BUSINESS ANALYTICS: DECISION MAKING USING DATA

ONLINE CERTIFICATE COURSE

OBJECTIVE

The Business Analytics programme provides you with the tools you need to put data to work: how to set up experiments, how to collect data, how to learn from data and make decisions to how to navigate the organisational, legal and ethical issues involved in data-based decision making. The programme teaches widely-used frameworks of business analytics: biases, experimentation, descriptive analytics, prescriptive analytics, predictive analytics. Participants then implement the frameworks they have learned through assignments. You will join a global and diverse group of participants in the discussion boards where you share your perspectives on the issues being discussed with other participants and seek their views.

 

WHO IS THIS PROGRAMME FOR?

This programme is designed for managers across different functions who are interested in implementing analytics projects at their organisation. It provides business managers with the techniques needed to transform their organisation into a data-driven organisation. The assignments and cases in the programme focus on interpreting the results of analysis and taking decisions based on those analysis. The programme will also include demonstration of some advanced analytics tools such as TensorFlow. The programme does not require coding.

 

WHAT ARE THE LEARNING OUTCOMES?

You will learn from outstanding faculty and associates of Cambridge Judge Business School Executive Education and gain an international experience from your global peer group.

After completing this programme, you will be able to:

  • Recognise different types of biases that give way to bad decision making and learn how to overcome them
  • Avoid bias in decision making by asking questions critical to your business and identifying the data needed to answer those questions
  • Learn about the sources of data, the intermediary software services that can fetch those data into your database, and then assess the quality of the collected data
  • Explain the reasons behind past events by analysing and summarising data
  • Predict future outcomes by choosing the appropriate machine learning algorithm to use in a business context
  • Learn the implementation challenges of creating a data-driven organisation
  • Understand the ethics and regulatory issues involved in making decisions using data

Business Analytics: Decision Making Using Data - Certificate

 

EMERITUS and Cambridge Judge Business School

Founded in 1990, Cambridge Judge Business School is part of the Faculty of Business and Management at the University of Cambridge. The reputation of Cambridge Judge Business School has grown rapidly, and today it is internationally celebrated as a provider of stimulating management education, with a particular emphasis on entrepreneurship and innovation management.

Cambridge Judge Business School Executive Education offers a wide range of open enrollment and customised programs designed for organisations, business professionals, managers, leaders, and executives from many different functions. These programs are developed to help executives and organisations from both the private and the public sectors achieve operational excellence and results.

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SYLLABUS

  • Decision traps
  • Benefits of analytics
  • What is data mining?
  • Web scraping
  • Application Programming Interface (API)
  • What data can you find?
  • What do you think about the data you found?
  • Amazon and APIs
  • Data cleaning
  • Descriptive statistics
  • Normal and not normal distributions
  • Effect size and confidence intervals
  • What does Big Data mean to you?
  • Introduction to Big Data
  • What is Big Data?
  • Four Vs of big data – volume, variety, velocity and veracity
  • Challenges for big data
  • Big Data opportunities
  • The gold standard
  • Making experimentation work
  • Overcoming barriers
  • Machine learning vs hypothesis testing
  • Machine learning in practice
  • Model over-fitting
  • Machine learning algorithms
  • Supervised machine learning
  • Decision trees & random forest
  • Support vector machines
  • Hyperparameter optimisation
  • Ensemble methods
  • Interpret an analysis
  • Machine learning in the real world
  • Applications of neural networks
  • The biology of animal neural networks
  • Assumptions for neural networks
  • How a neural network makes predictions
  • Choosing the network architecture
  • Recurrent neural networks
  • Reinforcement learning for businesses
  • What is prescriptive analytics?
  • Connecting predictive analytics to a business objective
  • Deep dive into a business model
  • Making a business decision
  • Decision Trees
  • SmartService Case
  • Risk aversion
  • Sunk cost fallacy
  • Diversification
  • Decision making process and debiasing
  • Implementation challenges
  • Setting up the right infrastructure
  • Big data strategy
  • GDPR
  • Privacy and Anonymization
  • Hacking and insider threats
  • Making customers comfortable

PROGRAM HIGHLIGHTS

Decision Biases

Decision Biases

Identify the types of biases in a decision making process and learn how to ask for the right information

Descriptive Analytics

Descriptive Analytics

Be able to collect, clean, and describe the data you have, including the summary statistics

Big Data Opportunities

Big Data Opportunities

Identify what big data means to you and what you can do with it

Experimentation

Experimentation

Design experiments to gather meaningful data to make data driven decisions

Predictive Analytics

Predictive Analytics

Use machine learning tools/models, identify neural networks, and analyse data to optimize decisions for your business

Organisational, Ethical and Legal Issues

Organisational, Ethical and Legal Issues

Identify Organisational issues that you will need to consider when making decisions; identify the legal and ethical issues behind gathering, storing, and using data

CASE STUDIES

Hotel Industry

Hotel Industry

How does a hotel booking platform test whether advertising on its website works?

