learning Library)

      Build toward a degree

      4.6
      Rating, 4.6 out of 5 stars
      ·
      3.1K reviews

      Intermediate · Professional Certificate · 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

    • D

      DeepLearning.AI

      Unsupervised Learning, Recommenders, Reinforcement Learning

      Skills you'll gain: Unsupervised Learning, Machine Learning Methods, Artificial Intelligence and Machine Learning (AI/ML), Applied Machine Learning, Data Ethics, Machine Learning, Machine Learning Algorithms, Supervised Learning, Reinforcement Learning, Statistical Machine Learning, Artificial Neural Networks, Deep Learning, Anomaly Detection, Dimensionality Reduction, Algorithms, Collaborative Software

      4.9
      Rating, 4.9 out of 5 stars
      ·
      4.7K reviews

      Beginner · Course · 1 - 4 Weeks

    • A

      Alberta Machine Intelligence Institute

      Machine Learning Algorithms: Supervised Learning Tip to Tail

      Skills you'll gain: Supervised Learning, Machine Learning Algorithms, Applied Machine Learning, Jupyter, Machine Learning, Classification And Regression Tree (CART), Scikit Learn (Machine Learning Library), Business Solutions, Python Programming, Regression Analysis, Performance Analysis, Feature Engineering, Data Processing, Performance Metric

      4.7
      Rating, 4.7 out of 5 stars
      ·
      413 reviews

      Mixed · Course · 1 - 4 Weeks

    • 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

    • R

      Rice University

      Algorithmic Thinking (Part 2)

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

      4.7
      Rating, 4.7 out of 5 stars
      ·
      216 reviews

      Intermediate · Course · 1 - 4 Weeks

    • U

      University of California San Diego

      Object Oriented Java Programming: Data Structures and Beyond

      Skills you'll gain: Unit Testing, Growth Mindedness, Data Structures, Graph Theory, Event-Driven Programming, Interactive Data Visualization, Java, Network Analysis, Object Oriented Programming (OOP), Technical Communication, Development Testing, User Interface (UI), Java Programming, Software Testing, Computer Programming, Adaptability, Object Oriented Design, Performance Tuning, Algorithms, Software Design

      4.7
      Rating, 4.7 out of 5 stars
      ·
      7.2K reviews

      Intermediate · Specialization · 3 - 6 Months

    • I

      IBM

      IBM Introduction to Machine Learning

      Skills you'll gain: Exploratory Data Analysis, Feature Engineering, Unsupervised Learning, Supervised Learning, Regression Analysis, Dimensionality Reduction, Statistical Inference, Predictive Modeling, Data Processing, Data Access, Anomaly Detection, Machine Learning, Machine Learning Algorithms, Classification And Regression Tree (CART), Scikit Learn (Machine Learning Library), Statistical Analysis, Data Analysis, Statistical Modeling, Applied Machine Learning, Data Cleansing

      4.6
      Rating, 4.6 out of 5 stars
      ·
      2.9K reviews

      Intermediate · Specialization · 3 - 6 Months

    Searches related to algorithms

    algorithms specialization
    algorithms, part i
    algorithms for searching, sorting, and indexing
    algorithms, data collection, and starting to code
    algorithms for dna sequencing
    algorithms for battery management systems
    algorithms on graphs
    algorithms on strings
    1…101112…119

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

    • Go and C++: Programming in Two Successor Languages of C: University of California, Santa Cruz
    • Mathematics for Machine Learning and Data Science: DeepLearning.AI
    • Advanced Data Structures in Java: University of California San Diego
    • Game Theory: Stanford University
    • IBM Machine Learning: IBM
    • MATLAB Programming for Engineers and Scientists: Vanderbilt University
    • Unsupervised Learning, Recommenders, Reinforcement Learning: DeepLearning.AI
    • Machine Learning Algorithms: Supervised Learning Tip to Tail: Alberta Machine Intelligence Institute
    • Machine Learning with Python: IBM
    • Algorithmic Thinking (Part 2): Rice 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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