Overview

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 Program 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.

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  • Starts on

    June 5, 2020

  • Duration

    3 Months, Online

    (4-6 hours per week)
  • Course Fees

    US$ 2,000*

Program Video

Curriculum & Faculty

syllabus

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

Case Studies / Assignments

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 London Time 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?

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

David Stillwell
David Stillwell

Academic Director of the Psychometrics Centre

Dr Nektarios (Aris) Oraiopoulos
Dr Nektarios (Aris) Oraiopoulos

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

Learning Experience

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

  • Orientation Week

    Orientation WeekThe 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 Setting

    Goal SettingOn other weeks, you have learning goals set for the week, including watching the video lectures and completing the assignments. All assignments have weekly deadlines.

  • Learning Videos

    Recorded Video LecturesThe recorded video lectures are by faculty from the collaborating university.

  • Live Webinars

    Live WebinarsDuring the programme, there are four live webinars conducted by Professor Ansari and Dr Munir. Live webinars are usually conducted between 1 p.m. and 3 p.m. UTC on Tuesdays or Wednesdays.

  • Q&A Sessions

    Q&A SessionsIn addition to the live webinars, Course Leaders also conduct Q&A sessions every week or every alternate week to help participants clarify any questions they may have regarding the programme content.

  • Follow-Up

    Follow-UpA Programme Support Team will follow-up through emails and via phone calls with participants who are unable to submit their assignments on time.

  • Continued Programme Access

    Continued Programme AccessYou will continue to have access to the programme videos and learning material for up to 12 months from the programme start date

 

Emeritus Programme Support Team

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

 

Device Support

You can access Emeritus courses on tablets, phones and laptops. You will require a high-speed internet connection.

 

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.

 

Program Highlights

<b>Organisational, Ethical and Legal Issues</b><br>Identify organisational issues that you will need to consider when making decisions; identify the legal and ethical issues behind gathering, storing, and using data
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
<b>Predictive Analytics</b><br>Use machine learning tools/models, identify neural networks, and analyse data to optimize decisions for your business
Predictive Analytics
Use machine learning tools/models, identify neural networks, and analyse data to optimize decisions for your business
<b>Experimentation</b><br>Design experiments to gather meaningful data to make data driven decisions
Experimentation
Design experiments to gather meaningful data to make data driven decisions
<b>Big Data Opportunities</b><br>Identify what big data means to you and what you can do with it
Big Data Opportunities
Identify what big data means to you and what you can do with it
<b>Descriptive Analytics</b><br>Be able to collect, clean, and describe the data you have, including the summary statistics
Descriptive Analytics
Be able to collect, clean, and describe the data you have, including the summary statistics
<b>Decision Biases</b><br>Identify the types of biases in a decision making process and learn how to ask for the right information
Decision Biases
Identify the types of biases in a decision making process and learn how to ask for the right information

CERTIFICATE

Certificate Click to view certificate

ADMISSION & FEES

 

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

FAQs

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