Netflix

Netflix

How Netflix used a competition to improve their search and recommendation algorithms

Art

Art

How do you use neural networks to train computers to replicate the styles of different artists?

London Time

London Time

How many fashion watches should LondonTime order before the selling season begins?

Cambridge Breakthrough Science (Biotech Company)

Cambridge Breakthrough Science (Biotech Company)

How do they decide which 2 of the 4 promising drugs can be developed further?

UPS

UPS

How their ORION inititiative allowed UPS to save an estimated $300-$400 million and led to a reduction of 100 million miles driven?

Google Oxygen

Google Oxygen

How Google used data to see whether managers matter?

ASSIGNMENTS

Carter Racing

Carter Racing

How does a car racing team decide whether to participate in a race or not?

SmartService (Scientific Instruments Company)

SmartService (Scientific Instruments Company)

How does SmartService use a decision tree to calculate their bid for a new contract?

TalkTalk

TalkTalk

What should TalkTalk have done differently after they were hacked? How should they have protected their customers’ data?

FACULTY

  • Dr Nektarios (Aris) Oraiopoulo

    Dr Nektarios (Aris) Oraiopoulos

    University Lecturer in Operations Management, Director of the MPhil in Strategy, Marketing & Operations Programme

    University of Cambridge Executive Education

Dr Oraiopoulos earned his PhD from Georgia Institute of Technology. His research is focused on understanding how organisations make high-stakes decisions, such as whether to invest in a new project, when to terminate a project that is not performing well, what data they can leverage to become more innovative, and what organisational structures they should put in place to empower a sound decision-making process. He has worked with organisations across various industries and sectors, including AstraZeneca, British Telecom, HSBC, Johnson & Johnson, and the Abu Dhabi Police Force.

 

  • David Stillwell

    David Stillwell

    Academic Director of the Psychometrics Centre

    University of Cambridge Executive Education

David studies the links between big data and psychology; his research with 6 million social media users found that the computer can predict a user’s personality as accurately as their spouse can. Follow up research found that personalizing an advert to the recipient’s psychology is more effective than generic ads.

David has also published research using various big data sources to show that spending money on products and services that match one’s personality leads to greater life satisfaction, that people tend to date others who have a similar personality, and that people who swear seem to be more honest. David is currently pursuing research with companies’ internal data for People Analytics.

LEARNING EXPERIENCE

EMERITUS follows a unique online model. This model has ensured that nearly 90 percent of our learners complete their course.

  • OrientationOrientation Week
    The first week is orientation week. During this week you will be introduced to the other participants in the class from across the world. You will also learn how to use the learning platform and other learning tools provided.
  • Goal SettingWeekly Goals
    On other weeks, you have learning goals set for the week. The goals would include watching the video lectures and completing the assignments. All assignments have weekly deadlines.
  • Video LecturesLearning Videos
    The learning video lectures are by the faculty from the collaborating university. These are uploaded on our learning management platform at the start of the week as per the module.  The length of the lectures ranges from 1 minute to 10 minutes. These lectures cannot be downloaded. However, access to them is available for a year from the course commencement date.
  • Live WebinarsLive Webinars
    Live webinars are conducted periodically, and it’s schedule is shared via our learning management platform and calendar invites. These sessions are conducted by EMERITUS course leaders who contextualize the video lectures and assist with assignment related questions. You can ask questions using the Q&A board or the chat box. The recorded link of the webinar is shared within 24 hours.
  • Live Q&A SessionsLive Q&A Sessions
    The course leaders conduct Live Q&A Sessions regularly that last for an hour. This activity is to help participants clarify their doubts about the content. The schedule is shared via our learning management platform and calendar invites.
  • Follow-UpFollow-Up
    The EMERITUS Program Support team members will follow up and assist over email and via phone calls with learners who are unable to submit their assignments on time.
  • Continuous Course AccessContinued Course Access
    You will continue to have access to the course videos and learning material for up to 12 months from the course start date.

EMERITUS Program Support Team

If at any point in the course you need tech, content or academic support, you can email program support and you will typically receive a response within 24 working hours or less.

 

EMERITUS Network

On completing the course you join a global community of 5000+ learners on the EMERITUS Network. The Network allows you to connect with EMERITUS past participants across the world.

ADMISSION & FEES

DURATION AND COURSE FEE

  • Starts 13 December 2019
  • 3 Months
  • 4–6 hours per week
  • Programme Fees USD 2,000

PAYMENT

  • You can pay for the course either with an international debit or credit card (unfortunately we are unable to accept Diners credit cards), or through a bank wire transfer. On clicking the apply now button below, you will be directed to the application form and the payment page.
  • We provide deferrals and refunds in specific cases. The deferrals and refund policy is available here.
  • You will be provided a course login within 48 hours of making a payment.

APPLICATION PROCESS

  • Please provide your work experience and your current employer via the application.
  • You can apply by clicking the Apply Now button

COURSE FAQs

For any questions regarding Emeritus, the learning experience, admission & fees,  grading & evaluation please visit ONLINE CERTIFICATE COURSE FAQs

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