This course provides an overview of LinkedIn Learning's Data Science courses. The courses focus on topics such as: the basics of data ethics and privacy, 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, how to solve problems by working with tools like R, Python, and SQL, and business intelligence and Power BI.
Data & Data Software
Data & Data Software
Certificates for courses on data management.
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This course described the process of turning facts and figures into stories to engage stakeholders as a data scientists share their findings. |
This course presented six data science professionals explaining how they got started, the different roles they have had, and how they continue to advance their skills. |
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This course discussed the top 15 data science mistakes: misunderstanding business problems, using the wrong tools, starting without a plan, etc. |
This course introduced the concept of data governance, why it is beneficial and how to implement it. |
Data scientists discussed how to manage time, work with data, create processes, use tools, structure a data science team, work with teams and with clients. |
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This course discussed PivotTable basics, adjusting, filtering and sorting data, conditional formatting, charts, slicers and addressing common errors. |
This course discussed why metrics are important, which metrics matter the most, how to interpret results, and examples of how successful organizations leverage metrics to improve decisions and performance. |
This course provided an overview of the data-driven learning design process and explained how to
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