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    Scikit-learn Courses Online

    Study Scikit-learn for machine learning in Python. Learn to build and evaluate models using this popular library.

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    Explore the Scikit-learn Course Catalog

    • Status: Free Trial
      Free Trial
      D

      DeepLearning.AI

      Introduction to TensorFlow for Artificial Intelligence, Machine Learning, and Deep Learning

      Skills you'll gain: Tensorflow, Computer Vision, Image Analysis, Keras (Neural Network Library), Deep Learning, Artificial Neural Networks, Artificial Intelligence and Machine Learning (AI/ML)

      4.8
      Rating, 4.8 out of 5 stars
      ·
      20K reviews

      Intermediate · Course · 1 - 4 Weeks

    • 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

    • Status: Free Trial
      Free Trial
      G

      Google

      Build Wireframes and Low-Fidelity Prototypes

      Skills you'll gain: Storyboarding, Wireframing, Figma (Design Software), Information Architecture, User Story, User Experience Design, User Centered Design, Prototyping, Usability, User Interface and User Experience (UI/UX) Design, Mockups, User Flows

      4.9
      Rating, 4.9 out of 5 stars
      ·
      9.3K reviews

      Beginner · Course · 1 - 4 Weeks

    • Status: Free Trial
      Free Trial
      I

      IBM

      Excel Basics for Data Analysis

      Skills you'll gain: Excel Formulas, Microsoft Excel, Data Cleansing, Data Analysis, Data Import/Export, Spreadsheet Software, Data Wrangling, Data Quality, Pivot Tables And Charts, Google Sheets, Data Manipulation, Data Visualization Software, Information Privacy

      4.8
      Rating, 4.8 out of 5 stars
      ·
      9.7K reviews

      Beginner · Course · 1 - 3 Months

    • Status: Free Trial
      Free Trial
      J

      Johns Hopkins University

      The Data Scientist’s Toolbox

      Skills you'll gain: Rmarkdown, Version Control, Data Science, Big Data, Git (Version Control System), GitHub, Data Analysis, R Programming, Statistical Programming, Development Environment, Integrated Development Environments, Software Installation

      4.6
      Rating, 4.6 out of 5 stars
      ·
      34K reviews

      Mixed · Course · 1 - 4 Weeks

    • Status: Free Trial
      Free Trial
      U

      University of Colorado Boulder

      Effective Communication: Writing, Design, and Presentation

      Skills you'll gain: Business Writing, Presentations, Peer Review, Graphic Design, Graphic and Visual Design, Business Correspondence, Public Speaking, Business Communication, Graphic and Visual Design Software, Verbal Communication Skills, Design, Visual Design, Storytelling, Writing, Organizational Skills, Project Design, Concision, Writing and Editing, Proofreading, Drive Engagement

      4.8
      Rating, 4.8 out of 5 stars
      ·
      12K reviews

      Beginner · Specialization · 3 - 6 Months

    • S

      Stanford University

      Child Nutrition and Cooking

      Skills you'll gain: Nutrition Education, Cooking, Nutrition and Diet, Food and Beverage, Food Safety and Sanitation, Child Health, Working With Children, Community Health, Parent Communication

      4.8
      Rating, 4.8 out of 5 stars
      ·
      10K reviews

      Beginner · Course · 1 - 3 Months

    • U

      Universidad Nacional Autónoma de México

      Contabilidad para no contadores

      Skills you'll gain: Financial Statements, Financial Statement Analysis, Financial Reporting, Accounting Records, Accounting, Standard Accounting Practices, Income Statement, Balance Sheet, Generally Accepted Accounting Principles (GAAP), Cash Flows

      4.8
      Rating, 4.8 out of 5 stars
      ·
      9.5K reviews

      Beginner · Course · 1 - 3 Months

    • Status: Free Trial
      Free Trial
      M

      Macquarie University

      Excel Skills for Business: Intermediate I

      Skills you'll gain: Microsoft Excel, Dashboard, Spreadsheet Software, Excel Formulas, Data Analysis Expressions (DAX), Data Visualization, Consolidation, Business Reporting, Data Management, Data Cleansing, Automation

