What you would learn in Visualization in Data Science & AI course?
Visualization of data is an integral element of the life cycle of a data science project. It's the process of putting data in an image-based context, such as a graph or map, to assist humans in processing the data and making conclusions. Data visualization's primary goal is to make recognizing patterns in trends, outliers, and trends in large data sets easier.
When they finish this course, participants receive a broad overview of the tools used to analyze and visualize data, can best practices, and create an action plan for the most important findings. It begins with common barriers that hinder the development of a culture based on data before introducing tools for data analysis (R software Minitab, MATLAB, and Python). An in-depth look is focused on statistical processing control (SPC), which is a method of looking at how variation changes over time. The course also covers rules and guidelines for visualizing data, using visualization software (Tableau, Excel, Power BI), and making a data-driven story.
The course includes online tutorials, videos, demo projects, readings, and discussions. This course is perfect for those who want to develop an analytical mindset that can yield important insights for improving a business's bottom line. It's beneficial if participants are familiar with understanding reports, collecting and analyzing data, and visuals. This is the second class within the Data-Driven Decision Making (DDDM) specialization.
Multi Business Intelligence Tools (BI) dominate the market, each with its advantages and disadvantages. Self-service dashboards were designed to enable users with no experience in data science to independently analyze the data and come up with results that can help them make daily business decisions. Here we will explore some of the uses of data visualization by using Tableau and Python in the following examples.
Do you want to look at massive data tables and understand the data or see an image of data that displays the data in a simple-to-understand visual format? The majority of you would use data visualization instead! It can be because it can be very beneficial in understanding data and providing valuable insight. It is a way to clearly comprehend the data that is impossible just by observing rows of data within tables. This is why it's crucial for Data Science!
Data visualization is the foundation of any analytical project. It's not just for understanding the data but also serves to aid in data preparation. Finding the best set of visualizations for various scenarios and data types is essential to successfully communicating the results.
Course Content:
- Visualization For Data Science
- Visualization from Basic To Advanced
- Not just Theory, However, Practical Hands-On Tutorial
- Learn How to Select and Design the most appropriate plot for your needs.
- Power BI: From Basic To Advance
- Competencies that are relevant to the industry
- Visualization in Python From Basic To Advanced
- Learn How To Make Compelling Graphics That Don't Refuse to
Download Visualization in Data Science & AI from below links NOW!
