Data Science Bootcamp with Power BI and Python

Welcome to this course on Data Science Bootcamp with Microsoft Power BI and Python. In this course, you will learn various concepts with hands-on examples where you will learn to create powerful BI reports and analytics dashboards. You will learn right from creating data visualization charts in Power BI with and without using Python programs. You will learn to create various kinds of charts such as Bar, Pie, Ring, Treemap and more that are available as default charts in Power BI. Moreover you will also learn to create advanced custom charts by writing Python programs such as line, scatterplot and violin chart. After that, you will also learn to create slicer filters for categories and dates based on which you can filter the data that is visually displayed on the chart. This feature helps in focused decision-making based on decided parameters such as region, category or date.

After learning lessons on Data Visualization, you will learn Data Cleaning and Data Preparation by using Power Query Editor. Here, you will learn to perform various kinds of operations on rows, columns or individual cells of the dataset. You will learn to create a new custom column or field in a table based on a certain condition such as a conditional column, and you will also learn to create an index column. You will learn to perform row operations such as row deletion. For columns, you would learn to perform Split, Merge, Extract and other operations in the Power Query editor.

You could use the skills learned in this course for various domains such as Data Science, Business Intelligence, Data Analysis, Data Preparation and Data Visualization.

Topics discussed under Data Visualization and Analytics with Python and Power BI:

• Bar chart.

• Line chart.

• Pie chart.

• Ring chart.

• Treemap chart.

• Table and Matrix.

• Drill down.

• Install python libraries.

• Create a line chart with matplotlib.

• Putting labels and creating a dashed line chart.

• Violin chart with seaborn.

• Slicer Filter.

• Date Slicer.

• Creating a calculated measure.

• Using live web data.

Topics covered under Data Preparation with Power Query:

• Row deletion and column Split.

• Replace column values.

• Column Merge.

• Adding Suffixes and Prefixes.

• Add and transform the column.

• Extract function.

• Adding conditional and Index columns.

• Date function in power query.