Deloitte
6 位校友岗位:Graduate Program · Graduate Consulting · Platform Engineer · Web developer · Platform engineer
DATA7201
数据科学
2 学分难度 超难👥 23 人学过
Data Science techniques often need to be applied to large amounts of data to generate insights. To deal with volume, velocity, and variety of data we need to rely on novel computational architectures that focus on scaling-out data processing as compared to the classic scale-up approach. Such systems allow to add computational resources to a distributed system depending on requirements and load which changes over time. In this course we will give students knowledge about modern scale-out system architectures to perform data analytics queries over very large structured/unstructured datasets as well as to run data mining algorithms at scale.
Syllabus
每周大纲
- 1
Lectures / Practicals
No separate week-by-week topic is publicly listed for Week 1; official repeated teaching activities are shown below: - Lecture: Lectures - Lectures will cover 1) use cases for data analytics at scale, 2) fundamental data infrastructure architectures, and 3) applications of data analytics at scale to problems like, e.g., recommender systems, log mining, and opinion mining. These sessions will also be used for exam preparation and student discussions. Learning outcomes: L01, L02, L03, L04, L05, L06 - Practical: Practicals - During this sessions, students will be exposed to the systems discussed during the lectures and they will be able to develop their own data analytics solutions over these scalable systems. Learning outcomes: L01, L02, L03, L06 Official timetable activities: - Lecture | Wed 12:00 | 120 mins | 07-234 Parnell Building, Learning Theatre - Practical | Wed 14:00 | 120 mins | 47A-351 Sir James Foots Building, Collaborative Room Source: 2026 S1 UQ Course Profile - https://course-profiles.uq.edu.au/course-profiles/DATA7201-22188-7620
- 2
Lectures / Practicals
No separate week-by-week topic is publicly listed for Week 2; official repeated teaching activities are shown below: - Lecture: Lectures - Lectures will cover 1) use cases for data analytics at scale, 2) fundamental data infrastructure architectures, and 3) applications of data analytics at scale to problems like, e.g., recommender systems, log mining, and opinion mining. These sessions will also be used for exam preparation and student discussions. Learning outcomes: L01, L02, L03, L04, L05, L06 - Practical: Practicals - During this sessions, students will be exposed to the systems discussed during the lectures and they will be able to develop their own data analytics solutions over these scalable systems. Learning outcomes: L01, L02, L03, L06 Official timetable activities: - Lecture | Wed 12:00 | 120 mins | 07-234 Parnell Building, Learning Theatre - Practical | Wed 14:00 | 120 mins | 47A-351 Sir James Foots Building, Collaborative Room Source: 2026 S1 UQ Course Profile - https://course-profiles.uq.edu.au/course-profiles/DATA7201-22188-7620
- 3
Lectures / Practicals
No separate week-by-week topic is publicly listed for Week 3; official repeated teaching activities are shown below: - Lecture: Lectures - Lectures will cover 1) use cases for data analytics at scale, 2) fundamental data infrastructure architectures, and 3) applications of data analytics at scale to problems like, e.g., recommender systems, log mining, and opinion mining. These sessions will also be used for exam preparation and student discussions. Learning outcomes: L01, L02, L03, L04, L05, L06 - Practical: Practicals - During this sessions, students will be exposed to the systems discussed during the lectures and they will be able to develop their own data analytics solutions over these scalable systems. Learning outcomes: L01, L02, L03, L06 Official timetable activities: - Lecture | Wed 12:00 | 120 mins | 07-234 Parnell Building, Learning Theatre - Practical | Wed 14:00 | 120 mins | 47A-351 Sir James Foots Building, Collaborative Room Source: 2026 S1 UQ Course Profile - https://course-profiles.uq.edu.au/course-profiles/DATA7201-22188-7620
- 4
Lectures / Practicals
No separate week-by-week topic is publicly listed for Week 4; official repeated teaching activities are shown below: - Lecture: Lectures - Lectures will cover 1) use cases for data analytics at scale, 2) fundamental data infrastructure architectures, and 3) applications of data analytics at scale to problems like, e.g., recommender systems, log mining, and opinion mining. These sessions will also be used for exam preparation and student discussions. Learning outcomes: L01, L02, L03, L04, L05, L06 - Practical: Practicals - During this sessions, students will be exposed to the systems discussed during the lectures and they will be able to develop their own data analytics solutions over these scalable systems. Learning outcomes: L01, L02, L03, L06 Official timetable activities: - Lecture | Wed 12:00 | 120 mins | 07-234 Parnell Building, Learning Theatre - Practical | Wed 14:00 | 120 mins | 47A-351 Sir James Foots Building, Collaborative Room Source: 2026 S1 UQ Course Profile - https://course-profiles.uq.edu.au/course-profiles/DATA7201-22188-7620
