What Will Participants Learn? (Course Objectives)

Data Extraction, Wrangling and Exploration

Learning Objectives - Discuss the different sources available to extract data, arrange the data in

structured form, analyze the data, and represent the data in a graphical format.

Topics:

Data Analysis Pipeline What is Data Extraction

Types of Data Raw and Processed Data

Data Wrangling Exploratory Data Analysis

Visualization of Data

This course is designed to build the foundation of Programming with the help of Python as a programming language.

During this course, our expert instructors will train you to-

• Define Data Science and its various stages

• Implement Data Science development methodology in business scenarios

• Identify areas of applications of Data Science.

• Understand the fundamental concepts of Python

• Use various Data Structures of Python.

• Perform operations on arrays using NumPy library

• Perform data manipulation using the Pandas library

• Visualize data and obtain insights from data using the Matplotlib and Seaborn library

• Apply Scrapy and Beautiful Soup to scrap data from websites

• Perform end to end Case study on data extraction, manipulation, visualization and analysis using Python

Today, the popularity of Python for Data Science is at its peak. Researchers and developers are using it for all sorts of functionality, from cleaning data and Training models to developing advanced AI and Machine Learning software. As per Statista, Python is LinkedIn's most wanted Data Science skill in the United States.