Big Data Technology MicroMasters

What you will learn:

  • Identify, explain, and use Big Data infrastructure.
  • Solve Big Data integration and storage problems.
  • Perform various data analytics tasks using Big Data management and computing techniques.
  • Investigate existing problems on Big Data and conduct original Big Data research.
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Foundations of Data Analytics (edX) EdX
The Hong Kong University of Science and Technology - HKUST,HKUSTx

Foundations of Data Analytics (edX)

Statistics & Data Analysis Computer Science

Embark on an educational journey with 'Foundations of Data Analytics' – your gateway to mastering the fundamental skills required in today's data-driven world. This course, offered by edX, will equip you with techniques such as data collection, extraction, integration, cleansing, and basic machine learning, setting a robust foundation for more advanced big data technologies.

Self Paced
Self-Paced
Machine Learning Big Data Data Privacy
Details
Big Data Technology Capstone Project (edX) EdX
The Hong Kong University of Science and Technology - HKUST,HKUSTx

Big Data Technology Capstone Project (edX)

Statistics & Data Analysis Computer Science

Embark on an advanced journey in big data with the Big Data Technology Capstone Project, offered by edX. Designed for those who have completed the four courses in the MicroMasters program, this capstone course provides a practical application of theoretical concepts and techniques to a real-world project scenario. Dive deep into applying your expertise and take your understanding of big data technology to the next level.

Self Paced
Self-Paced
Big Data Data Mining Data Analysis
Details
Mathematical Methods for Data Analysis (edX) EdX
The Hong Kong University of Science and Technology - HKUST,HKUSTx

Mathematical Methods for Data Analysis (edX)

Statistics & Data Analysis Computer Science

Dive into the world of data analysis with our 'Mathematical Methods for Data Analysis' course. Gain a deep understanding of mathematical formulations and computational methods essential for interpreting complex datasets. Explore machine learning algorithms through practical examples and learn how to apply these techniques to solve real-world problems effectively.

Self Paced
Self-Paced
Data Analysis Differentiation Linear Functions
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