- 5
Lectures / Practicals
No separate week-by-week topic is publicly listed for Week 5; official repeated teaching activities are shown below: - Lecture: Lectures - Lectures will cover 1) use cases for data analytics at scale, 2) fundamental data infrastructure architectures, and 3) applications of data analytics at scale to problems like, e.g., recommender systems, log mining, and opinion mining. These sessions will also be used for exam preparation and student discussions. Learning outcomes: L01, L02, L03, L04, L05, L06 - Practical: Practicals - During this sessions, students will be exposed to the systems discussed during the lectures and they will be able to develop their own data analytics solutions over these scalable systems. Learning outcomes: L01, L02, L03, L06 Official timetable activities: - Lecture | Wed 12:00 | 120 mins | 07-234 Parnell Building, Learning Theatre - Practical | Wed 14:00 | 120 mins | 47A-351 Sir James Foots Building, Collaborative Room Source: 2026 S1 UQ Course Profile - https://course-profiles.uq.edu.au/course-profiles/DATA7201-22188-7620
- 6
Lectures / Practicals
No separate week-by-week topic is publicly listed for Week 6; official repeated teaching activities are shown below: - Lecture: Lectures - Lectures will cover 1) use cases for data analytics at scale, 2) fundamental data infrastructure architectures, and 3) applications of data analytics at scale to problems like, e.g., recommender systems, log mining, and opinion mining. These sessions will also be used for exam preparation and student discussions. Learning outcomes: L01, L02, L03, L04, L05, L06 - Practical: Practicals - During this sessions, students will be exposed to the systems discussed during the lectures and they will be able to develop their own data analytics solutions over these scalable systems. Learning outcomes: L01, L02, L03, L06 Official timetable activities: - Lecture | Wed 12:00 | 120 mins | 07-234 Parnell Building, Learning Theatre - Practical | Wed 14:00 | 120 mins | 47A-351 Sir James Foots Building, Collaborative Room Source: 2026 S1 UQ Course Profile - https://course-profiles.uq.edu.au/course-profiles/DATA7201-22188-7620
- 7
Lectures / Practicals
No separate week-by-week topic is publicly listed for Week 7; official repeated teaching activities are shown below: - Lecture: Lectures - Lectures will cover 1) use cases for data analytics at scale, 2) fundamental data infrastructure architectures, and 3) applications of data analytics at scale to problems like, e.g., recommender systems, log mining, and opinion mining. These sessions will also be used for exam preparation and student discussions. Learning outcomes: L01, L02, L03, L04, L05, L06 - Practical: Practicals - During this sessions, students will be exposed to the systems discussed during the lectures and they will be able to develop their own data analytics solutions over these scalable systems. Learning outcomes: L01, L02, L03, L06 Official timetable activities: - Lecture | Wed 12:00 | 120 mins | 07-234 Parnell Building, Learning Theatre - Practical | Wed 14:00 | 120 mins | 47A-351 Sir James Foots Building, Collaborative Room Source: 2026 S1 UQ Course Profile - https://course-profiles.uq.edu.au/course-profiles/DATA7201-22188-7620
- 8
Lectures / Practicals
No separate week-by-week topic is publicly listed for Week 8; official repeated teaching activities are shown below: - Lecture: Lectures - Lectures will cover 1) use cases for data analytics at scale, 2) fundamental data infrastructure architectures, and 3) applications of data analytics at scale to problems like, e.g., recommender systems, log mining, and opinion mining. These sessions will also be used for exam preparation and student discussions. Learning outcomes: L01, L02, L03, L04, L05, L06 - Practical: Practicals - During this sessions, students will be exposed to the systems discussed during the lectures and they will be able to develop their own data analytics solutions over these scalable systems. Learning outcomes: L01, L02, L03, L06 Official timetable activities: - Lecture | Wed 12:00 | 120 mins | 07-234 Parnell Building, Learning Theatre - Practical | Wed 14:00 | 120 mins | 47A-351 Sir James Foots Building, Collaborative Room Source: 2026 S1 UQ Course Profile - https://course-profiles.uq.edu.au/course-profiles/DATA7201-22188-7620
- 9
Lectures / Practicals
