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所在平台: Udemy |
课程主页: https://www.udemy.com/course/data-science-bootcamp-with-power-bi-and-python/
课程评论：没有评论
Coursera《使用 Power BI 和 Python 的数据科学训练营》课程总结： 本课程旨在教授学员数据科学的核心概念，重点在于使用 Microsoft Power BI 和 Python 进行强大的商业智能报告和分析仪表板的创建。 **核心内容包括：** * **数据可视化 (Data Visualization)：** * **Power BI 内置图表：** 学习创建各种基础图表，如条形图 (Bar chart)、饼图 (Pie chart)、圆环图 (Ring chart)、树状图 (Treemap) 等。 * **Python 结合 Power BI 的高级图表：** 利用 Python 编程创建更复杂的自定义图表，例如折线图 (Line chart)、散点图 (Scatterplot) 和小提琴图 (Violin chart)。 * **交互式筛选器：** 学习创建切片器 (Slicer) 和日期切片器 (Date Slicer)，以根据特定参数（如地区、类别或日期）对可视化数据进行筛选，从而支持专注的决策制定。 * **其他可视化技巧：** 包含表格 (Table)、矩阵 (Matrix) 以及钻取 (Drill down) 功能。 * **数据准备 (Data Preparation) - 使用 Power Query Editor：** * **数据清洗与转换：** 学习如何有效地对数据集的行、列和单个单元格执行各种操作。 * **行操作：** 包括行删除 (Row deletion)。 * **列操作：** 涉及拆分列 (Split column)、合并列 (Merge column)、提取列 (Extract) 等。 * **自定义列创建：** 学习基于特定条件创建新的自定义列 (Custom column)，例如条件列 (Conditional column)，以及创建索引列 (Index column)。 * **日期函数：** 掌握在 Power Query 中使用日期函数。 * **其他数据转换：** 包括替换列值 (Replace column values)、添加后缀和前缀 (Adding Suffix and Prefix)，以及添加和转换列 (Add and transform column)。 **Python 库的使用：** 课程还将涉及安装必要的 Python 库，并展示如何使用 Matplotlib 创建折线图、添加标签以及创建虚线图表，以及使用 Seaborn 创建小提琴图。 **应用领域：** 本课程的技能可广泛应用于数据科学 (Data Science)、商业智能 (Business Intelligence)、数据分析 (Data Analysis)、数据准备 (Data Preparation) 和数据可视化 (Data Visualization) 等多个领域。 **数据源：** 课程还将教授如何使用实时网络数据 (live web data)。 总而言之，本课程提供了一个全面的数据科学入门体验，让学员能够熟练运用 Power BI 和 Python 来处理、分析和可视化数据，并从中提取有价值的洞察。
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 dashboard. 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 date 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 parameter 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 new custom column or field in a table based on a certain condition such as conditional column, and you will also learn to create 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 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 chartLine chartPie chartRing chartTreemap chartTable and MatrixDrill downInstall python librariesCreate line chart with matplotlibPutting labels and creating a dashed line chartViolin chart with seabornSlicer FilterDate SlicerCreating a calculated measureUsing live web dataTopics covered under Data preparation with Power Query-Row deletion and column SplitReplace column valuesColumn MergeAdding Suffix and PrefixAdd and transform columnExtract functionAdding conditional and Index columnDate function in power query
