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Big data
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MOOC
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MOOC
Data science has critical applications across most industries, and is one of the most in-demand careers in computer science. Data scientists are the detectives of the big data era, responsible for unearthing valuable data insights through analysis of massive datasets. And just like a detective is responsible for finding clues, interpreting them, and ultimately arguing their case in court, the field of data science encompasses the entire data life cycle. That starts with capturing lots of raw data using data collection techniques, and then building and maintaining data pipelines and data warehouses that efficiently “clean” the data and make it accessible for analysis at scale. This data infrastructure allows data scientists to efficiently process datasets using data mining and data modeling skills, as well as analyze these outputs with sophisticated techniques like predictive analysis and qualitative analysis. Finally, these findings must be presented using data visualization and data reporting skills to help business decision makers. Depending on the size of the company, data scientists may be responsible for this entire data life cycle, or they might specialize in a particular portion of the life cycle as part of a larger data science team
- Subjects:
- Computing
- Keywords:
- Machine learning Data mining Big data
- Resource Type:
- MOOC
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MOOC
This course covers a wide variety of topics in machine learning and statistical modeling. While mathematical methods and theoretical aspects will be covered, the primary goal is to provide students with the tools and principles needed to solve the data science problems found in practice. This course also serves as a foundation on which more specialized courses and further independent study can build. This course was designed as part of the core curriculum for the Center for Data Science's Masters degree in Data Science. Other interested students who satisfy the prerequisites are welcome to take the class as well. Note that class is intended as a continuation of DS-GA-1001 Intro to Data Science, which covers some important, fundamental data science topics that may not be explicitly covered in this DS-GA class (e.g. data cleaning, cross-validation, and sampling bias).
- Course related:
- LGT6801 Guided Study in Logistics I
- Subjects:
- Computing and Mathematics and Statistics
- Keywords:
- Big data Data mining Machine learning Mathematical statistics -- Data processing
- Resource Type:
- MOOC
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MOOC
In the past few decades, China's cities have experienced a period of rapid development. Great changes have taken place in both urban space and urban life. With the booming of information and communications technology (ICT), ‘Big data’ such as mobile phone signaling, public transportation smart card records and ‘open data’ from commercial websites and government websites jointly promote the formation of the ‘new data environment’, thus providing a novel perspective for a better understanding of what changes have happened or are happening in China’s cities. This course combines both the new data generated for urban analysis and its research applications. The content ranges from big data acquisition, analysis, visualization and applications in the context of China’s urbanization and its city planning, to urban modeling methods and typical models, as well as the emerging trend and potential revolution of big data in urban planning. We have categorized the overall content of this online course into five sections, namely, overview, data, data processing, application, and perspective. The section of overview introduces cities in transition and describe the changing of urban space and urban life in China. The second section lists some commonly used open data and big data in the ‘new data environment’. Then, methods for data acquisition, cleaning and analysis are illustrated in data processing section. To better explain the data analysis method, the fourth part introduces several Chinese research cases to illustrate the application of these methods in urban research. Last but not least, the last section is the most future-oriented one, which is composed of some methodologies and proposals such as Data Augmented Design (DAD) and Big Model. This course, which shares experiences on big data analysis and its research application, will suit those concerning contemporary urbanizing China and its urban planning in the context of information and communication technologies.
- Subjects:
- Building Services Engineering and Building and Real Estate
- Keywords:
- China Cities towns -- Data processing City planning Big data
- Resource Type:
- MOOC
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MOOC
Learn about the integrative power of knowledge management, Big Data and Cloud Computing, and how they impact the new business era.
- Subjects:
- Business Information Technology, Management, Computing, and Industrial and Systems Engineering
- Keywords:
- Big data Knowledge management
- Resource Type:
- MOOC