No separate week-by-week topic is publicly listed for Week 9; official repeated teaching activities are shown below: - Lecture: Lectures - Lectures will cover 1) use cases for data analytics at scale, 2) fundamental data infrastructure architectures, and 3) applications of data analytics at scale to problems like, e.g., recommender systems, log mining, and opinion mining. These sessions will also be used for exam preparation and student discussions. Learning outcomes: L01, L02, L03, L04, L05, L06 - Practical: Practicals - During this sessions, students will be exposed to the systems discussed during the lectures and they will be able to develop their own data analytics solutions over these scalable systems. Learning outcomes: L01, L02, L03, L06 Official timetable activities: - Lecture | Wed 12:00 | 120 mins | 07-234 Parnell Building, Learning Theatre - Practical | Wed 14:00 | 120 mins | 47A-351 Sir James Foots Building, Collaborative Room Source: 2026 S1 UQ Course Profile - https://course-profiles.uq.edu.au/course-profiles/DATA7201-22188-7620
- 10
Lectures / Practicals
No separate week-by-week topic is publicly listed for Week 10; official repeated teaching activities are shown below: - Lecture: Lectures - Lectures will cover 1) use cases for data analytics at scale, 2) fundamental data infrastructure architectures, and 3) applications of data analytics at scale to problems like, e.g., recommender systems, log mining, and opinion mining. These sessions will also be used for exam preparation and student discussions. Learning outcomes: L01, L02, L03, L04, L05, L06 - Practical: Practicals - During this sessions, students will be exposed to the systems discussed during the lectures and they will be able to develop their own data analytics solutions over these scalable systems. Learning outcomes: L01, L02, L03, L06 Official timetable activities: - Lecture | Wed 12:00 | 120 mins | 07-234 Parnell Building, Learning Theatre - Practical | Wed 14:00 | 120 mins | 47A-351 Sir James Foots Building, Collaborative Room Source: 2026 S1 UQ Course Profile - https://course-profiles.uq.edu.au/course-profiles/DATA7201-22188-7620
- 11
Lectures / Practicals
No separate week-by-week topic is publicly listed for Week 11; official repeated teaching activities are shown below: - Lecture: Lectures - Lectures will cover 1) use cases for data analytics at scale, 2) fundamental data infrastructure architectures, and 3) applications of data analytics at scale to problems like, e.g., recommender systems, log mining, and opinion mining. These sessions will also be used for exam preparation and student discussions. Learning outcomes: L01, L02, L03, L04, L05, L06 - Practical: Practicals - During this sessions, students will be exposed to the systems discussed during the lectures and they will be able to develop their own data analytics solutions over these scalable systems. Learning outcomes: L01, L02, L03, L06 Official timetable activities: - Lecture | Wed 12:00 | 120 mins | 07-234 Parnell Building, Learning Theatre - Practical | Wed 14:00 | 120 mins | 47A-351 Sir James Foots Building, Collaborative Room Source: 2026 S1 UQ Course Profile - https://course-profiles.uq.edu.au/course-profiles/DATA7201-22188-7620
- 12
Lectures / Practicals
No separate week-by-week topic is publicly listed for Week 12; official repeated teaching activities are shown below: - Lecture: Lectures - Lectures will cover 1) use cases for data analytics at scale, 2) fundamental data infrastructure architectures, and 3) applications of data analytics at scale to problems like, e.g., recommender systems, log mining, and opinion mining. These sessions will also be used for exam preparation and student discussions. Learning outcomes: L01, L02, L03, L04, L05, L06 - Practical: Practicals - During this sessions, students will be exposed to the systems discussed during the lectures and they will be able to develop their own data analytics solutions over these scalable systems. Learning outcomes: L01, L02, L03, L06 Official timetable activities: - Lecture | Wed 12:00 | 120 mins | 07-234 Parnell Building, Learning Theatre - Practical | Wed 14:00 | 120 mins | 47A-351 Sir James Foots Building, Collaborative Room Source: 2026 S1 UQ Course Profile - https://course-profiles.uq.edu.au/course-profiles/DATA7201-22188-7620
Assessment
考核结构
Module quizzes (Series of 3) Online
Official due date: Week 6, Mon 3:00 pm Week 9, Mon 3:00 pm Week 13, Mon 3:00 pm Quizzes will open Mondays on Week 5, 8 and 12. Students will have one week to complete the quiz.. Source: 2026 S1 UQ Course Profile.
10%
Report on Dataset Analytics Online
Official due date: 22/05/2026 3:00 pm. Source: 2026 S1 UQ Course Profile.
60%
Final Exam Hurdle Identity Verified In-personHurdle
Official due date: End of Semester Exam Period 6/06/2026 - 20/06/2026. Source: 2026 S1 UQ Course Profile.
30%
From Seniors
学长留下的
基础信息谁都查得到,真正值钱的是过来人的经验。
学姐说
比你早一年的学长留下的真实经验 —— ChatGPT 给不了。
这门课还没有学长经验,你可以是第一个 —— 注册后在课内分享。
往年考点 / 踩坑
这门课暂无往年考点记录。
毕业生去向(整体)
下面是匠人学院毕业生整体去过的公司分布(来自脱敏校友证言)。这是全平台的总体去向,不代表选这门课的人一定去这些公司。
统计自 313 份脱敏校友证言
Zerologix
4 位校友岗位:Frontend Dev · junior frontend developer · Front-end Developer · Full Stack Developer
Servian
4 位校友岗位:Full-stack Developer · Data Engineer · Consultant
关于这块数据,我们说实话
雇主墙来自脱敏毕业生证言（testimonials）的整体分布，无法关联到具体学员或其所选课程；仅作为毕业生去向的总体社会证明展示。
我们没有"某位学长选了这门课、后来进了哪家公司"这种可查询的个人去向档案 —— 校友证言是脱敏的,无法关联到具体的人或他选过的课。所以这里只给整体分布,不给个人路径,不编。