Statistical Thinking for Data Science and Analytics
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Course Feature
Cost:
Free
Provider:
Edx
Certificate:
Paid Certification
Language:
English
Start Date:
16th May, 2022
Course Overview
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Updated in [June 30th, 2023]
This course, Statistical Thinking for Data Science and Analytics, provides an introduction to the fundamentals of statistics and data analysis. Students will learn how to exercise statistical thinking in designing data collection, deriving insights from visualizing data, obtaining supporting evidence for data-based decisions, and constructing models for predicting future trends from data. Through a combination of lectures, discussions, and hands-on activities, students will gain an understanding of the principles of statistical thinking and how to apply them to data science and analytics.
[Applications]
Upon completion of this course, participants are encouraged to apply the statistical thinking and data analysis skills they have acquired to their own data science projects. They should be able to use the techniques they have learned to design data collection, visualize data, obtain evidence for data-based decisions, and construct models for predicting future trends. Additionally, they should be able to use the knowledge they have gained to interpret the results of their data analysis and communicate their findings to stakeholders.
[Career Path]
One job position path that is recommended for learners of this course is a Data Scientist. Data Scientists are responsible for collecting, analyzing, and interpreting large amounts of data to identify trends and patterns. They use their findings to develop strategies and solutions to improve business operations. Data Scientists must have strong analytical and problem-solving skills, as well as a deep understanding of data analysis techniques and tools. They must also be able to communicate their findings to stakeholders in a clear and concise manner.
The development trend for Data Scientists is very positive. As businesses become increasingly reliant on data-driven decision making, the demand for Data Scientists is expected to grow significantly. Companies are also investing more in data-driven technologies, such as artificial intelligence and machine learning, which will create even more opportunities for Data Scientists. Additionally, the emergence of new data sources, such as the Internet of Things, will create even more opportunities for Data Scientists to explore and analyze.
[Education Path]
The recommended educational path for learners is a Bachelor's degree in Data Science and Analytics. This degree program will provide students with a comprehensive understanding of the principles and techniques of data science and analytics. Students will learn how to use data to solve real-world problems, develop data-driven strategies, and create data-driven products. They will also gain an understanding of the ethical implications of data science and analytics.
The development trend of this degree program is to focus on the application of data science and analytics in various industries. Students will learn how to use data to make decisions in areas such as healthcare, finance, marketing, and more. They will also learn how to use data to create predictive models and develop data-driven products. Additionally, the degree program will focus on the ethical implications of data science and analytics, teaching students how to use data responsibly and ethically.
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