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  • Probabilistic Logic

Results for "probabilistic+logic"


  • Status: Preview
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    U

    University of Zurich

    An Intuitive Introduction to Probability

    Skills you'll gain: Probability, Probability Distribution, Probability & Statistics, Descriptive Statistics, Statistical Methods, Applied Mathematics, Finance, Correlation Analysis

    4.8
    Rating, 4.8 out of 5 stars
    ·
    1.9K reviews

    Beginner · Course · 1 - 3 Months

  • Status: Free Trial
    Free Trial
    I

    Imperial College London

    Probabilistic Deep Learning with TensorFlow 2

    Skills you'll gain: Generative AI, Tensorflow, Autoencoders, Generative Model Architectures, Bayesian Network, Deep Learning, Image Analysis, Bayesian Statistics, Model Optimization, Probability Distribution, Model Training, Sampling (Statistics), Data Transformation

    4.7
    Rating, 4.7 out of 5 stars
    ·
    109 reviews

    Advanced · Course · 1 - 3 Months

  • Status: New
    New
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    C

    Coursera

    Building Reliable LLM Systems

    Skills you'll gain: LLM Application, Model Evaluation, Large Language Modeling, Retrieval-Augmented Generation, Vector Databases, MLOps (Machine Learning Operations), Performance Tuning, Debugging, Performance Testing, Statistical Methods, Query Languages, SQL, Statistical Hypothesis Testing, Statistical Analysis, Artificial Intelligence and Machine Learning (AI/ML), Data-Driven Decision-Making, Python Programming

    Intermediate · Course · 1 - 3 Months

  • Status: Free Trial
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    D

    DeepLearning.AI

    Probability & Statistics for Machine Learning & Data Science

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

    4.6
    Rating, 4.6 out of 5 stars
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    685 reviews

    Intermediate · Course · 1 - 4 Weeks

  • Status: Free Trial
    Free Trial
    B

    Birla Institute of Technology & Science, Pilani

    Logic for Computer Science

    Skills you'll gain: Computational Logic, Logical Reasoning, Deductive Reasoning, Theoretical Computer Science, Analytical Skills, Programming Principles, Computer Science, Data Analysis, Computer Programming, Algorithms, Verification And Validation, Software Development, Machine Learning

    Build toward a degree

    Beginner · Course · 1 - 3 Months

  • Status: Free Trial
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    S

    Stanford University

    Probabilistic Graphical Models 2: Inference

    Skills you'll gain: Bayesian Network, Machine Learning Methods, Statistical Inference, Markov Model, Statistical Machine Learning, Graph Theory, Sampling (Statistics), Applied Machine Learning, Statistical Methods, Probability & Statistics, Algorithms, Probability Distribution, Machine Learning Algorithms

    4.6
    Rating, 4.6 out of 5 stars
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    489 reviews

    Advanced · Course · 1 - 3 Months

  • Status: Preview
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    É

    École Polytechnique

    Aléatoire : une introduction aux probabilités - Partie 1

    Skills you'll gain: Probability, Probability Distribution, Probability & Statistics, Simulations, Statistical Methods, Interactive Data Visualization, Mathematical Theory & Analysis, Applied Mathematics, Correlation Analysis

    4.5
    Rating, 4.5 out of 5 stars
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    105 reviews

    Mixed · Course · 1 - 3 Months

  • Status: Free Trial
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    S

    Stanford University

    Probabilistic Graphical Models 1: Representation

    Skills you'll gain: Bayesian Network, Decision Intelligence, Bayesian Statistics, Graph Theory, Probability Distribution, Network Model, Statistical Modeling, Markov Model, Decision Support Systems, Probability & Statistics, Network Analysis, Dependency Analysis

    4.6
    Rating, 4.6 out of 5 stars
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    1.4K reviews

    Advanced · Course · 1 - 3 Months

  • Status: Preview
    Preview
    S

    Stanford University

    Introduction to Logic

    Skills you'll gain: Logical Reasoning, Computational Logic, Deductive Reasoning, Computational Thinking, Problem Solving, Mathematics and Mathematical Modeling, Business Logic

    4.4
    Rating, 4.4 out of 5 stars
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    655 reviews

    Intermediate · Course · 1 - 3 Months

  • Status: Free Trial
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    J

    Johns Hopkins University

    Foundations of Probability and Random Variables

    Skills you'll gain: R Programming, Statistical Analysis, Statistical Methods, Combinatorics, Statistical Programming, Data Analysis, Probability, Probability Distribution, Applied Machine Learning, Probability & Statistics, Bayesian Statistics, Data Science, Simulations

    Intermediate · Course · 1 - 3 Months

  • Status: Preview
    Preview
    U

    University of Leeds

    An Introduction to Logic for Computer Science

    Skills you'll gain: Logical Reasoning, Deductive Reasoning, Computational Logic, Computational Thinking, Algorithms, Artificial Intelligence, Cryptography, Graph Theory

    4.6
    Rating, 4.6 out of 5 stars
    ·
    33 reviews

    Beginner · Course · 1 - 4 Weeks

  • Status: Free Trial
    Free Trial
    D

    Deep Teaching Solutions

    Critical Thinking & Logic: Real-World Skills

    Skills you'll gain: Deductive Reasoning, Logical Reasoning, Critical Thinking and Problem Solving, Critical Thinking, Creative Problem-Solving, Problem Solving, Analytical Skills, Creative Thinking, Innovation, Decision Making, Analysis, Persuasive Communication, Verbal Communication Skills, Psychology

    4.8
    Rating, 4.8 out of 5 stars
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    40 reviews

    Beginner · Course · 1 - 4 Weeks

1234…9

In summary, here are 10 of our most popular probabilistic+logic courses

  • An Intuitive Introduction to Probability: University of Zurich
  • Probabilistic Deep Learning with TensorFlow 2: Imperial College London
  • Building Reliable LLM Systems: Coursera
  • Probability & Statistics for Machine Learning & Data Science: DeepLearning.AI
  • Logic for Computer Science: Birla Institute of Technology & Science, Pilani
  • Probabilistic Graphical Models 2: Inference: Stanford University
  • Aléatoire : une introduction aux probabilités - Partie 1: École Polytechnique
  • Probabilistic Graphical Models 1: Representation: Stanford University
  • Introduction to Logic: Stanford University
  • Foundations of Probability and Random Variables: Johns Hopkins University

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