Introduction to Big Data
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Course Feature
Cost:
Free
Provider:
Edx
Certificate:
No Information
Language:
English
Start Date:
1st Apr, 2020
Course Overview
❗The content presented here is sourced directly from Edx platform. For comprehensive course details, including enrollment information, simply click on the 'Go to class' link on our website.
Updated in [May 19th, 2023]
This course provides an introduction to Big Data analytics solutions. It covers the fundamentals of working with data, as well as some of the core concepts and technologies for Big Data scenarios. Students will gain an understanding of the tools and techniques used to build Big Data analytics solutions. The course will also provide an opportunity to connect with fellow students and teaching assistants, and plan their learning schedule. Note that this course will retire in June, so students should only enroll if they are able to finish their coursework in time.
[Applications]
After completing this course, students can apply their knowledge to build Big Data analytics solutions. They can use the fundamental concepts and technologies they have learned to create data-driven solutions that can help them make better decisions. Additionally, they can use the skills they have acquired to develop and deploy Big Data applications.
[Career Paths]
1. Data Scientist: Data Scientists are responsible for analyzing large datasets to uncover trends and insights. They use a variety of tools and techniques to extract, clean, and process data, and then use statistical methods to interpret the data and develop predictive models. As Big Data continues to grow, the demand for Data Scientists is expected to increase.
2. Data Engineer: Data Engineers are responsible for designing, building, and maintaining data pipelines and data warehouses. They use a variety of technologies to extract, transform, and load data into data warehouses, and then use SQL and other query languages to query and analyze the data. As Big Data continues to grow, the demand for Data Engineers is expected to increase.
3. Business Intelligence Analyst: Business Intelligence Analysts are responsible for analyzing data to identify trends and insights that can be used to inform business decisions. They use a variety of tools and techniques to extract, clean, and process data, and then use statistical methods to interpret the data and develop predictive models. As Big Data continues to grow, the demand for Business Intelligence Analysts is expected to increase.
4. Machine Learning Engineer: Machine Learning Engineers are responsible for developing and deploying machine learning models. They use a variety of tools and techniques to extract, clean, and process data, and then use machine learning algorithms to develop predictive models. As Big Data continues to grow, the demand for Machine Learning Engineers is expected to increase.
[Education Paths]
1. Bachelor of Science in Data Science: This degree path focuses on the fundamentals of data science, including data analysis, machine learning, and data visualization. It also covers topics such as data engineering, data mining, and data warehousing. This degree path is ideal for those looking to develop a strong foundation in data science and its related technologies.
2. Master of Science in Artificial Intelligence: This degree path focuses on the development of artificial intelligence (AI) systems and their applications. It covers topics such as natural language processing, computer vision, robotics, and machine learning. This degree path is ideal for those looking to develop advanced skills in AI and its related technologies.
3. Doctor of Philosophy in Data Science: This degree path focuses on the research and development of data science and its related technologies. It covers topics such as data mining, machine learning, and data visualization. This degree path is ideal for those looking to pursue a career in data science research.
4. Master of Business Administration in Data Science: This degree path focuses on the business applications of data science. It covers topics such as data analytics, data management, and data governance. This degree path is ideal for those looking to develop a strong understanding of the business implications of data science.
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