Bachelor of Computer Science in Data Science - Principles of Data Science

蒙纳士大学马来西亚校区

AU

QS排名:

  • 学历文凭

    Bachelor Degree

  • 专业院系

    信息系统

  • 开学时间

  • 课程时长

  • 课程学费

    汇率提示

国际学生入学条件

International Baccalaureate Diploma Program (IB Diploma Program) - 28 IELTS (International English Language Testing System – academic test) - Overall score : 6.5 (Listening score: 6.0; Reading score: 6.0; Writing score: 6.0; Speaking score: 6.0) TOEFL- PBT- 550 or above with (Test of Written English Score: 4.5 or above) TOEFL IBT - 79 (Listening score: 12; Reading score: 13; Writing score: 21; Speaking score: 18)
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IDP—雅思考试联合主办方

雅思考试总分

6.5

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  • 雅思总分:6.5
  • 托福网考总分:79
  • 托福笔试总分:550
  • 其他语言考试:PTE Academic - Overall score: 58 (Listening score: 50; Reading score: 50; Writing score: 50; Speaking score: 50)
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课程简介

This is the era of big data and artificial intelligence. Data science, a distinct but related field to computer science, represents a cutting-edge discipline which applies scientific methods, mathematics, algorithms and artificial intelligence to extract and visualise intelligent insights from huge volumes of complex data.<br>In the fast-progressing world of the Information Age, these insights have the potential to fuel innovation and transform decision making. Data scientists deal with the challenges of big data – its interpretation, management and use – in fields as diverse as marketing, information systems, engineering, finance, arts, humanities, science and medicine.<br>Monash brings a breadth of expertise to bear on issues relating to big data. If you aspire to solve real-world problems based on the information challenges of big data, then specialising in data science will equip you with the practical skills to excel in your chosen career.<br>The world faces a substantial talent gap in the field of big data analytics and data engineering, so get your foot in the door now.<br>Principles of data science: Embark on an exciting journey of understanding the multifaceted world of data through real-life case studies. Gain practical knowledge on data handling, storage, preparation, and analysis, empowering you in the ever-evolving field of Data Science.
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