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This Excel Data Analytics Full Course video will help you understand the various crucial functions available in Excel, such as lookup, H lookup, sumif/s, counif/s, if error, and others. Finally, you will see how to use the Data study Toolpak to perform various data study operations. So, let’s begin.
00:00:00 Basic of excel data study
00:04:20 Lookup & functions in excel data study
01:37:58 Conditional formating in excel data study
01:54:30 Data validation in excel data study
02:36:30 Sorting and filtering in excel data study
03:23:55 Data study using toolpak in excel data study
Dataset Link: https://drive.google.com/drive/folders/1U8CF0Xx3NivXdfrQvXJ_462tEb26oPuX
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What is Microsoft Excel?
Excel is one of the best applications available for creating spreadsheets to crunch numbers and dashboard reports and storing and administering data. This software first appeared on the scene back in 1987, and since then it has grown to become one of the most popular pieces of software for home or company. Excel can be used for data entry to store data in the form of a table, such as recording your daily expenditures or company expenditure. It can also be used for inventory management.
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This Data Analytics Program is ideal for all working professionals and prior programming knowledge is not required. It covers topics like data study, data visualization, regression techniques, and supervised learning in-depth via our applied learning model with live sessions by leading practitioners and sector projects.
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– Professional Program certificate and Alumni Association membership
– Exclusive hackathons and Ask me Anything sessions by IBM
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– Capstone from 3 domains and 14+ Data Analytics Projects with sector datasets from Google PlayStore, Lyft, World money institution etc.
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– Resume preparation and LinkedIn profile building
– 1:1 mock interview
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âś… Skills Covered
– Data Analytics
– Statistical study using Excel
– Data study Python and R
– Data Visualization Tableau and Power BI
– Linear and logistic regression modules
– Clustering using kmeans
– Supervised Learning
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