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    Results for "scheduling algorithms"

    • 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

    • University of California San Diego

      Data Structures

      Skills you'll gain: Data Structures, Algorithms, Data Storage, Programming Principles, Computer Programming, C++ (Programming Language), Theoretical Computer Science, File Management

      4.6
      Rating, 4.6 out of 5 stars
      ·
      5.5K reviews

      Intermediate · Course · 1 - 3 Months

    • 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

    • University of Illinois Urbana-Champaign

      Cloud Computing Concepts, Part 1

      Skills you'll gain: Distributed Computing, Data Store, NoSQL, Operating Systems, Apache Cassandra, Cloud Computing, Systems Design, Apache Hadoop, Database Theory, Algorithms, Theoretical Computer Science, Scalability, C++ (Programming Language), Network Protocols

      4.3
      Rating, 4.3 out of 5 stars
      ·
      1.1K reviews

      Beginner · Course · 1 - 3 Months

    • Duke University

      Java Programming: Solving Problems with Software

      Skills you'll gain: Debugging, Java, Algorithms, Statistical Analysis, Software Design, Computer Programming, Integrated Development Environments, Data Processing, Object Oriented Programming (OOP), Data Analysis, Software Testing

      4.6
      Rating, 4.6 out of 5 stars
      ·
      8K reviews

      Beginner · Course · 1 - 3 Months

    • DeepLearning.AI

      Probability & Statistics for Machine Learning & Data Science

      Skills you'll gain: Descriptive Statistics, Bayesian Statistics, Statistical Hypothesis Testing, Probability & Statistics, Sampling (Statistics), Probability Distribution, Probability, Statistical Inference, A/B Testing, Statistical Analysis, Statistical Machine Learning, Data Science, Exploratory Data Analysis, Statistical Visualization

      4.6
      Rating, 4.6 out of 5 stars
      ·
      557 reviews

      Intermediate · Course · 1 - 4 Weeks

    • Stanford University

      Shortest Paths Revisited, NP-Complete Problems and What To Do About Them

      Skills you'll gain: Algorithms, Graph Theory, Theoretical Computer Science, Computational Thinking, Data Structures, Operations Research, Design Strategies

      4.8
      Rating, 4.8 out of 5 stars
      ·
      823 reviews

      Intermediate · Course · 1 - 4 Weeks

    • IBM

      IBM Introduction to Machine Learning

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

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

      Intermediate · Specialization · 3 - 6 Months

    • University of California San Diego

      Mathematical Thinking in Computer Science

      Skills you'll gain: Logical Reasoning, Computational Logic, Deductive Reasoning, Computational Thinking, Theoretical Computer Science, Algorithms, Python Programming, Computer Programming, Computer Science, Program Development

      4.4
      Rating, 4.4 out of 5 stars
      ·
      2.3K reviews

      Beginner · Course · 1 - 3 Months

    • Johns Hopkins University

      Algorithms for DNA Sequencing

      Skills you'll gain: Bioinformatics, Molecular Biology, Computational Thinking, Data Structures, Python Programming, Data Analysis, Algorithms, Life Sciences

      4.7
      Rating, 4.7 out of 5 stars
      ·
      921 reviews

      Mixed · Course · 1 - 4 Weeks

    • 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, Image Analysis, Artificial Intelligence

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

      Intermediate · Course · 1 - 4 Weeks

    • DeepLearning.AI

      Convolutional Neural Networks

      Skills you'll gain: Computer Vision, Image Analysis, Deep Learning, Artificial Neural Networks, Tensorflow, Applied Machine Learning, PyTorch (Machine Learning Library), Artificial Intelligence, Data Processing, Algorithms

      4.9
      Rating, 4.9 out of 5 stars
      ·
      42K reviews

      Intermediate · Course · 1 - 4 Weeks

    1…91011…136

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

    • Mathematics for Machine Learning and Data Science: DeepLearning.AI
    • Data Structures: University of California San Diego
    • Unsupervised Learning, Recommenders, Reinforcement Learning: DeepLearning.AI
    • Cloud Computing Concepts, Part 1: University of Illinois Urbana-Champaign
    • Java Programming: Solving Problems with Software: Duke University
    • Probability & Statistics for Machine Learning & Data Science: DeepLearning.AI
    • Shortest Paths Revisited, NP-Complete Problems and What To Do About Them: Stanford University
    • IBM Introduction to Machine Learning: IBM
    • Mathematical Thinking in Computer Science: University of California San Diego
    • Algorithms for DNA Sequencing: Johns Hopkins University

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