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    • Scikit Learn

    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

    • I

      IBM

      Data Science Fundamentals with Python and SQL

      Skills you'll gain: Dashboard, SQL, Descriptive Statistics, Jupyter, Statistical Analysis, Data Analysis, Probability Distribution, Pandas (Python Package), Data Visualization Software, Statistics, Data Visualization, Web Scraping, Relational Databases, Stored Procedure, Databases, Computer Programming Tools, Automation, Data Analysis Software, Data Science, Python Programming

      Build toward a degree

      4.6
      Rating, 4.6 out of 5 stars
      ·
      71K reviews

      Beginner · Specialization · 3 - 6 Months

    • G

      Google

      Process Data from Dirty to Clean

      Skills you'll gain: Data Cleansing, Sampling (Statistics), Data Integrity, Data Quality, Data Validation, Sample Size Determination, Data Analysis, Data Manipulation, SQL, Data Transformation, Spreadsheet Software

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

      Beginner · Course · 1 - 3 Months

    • Status: Free
      Free
      U

      University of Alberta

      Indigenous Canada

      Skills you'll gain: Art History, Social Studies, Storytelling, Cultural Diversity, Culture, Social Justice, Intercultural Competence, Socioeconomics, World History, Political Sciences, Social Sciences, Community Development, Land Management, Governance

      4.8
      Rating, 4.8 out of 5 stars
      ·
      23K reviews

      Mixed · Course · 1 - 3 Months

    • G

      Google

      Project Planning: Putting It All Together

      Skills you'll gain: Project Management, Project Planning, Communication Planning, Project Documentation, Milestones (Project Management), Project Schedules, Risk Management, Cost Management, Budgeting, Estimation, Timelines, Procurement

      4.8
      Rating, 4.8 out of 5 stars
      ·
      14K reviews

      Beginner · Course · 1 - 3 Months

    • U

      University of Michigan

      Programming for Everybody (Getting Started with Python)

      Skills you'll gain: Programming Principles, Computer Programming, Python Programming, Software Installation, Development Environment

      4.8
      Rating, 4.8 out of 5 stars
      ·
      231K reviews

      Beginner · Course · 1 - 3 Months

    • Status: Free
      Free
      D

      Deep Teaching Solutions

      Aprendiendo a aprender: Poderosas herramientas mentales con las que podrás dominar temas difíciles (Learning How to Learn)

      Skills you'll gain: Learning Strategies, Critical Thinking and Problem Solving, Learning Theory, Time Management, Prioritization, Cognitive flexibility, Productivity, Growth Mindedness, Stress Management, Planning, Self-Awareness, Persistence

      4.9
      Rating, 4.9 out of 5 stars
      ·
      11K reviews

      Beginner · Course · 1 - 3 Months

    • Status: New
      New
      I

      IBM

      IBM Relational Database Administrator

      Skills you'll gain: Data Warehousing, Extract, Transform, Load, Apache Airflow, Web Scraping, Linux Commands, Database Design, SQL, Database Administration, MySQL, Data Pipelines, Apache Kafka, Database Management, Bash (Scripting Language), Shell Script, Database Architecture and Administration, Data Transformation, Data Store, IBM DB2, Jupyter, Generative AI

      4.6
      Rating, 4.6 out of 5 stars
      ·
      57K reviews

      Intermediate · Professional Certificate · 3 - 6 Months

    • I

      IBM

      BI Foundations with SQL, ETL and Data Warehousing

      Skills you'll gain: Data Warehousing, Extract, Transform, Load, Apache Airflow, Linux Commands, SQL, IBM Cognos Analytics, Data Pipelines, Apache Kafka, Bash (Scripting Language), Shell Script, Dashboard, File Management, Star Schema, Unix Shell, IBM DB2, Business Intelligence, Interactive Data Visualization, Relational Databases, Stored Procedure, Databases

      4.6
      Rating, 4.6 out of 5 stars
      ·
      24K reviews

      Beginner · Specialization · 3 - 6 Months

    • T

      Tsinghua University

      Learn English

      Skills you'll gain: Intercultural Competence, Cultural Diversity, Mental Health, Learning Strategies, Culture, Stress Management, Liberal Arts, English Language, Social Sciences, Literacy, Language Learning, Economics, Interpersonal Communications, Psychology, Writing, Research, Business Management, Grammar, Higher Education, Oral Comprehension

      4.3
      Rating, 4.3 out of 5 stars
      ·
      926 reviews

      Beginner · Specialization · 3 - 6 Months

    • U

      University of Michigan

      Introduction to Data Science in Python

      Skills you'll gain: Pandas (Python Package), Jupyter, NumPy, Data Manipulation, Data Science, Data Structures, Data Analysis, Statistical Analysis, Pivot Tables And Charts, Data Cleansing, Data Import/Export, Probability & Statistics, Python Programming, Programming Principles

      4.5
      Rating, 4.5 out of 5 stars
      ·
      27K reviews

      Intermediate · Course · 1 - 4 Weeks

    • I

      IBM

      AI Foundations for Everyone

      Skills you'll gain: Prompt Engineering, ChatGPT, Large Language Modeling, Generative AI, Artificial Intelligence, Data Ethics, Artificial Intelligence and Machine Learning (AI/ML), OpenAI, Workflow Management, Applied Machine Learning, Deep Learning, Artificial Neural Networks, Governance, Machine Learning, Automation, Application Deployment, Digital Transformation, Business Transformation, IBM Cloud, Business Technologies

      4.7
      Rating, 4.7 out of 5 stars
      ·
      26K reviews

      Beginner · Specialization · 3 - 6 Months

    • I

      IBM

      Data Analysis and Visualization Foundations

      Skills you'll gain: Data Storytelling, Big Data, Data Visualization Software, Data Analysis, Dashboard, IBM Cognos Analytics, Statistical Analysis, Data Mining, Apache Hadoop, Tree Maps, Excel Formulas, Data Wrangling, Apache Hive, Data Collection, Data Mart, Microsoft Excel, Data Warehousing, Data Quality, Data Cleansing, Data Import/Export

      Build toward a degree

      4.7
      Rating, 4.7 out of 5 stars
      ·
      27K reviews

      Beginner · Specialization · 3 - 6 Months

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    1…8910…834

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

    • Data Science Fundamentals with Python and SQL: IBM
    • Process Data from Dirty to Clean: Google
    • Indigenous Canada: University of Alberta
    • Project Planning: Putting It All Together: Google
    • Programming for Everybody (Getting Started with Python): University of Michigan
    • Aprendiendo a aprender: Poderosas herramientas mentales con las que podrás dominar temas difíciles (Learning How to Learn): Deep Teaching Solutions
    • IBM Relational Database Administrator: IBM
    • BI Foundations with SQL, ETL and Data Warehousing: IBM
    • Learn English: Tsinghua University
    • Introduction to Data Science in Python: University of Michigan

    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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