University of Cambridge
Overview
This is an opportunity to learn from the faculty and associates of Cambridge University and gain an international experience and perspective from your global peer group.
It is not optional but it is essential to be able to make decisions informed by data, in the digital economy. People make decisions based on data and perform better.
The programme provides you with the tools for you to set up experiments, to collect data together to work, to learn from data, and to make decisions to navigate the legal and ethical issues involved in data-based decision making.
You will learn widely used frameworks of biases, experimentation, descriptive analytics, prescriptive analytics, predictive analytics.
You will implement the frameworks you have learned through the programme.
You will meet a global and diverse group of participants to share your perspectives on the issues being discussed with other participants and seek their views.
It is not optional but it is essential to be able to make decisions informed by data, in the digital economy. People make decisions based on data and perform better.
The programme provides you with the tools for you to set up experiments, to collect data together to work, to learn from data, and to make decisions to navigate the legal and ethical issues involved in data-based decision making.
You will learn widely used frameworks of biases, experimentation, descriptive analytics, prescriptive analytics, predictive analytics.
You will implement the frameworks you have learned through the programme.
You will meet a global and diverse group of participants to share your perspectives on the issues being discussed with other participants and seek their views.
Programmes
Decision-Making Using Data
In the present digital economy, it is essential:- to use data for informed decisions
- to focus on interpreting results of analysis
- to gain the tools you need to put data to work
- to maximise your data-based decision making
- to transform your business into a data-driven organisation
- Perceive the ethics and regulatory issues involved in making decisions using data
- Learn about the sources of data for you to fetch those data into your database and to evaluate the quality of the collected data
- Identify different types of biases that lead to bad decision making
- Keep away biases in decision making by identifying the data needed to answer the questions critical to your business
- Make analysis of data in order to explain the reasons behind past events
- Implement challenges of creating a data-driven organization
- Indicate future outcomes by choosing the precise machine learning a set of mathematical instructions or rules, algorithmic rules to use in a business context.
Syllabus
The programme is to cover about six areas of decision-making using data and it includes lectures, discussions and assignments, including the visits to a number of industries.
Modules
- Module 1: Decision Biases
- Module 2: Big Data Opportunities
- Module 3: Descriptive Analytics
- Module 4: Predictive Analytics – Machine Learning and Neural Networks
- Module 5: Prescriptive Analytics – Behavioural Economics Biases
- Module 6: Ethics/Legal and Organisational issues
Duration
3 weeks
- 1 week Online preparation lesson
- 2 weeks Onsite residential lesson
Dates
Spring Course
Online the 2nd week of March
Onsite the 3rd and 4th week of March
Onsite the 3rd and 4th week of March
Summer Course
Online the 2nd week of August
Onsite the 3rd and 4th week of August
Onsite the 3rd and 4th week of August
Accommodation
- Homestay
- University of Cambridge College Residence
English Proficiency
It is advisable that the participant has the following proficiency in English to take the course.
- TOEFL CBT® 213~283
- TOEFL PBT® 550~657
- TOEFL iBT® 80~116
- IELTS 6.0~7.5
- TOEIC ® 820~970
■CEFR / IELTS / TOEFL / PTE / TOEIC / EIKEN
CEFR | IELTS | TOEFL iBT | TOEFL CBT | TOEFL PBT | PTE | TOEIC | EIKEN |
---|---|---|---|---|---|---|---|
C2 | 9 | 120 | 297-300 | 673-677 | 87-90 | - | - |
8.5 | 119 | 293 | 670 | 83-86 | - | - | |
C1 | 8 | 117-118 | 287-290 | 660-667 | 79-82 | - | - |
7.5 | 109-116 | 267-283 | 630-657 | 73-78 | 970-990 | - | |
7 | 100-108 | 250-263 | 600-627 | 65-72 | 870-970 | Grade 1 | |
B2 | 6.5 | 90-99 | 233-247 | 577-597 | 58-64 | 820-870 | - |
6 | 80-89 | 213-230 | 550-573 | 50-58 | 740-820 | Grade Pre-1 | |
5.5 | 69-79 | 192-212 | 521-549 | 42-49 | 600-740 | - | |
B1 | 5 | 61-68 | 173-190 | 500-520 | 35-42 | 550-600 | Grade 2 |
4.5 | 52-60 | 150-170 | 470-499 | 28-34 | 500-550 | - | |
4 | 45-51 | 130-149 | 450-469 | -27 | 450-490 | Grade Pre-2 | |
A2 | 3.5 | 33-44 | 110-129 | 400-449 | - | 300-440 | - |
3 | 29-32 | 100 | 391-399 | - | 291-299 | Grade 3 | |
A1 | 2.5 | 20-28 | 90 | 390 | - | 270-290 | - |
2 | 12-19 | - | 350-389 | - | 260-269 | Grade 4 | |
1.5 | - | - | - | - | 100-259 | Grade 5 |
For whom
The course is for university students who intend to drive analytics projects at their future organisations, and present business managers across different functions.