LinkedIn Learning Highlights: Data Science and Analytics

  • Course details

    In the growing field of data science, there's always something new to learn. And whether you're looking to break into this exciting field—or just keep your data science and analytics skills sharp—LinkedIn Learning has courses that can help. Enjoy this selection of curated highlights from our very best data science courses. Dive into the basics of data ethics and privacy. Learn how to work with data analytics platforms and tools, help others visualize data, and apply advanced knowledge of machine learning, deep learning, and neural networks. Plus, discover how to solve problems by working with tools like R, Python, and SQL, explore business intelligence and Power BI, and more.


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      LinkedIn Learning Staff Instructor

      LinkedIn Learning connects learners with quality content to develop their skills and achieve their goals.

      Our staff instructors are industry experts who develop engaging, top-quality courses on a wide range of topics, including creative, business, and technology skills.

    Skills covered in this course

    For each course you will get

    • Exercise files and quizzes
    • Certificate of completion from LinkedIn
    • Offline and audio-only options
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  • Teaming up for data science

    (upbeat music) - Try not to think of data-driven decision making as a drop-in replacement for your own intuition. A data-driven culture uses data to enhance their teams' instinct. Your data science team will be the starting point in creating a larger data-driven organization. It's within this team that you'll start to develop a deeper relationship with your data. Try to think of data-driven organizations as companies with many data science teams. These teams create a mindset of questions and insight. They should help the organization not just collect data, but think about the data in new ways. - [Interviewer] What are you looking for in your team members? - So first off is that they want to be part of a team and you know, many times, especially some of the training we receive in academia, for those that come out of that realm, is that we're used to locking ourselves behind a door and working on the problem in a deep way…

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