Download Coursera – Google Advanced Data Analytics Professional Certificate 2023-6

Description

Google Advanced Data Analytics Professional Certificate, the Google Advanced Data Analytics Professional Certificate course is published by Coursera Academy. Learn professional training designed by Google and take the next step in your career with advanced data analysis skills. There are more than 144,000 open positions in advanced data analytics, and the average salary for entry-level jobs is $118,000. Advanced data professionals are responsible for collecting, analyzing and interpreting large amounts of data. These jobs require the manipulation of large data sets and the use of advanced analytics, including machine learning, predictive modeling, and experimental design. This certification builds on your data analysis skills and experience to reach the next level. This program is designed for graduates of the Google Data Analytics Certificate or those with equivalent data analytics experience. Expand your knowledge with hands-on projects in Jupyter Notebook, Python, and Tableau.

After completing seven courses, you will be prepared for jobs like Senior Data Analyst, Junior Data Scientist, Data Science Analyst, etc. In less than 10 hours of work per week, the certificate program can be completed in less than six months. Once you’re done, you can apply for jobs at Google and over 150 US employers, including Deloitte, Target, and Verizon. The program includes hours of training and hundreds of practice-based assessments that will help you simulate advanced real-world data analysis scenarios that are critical to success in the workplace. This highly interactive content is exclusively developed by Google employees with decades of experience in advanced data analytics and data science. Through a combination of videos, assessments, and hands-on labs, you’ll learn advanced data analytics tools and platforms and the key technical skills needed for an advanced career.

What you will learn

Examining the role of data professionals in an organization
Create data visualization and use statistical methods to examine data
Building regression and machine learning models for data analysis and interpretation
Communicate your insights from data analysis to stakeholders