Google Advanced Data Analytics Certificate

Advanced data analytics (also known as data science) uses math and statistics, programming, advanced analytics, artificial intelligence (AI), and machine learning to uncover key insights within an organization’s data. These insights can be used to guide the organization’s decision making and strategic planning.

Advanced data professionals (e.g. advanced data analysts and data scientists) are responsible for collecting, analyzing, and interpreting extremely large amounts of data within organizations. These roles require manipulation of large data sets and the use of advanced analytics including machine learning, predictive modeling, and experimental design.

The Google Advanced Data Analytics Certificate is for anyone seeking to improve their data analytics skills while learning how to use machine learning, predictive modeling, and experimental design to collect and analyze large amounts of data. This program follows the Data Analytics Certificate or equivalent experience.

Enrolling in the Google Advanced Data Analytics Certificate will teach you the skill set required to become a senior data analyst, junior data scientist, data science analyst. Advanced data analysts and data scientists are responsible for collecting, analyzing, and interpreting extremely large amounts of data.

You'll learn these job-ready skills in our certificate program through interactive content (discussion prompts, quizzes, and activities) in under six months, with under 10 hours of flexible study a week.* Along the way, you'll work through a curriculum designed with input from top employers and industry leaders, like Tableau, Accenture, and Deloitte. You'll even have the opportunity to complete a case study that you can share with potential employers to showcase your new skill set.

After you've graduated from the program, you'll have access to career resources and the opportunity to connect directly with over 150 employers who are hiring for open entry-level roles in data analytics.

Large volumes of data and the technology needed to manage and analyze it are becoming increasingly accessible. Because of this, there has been a surge in career opportunities for people who can tell stories using data, such as senior data analysts and data scientists. These professionals collect, analyze, and interpret large amounts of data within a variety of different organizations. Their responsibilities require advanced analytical skills such as data manipulation, experimental design, predictive modeling, and machine learning.

The courses offered in the Google Advanced Data Analytics Certificate are...

• Foundations of Data Science
• Get Started with Python
• Go Beyond the Numbers: Translate Data into Insights
• The Power of Statistics
• Regression Analysis: Simplify Complex Data Relationships
• The Nuts and Bolts of Machine Learning
• Google Advanced Data Analytics Capstone
• Data Analytics Capstone Project: Complete a Case Study

The data analysis tools and platforms included in the certificate curriculum are Jupyter Notebook, Python and Tableau

This advanced data analytics program teaches the open-source programming language Python. The Python programming language is a powerful tool for data analysis due to its simplicity, readability, and its rich ecosystem of libraries and tools. You'll learn to manipulate various data structures like lists, tuples, dictionaries, and sets. Import and utilize Python libraries such as NumPy and pandas.

A data analyst works with data to solve business problems using tools like SQL, R or other programming languages, data visualization software, and statistical analysis. A data scientist uses more advanced data techniques to make predictions about the future. They may come up with the questions their team should be asking and determine how to use data to answer them.

Data analytics and BI share a lot of common ground: They are both fields in which professionals use data to create insights that inform decision-making. Data analysts share insights via a report while BI professionals build a dashboard for stakeholders to monitor themselves. BI is more focused on making data readily available and easily understandable by organizational leaders. BI professionals retrieve and prepare data from multiple sources to then create reports and dashboards that make the data - and insights from the data - easily accessible.