      4.9
      Rating, 4.9 out of 5 stars
      ·
      17K reviews

      Intermediate · Course · 1 - 3 Months

    • U

      University of California, Davis

      The Strategy of Content Marketing

      Skills you'll gain: Content Marketing, Content Performance Analysis, Content Strategy, Marketing Strategies, Content Creation, Strategic Marketing, Social Media Strategy, Marketing, Multimedia, Copywriting, Branding, Target Audience, Persona Development, Business Ethics

      4.5
      Rating, 4.5 out of 5 stars
      ·
      5.2K reviews

      Intermediate · Course · 1 - 3 Months

    • J

      Johns Hopkins University

      Business Analytics with Excel: Elementary to Advanced

      Skills you'll gain: Risk Modeling, Operations Research, Regression Analysis, Microsoft Excel, Business Analytics, Risk Analysis, Business Modeling, Resource Allocation, Statistical Analysis, Process Optimization, Financial Analysis, Predictive Analytics, Transportation Operations, Linear Algebra

      4.8
      Rating, 4.8 out of 5 stars
      ·
      3.8K reviews

      Intermediate · Course · 1 - 3 Months

    • W

      Wesleyan University

      Social Psychology

      Skills you'll gain: Social Sciences, Psychology, Persuasive Communication, Behavior Management, Conflict Management, Interpersonal Communications, Cultural Diversity, Research, Ethical Standards And Conduct, Experimentation

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

      Beginner · Course · 1 - 3 Months

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    1…192021…834

    In summary, here are 10 of our most popular scikit learn courses

    • Introduction to TensorFlow for Artificial Intelligence, Machine Learning, and Deep Learning: DeepLearning.AI
    • Game Theory: Stanford University
    • Build Wireframes and Low-Fidelity Prototypes: Google
    • Excel Basics for Data Analysis: IBM
    • The Data Scientist’s Toolbox: Johns Hopkins University
    • Effective Communication: Writing, Design, and Presentation: University of Colorado Boulder
    • Child Nutrition and Cooking: Stanford University
    • Contabilidad para no contadores : Universidad Nacional Autónoma de México
    • Excel Skills for Business: Intermediate I: Macquarie University
    • The Strategy of Content Marketing: University of California, Davis

    Frequently Asked Questions about Scikit Learn

    Scikit-learn—or skilearn—is a very useful library of algorithms in Python for machine learning. It started out as a Google summer of code project in 2007 then was further developed by a group of data scientists from the French Institute for Research in Computer Science and Automation (FIRCA) and released to the public in 2010. The scikit-learn library lives at a github.com URL and is now a community effort that anyone with qualified skills can contribute to. While the library is primarily written in Python, it's also built on Python-based libraries that include NumPy, Matplotlib, pandas, and SciPy. It gives users tools for statistical modeling and machine learning, such as classification, clustering, regression, model selection, preprocessing, and dimensionality reduction.‎

    When you learn scikit-learn, you put yourself in a position to be able to contribute to and help maintain the scikit-learn library. Top contributors include data scientists, software developers, machine learning researchers, research scientists, and open-source developers. Outside of contributing to the library, individuals in these career fields and others related to machine learning are better equipped to perform their job duties when they've learned how to utilize the algorithms in scikit-learn.‎

    Before starting to learn scikit-learn, you should have experience in and a sound understanding of Python. It is also often required to have experience in additional Python libraries, including NumPy, Scipy, Joblib, Matplotlib, and pandas.‎

    Taking online courses on Coursera can help you learn about Python and machine learning as well as the specifics of using and creating algorithms for scikit-learn. You might learn how to build univariate and multivariate linear regression models using scikit-learn, use pandas to manage data, and perform exploratory data analysis and data visualization with seaborn, a Python library based on Matplotlib. With Coursera's online courses, you may also have the opportunity to make predictions in specific topics like electricity consumption, sentiment analysis, and career longevity for NBA rookies, for example.‎

    Online Scikit Learn courses offer a convenient and flexible way to enhance your knowledge or learn new Scikit Learn skills. Choose from a wide range of Scikit Learn courses offered by top universities and industry leaders tailored to various skill levels.‎

    When looking to enhance your workforce's skills in Scikit Learn, it's crucial to select a course that aligns with their current abilities and learning objectives. Our Skills Dashboard is an invaluable tool for identifying skill gaps and choosing the most appropriate course for effective upskilling. For a comprehensive understanding of how our courses can benefit your employees, explore the enterprise solutions we offer. Discover more about our tailored programs at Coursera for Business here.‎

    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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