Data Analytics using Python

Are you aspiring to learn Data Analysis using Python? if yes, then this course on Python will give you the right base, and that too in less than 10 hours.

In this course, you will learn about the basics of the Python Language, Language Elements, Multidimensional Array Handling using the Numpy Library, handling business data using Pandas Library, etc.

You will also learn the tools and techniques of Data Analysis followed by a Data Analysis Project.

Course Sections:

• Python Language in Detail

• Python internal Data Structures

• Python Language Elements

• Pandas Data Structure – Series and DataFrames

• Python Visualizations

• Data Analysis (EDA) Techniques covered exhaustively through Project work

Some of the areas you will master using the powerful Numpy and Pandas Libraries in this course:

• Data Structures: Numpy provides arrays that are optimized for numerical operations, while Pandas provides two main data structures - Series and DataFrame. You will learn how to create, manipulate, and use these structures for data analysis.

• Data Cleaning: Pandas provides a range of functions to clean and preprocess data. You can learn how to handle missing data, remove duplicates, and deal with data outliers.

• Data Aggregation: Pandas provides functions to group data by one or more variables and perform various aggregation operations on the data such as sum, count, mean, and standard deviation. Numpy provides functions to perform mathematical operations on arrays such as sum, mean, max, min, etc.

• Data Transformation: Pandas provides functions for transforming data, including reshaping, merging, and pivoting data. Numpy provides functions for slicing and indexing arrays, and for reshaping and manipulating arrays.

Happy Learning!