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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

    • I

      IBM

      IBM AI Engineering

      Skills you'll gain: PyTorch (Machine Learning Library), Supervised Learning, Feature Engineering, Generative AI, Keras (Neural Network Library), Deep Learning, Jupyter, Natural Language Processing, Reinforcement Learning, Unsupervised Learning, Scikit Learn (Machine Learning Library), Machine Learning Algorithms, Data Manipulation, Tensorflow, Python Programming, Verification And Validation, Applied Machine Learning, ChatGPT, Artificial Neural Networks, Statistical Machine Learning

      Build toward a degree

      4.6
      Rating, 4.6 out of 5 stars
      ·
      20K reviews

      Intermediate · Professional Certificate · 3 - 6 Months

    • D

      DeepLearning.AI

      Improving Deep Neural Networks: Hyperparameter Tuning, Regularization and Optimization

      Skills you'll gain: Tensorflow, Deep Learning, Artificial Intelligence and Machine Learning (AI/ML), Performance Tuning, Machine Learning Methods, Artificial Neural Networks, Applied Machine Learning, Machine Learning, Supervised Learning, Machine Learning Algorithms, Network Architecture, Algorithms, Analysis, Debugging

      4.9
      Rating, 4.9 out of 5 stars
      ·
      63K reviews

      Intermediate · Course · 1 - 4 Weeks

    • G

      Google

      Technical Support Fundamentals

      Skills you'll gain: Computer Hardware, Technical Support, Software Installation, Operating Systems, Technical Documentation, Hardware Troubleshooting, Computer Networking, Information Technology, Technical Communication, TCP/IP, Software Systems, Linux, Microsoft Windows

      4.8
      Rating, 4.8 out of 5 stars
      ·
      159K reviews

      Beginner · Course · 1 - 3 Months

    • U

      University of Illinois Urbana-Champaign

      Digital Marketing

      Skills you'll gain: Data Storytelling, Data Visualization, Email Marketing, Data Presentation, Google Analytics, Digital Marketing, Analytics, Marketing Communications, Business Analytics, Content Marketing, Marketing Strategies, Marketing Analytics, Social Media Marketing, Marketing Management, Marketing, Web Analytics, Strategic Marketing, Digital Communications, Integrated Marketing Communications, Media Strategy

      4.7
      Rating, 4.7 out of 5 stars
      ·
      23K reviews

      Beginner · Specialization · 3 - 6 Months

    • U

      University of Pennsylvania

      Business Analytics

      Skills you'll gain: People Analytics, Data-Driven Decision-Making, Business Analytics, Descriptive Analytics, Business Intelligence, Human Resource Strategy, Financial Data, Marketing Analytics, Analytics, Talent Management, Financial Analysis, Predictive Analytics, Human Resources Management and Planning, Peer Review, Business Analysis, Financial Statement Analysis, Financial Forecasting, Customer Insights, Workforce Planning, Demand Planning

      4.6
      Rating, 4.6 out of 5 stars
      ·
      18K reviews

      Beginner · Specialization · 3 - 6 Months

    • G

      Google

      The Bits and Bytes of Computer Networking

      Skills you'll gain: Computer Networking, Network Troubleshooting, TCP/IP, Network Architecture, Routing Protocols, Network Protocols, OSI Models, Network Infrastructure, Dynamic Host Configuration Protocol (DHCP), Virtual Private Networks (VPN), Network Security, Wireless Networks, Network Model

      4.7
      Rating, 4.7 out of 5 stars
      ·
      51K reviews

      Beginner · Course · 1 - 3 Months

    • M

      Macquarie University

      Excel Skills for Business: Essentials

      Skills you'll gain: Microsoft Excel, Data Visualization, Spreadsheet Software, Excel Formulas, Data Management, Microsoft 365, Data Entry, Productivity Software

      4.9
      Rating, 4.9 out of 5 stars
      ·
      50K reviews

      Beginner · Course · 1 - 3 Months

    • I

      IBM

      IBM DevOps and Software Engineering

      Skills you'll gain: CI/CD, Istio, Open Web Application Security Project (OWASP), Continuous Integration, Software Development Life Cycle, Linux Commands, Agile Software Development, Unit Testing, Cloud Computing Architecture, Application Deployment, Test Driven Development (TDD), Gherkin (Scripting Language), Jenkins, Kubernetes, Bash (Scripting Language), Cloud Services, Git (Version Control System), DevOps, Jupyter, Grafana

      Build toward a degree

      4.6
      Rating, 4.6 out of 5 stars
      ·
      59K reviews

      Beginner · Professional Certificate · 3 - 6 Months

    • Status: AI skills
      AI skills
      I

      IBM

      IBM Data Analyst

      Skills you'll gain: Data Storytelling, Dashboard, Data Visualization Software, Plotly, Data Presentation, Data Wrangling, Data Visualization, SQL, Generative AI, Interactive Data Visualization, Exploratory Data Analysis, Data Cleansing, Big Data, Jupyter, Matplotlib, Data Analysis, Statistical Analysis, Pandas (Python Package), Excel Formulas, Professional Networking

      Build toward a degree

      4.6
      Rating, 4.6 out of 5 stars
      ·
      91K reviews

      Beginner · Professional Certificate · 3 - 6 Months

    • G

      Google Cloud

      Architecting with Google Compute Engine

      Skills you'll gain: Cloud Infrastructure, Google Cloud Platform, Identity and Access Management, Kubernetes, Application Deployment, Cloud Storage, Infrastructure As A Service (IaaS), Containerization, Cloud Computing, CI/CD, Cloud Computing Architecture, Cloud Security, Cloud Applications, Cloud Services, Load Balancing, Service Level Agreement, Infrastructure as Code (IaC), Virtual Machines, Microservices, Service Level

      4.7
      Rating, 4.7 out of 5 stars
      ·
      58K reviews

      Intermediate · Specialization · 3 - 6 Months

    • D

      Duke University

      Introduction to Machine Learning

      Skills you'll gain: PyTorch (Machine Learning Library), Reinforcement Learning, Image Analysis, Applied Machine Learning, Deep Learning, Machine Learning, Natural Language Processing, Supervised Learning, Artificial Neural Networks, Computer Vision, Regression Analysis

      4.7
      Rating, 4.7 out of 5 stars
      ·
      3.7K reviews

      Intermediate · Course · 1 - 3 Months

    • I

      IBM

      IBM Full-Stack JavaScript Developer

      Skills you'll gain: Istio, Node.JS, Software Development Life Cycle, Server Side, MongoDB, Application Deployment, CI/CD, Cloud-Native Computing, React Redux, NoSQL, Kubernetes, Restful API, OpenShift, Git (Version Control System), Cloud Applications, Containerization, GitHub, HTML and CSS, Ajax, Interviewing Skills

      4.6
      Rating, 4.6 out of 5 stars
      ·
      7.1K reviews

      Beginner · Professional Certificate · 3 - 6 Months

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    1…678…834

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

    • IBM AI Engineering: IBM
    • Improving Deep Neural Networks: Hyperparameter Tuning, Regularization and Optimization: DeepLearning.AI
    • Technical Support Fundamentals: Google
    • Digital Marketing: University of Illinois Urbana-Champaign
    • Business Analytics: University of Pennsylvania
    • The Bits and Bytes of Computer Networking: Google
    • Excel Skills for Business: Essentials: Macquarie University
    • IBM DevOps and Software Engineering: IBM
    • IBM Data Analyst: IBM
    • Architecting with Google Compute Engine: Google Cloud

    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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