Google Advanced Data Analytics
This Google Advanced Data Analytics course is designed to help you take the next step in your career. You'll gain the skills and knowledge needed to become an advanced data professional, including manipulating large data sets, using advanced analytics, and machine learning. Through over 200 hours of instruction, hands-on projects, and assessments, you'll learn Jupyter Notebook, Python, and Tableau. Upon completion, you can apply for jobs with Google and over 150 U.S. employers, including Deloitte, Target, and Verizon. 75% of certificate graduates report a positive career outcome within six months of completion. Take the next step in your career with this advanced data analytics course. ▼
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Course Feature
Cost:
Free
Provider:
Coursera
Certificate:
Paid Certification
Language:
English
Course Overview
❗The content presented here is sourced directly from Coursera platform. For comprehensive course details, including enrollment information, simply click on the 'Go to class' link on our website.
Updated in [May 30th, 2023]
Introducing Google Advanced Data Analytics, a professional training course designed by Google to help you take the next step in your career. With over 144,000 open jobs in advanced data analytics and a median salary of $118,000, this course is the perfect way to get ahead in the field. You'll learn how to manipulate large data sets, use advanced analytics such as machine learning, predictive modeling, and experimental design, and develop the skills necessary to become a senior data analyst, junior data scientist, data science analyst, and more. With over 200 hours of instruction and hundreds of practice-based assessments, you'll get the chance to simulate real-world advanced data analytics scenarios and gain the skills employers are looking for. You'll also complete a capstone project to showcase your new skill set. With this course, you'll be well on your way to a successful career in advanced data analytics.
Possible Development Paths in career or education include becoming a senior data analyst, junior data scientist, data science analyst, or any other related role. Related Learning Suggestions include taking courses in machine learning, predictive modeling, and experimental design, as well as gaining experience with Jupyter Notebook, Python, and Tableau. Additionally, it is important to stay up to date with the latest trends in the field and to network with other professionals in the industry.
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