Strategic Business Transformation using AI/ML

Digital Transformation is Business Transformation

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Course Dates

STARTS ON

15 December 2022

Course Duration

DURATION

6 Months, Online
4-6 hours per week + Live sessions with faculty

Course Fee

Apply by 7 December 2022 to avail our Festive Enrolment Benefit of 20%.
Use the code FUTUREYOU20 during payment to avail.
Limited seats available!

New features:
Tools being covered in the programme -
●   Tableau
●   Weka
●   XLSTAT

Free One-Year Access to Emeritus Insights

This programme features 1 year of free Premium Access to Emeritus Insights—a mobile app with 5,000+ bite-sized, business-focused videos to help you meet your daily learning goals on the go.

Complimentary Annual Digital WSJ Membership

As a participant in the programme, you can enjoy a complimentary annual digital membership to The Wall Street Journal, giving you unlimited access to award-winning journalism across any device. From business and world news, to technology and life and arts, WSJ provides ambitious and fact-based reporting that readers can trust.

To ensure that holiday plans on the occasion of Christmas, New Year and Chinese New Year are not interrupted, no new modules will be released during this time and participants will receive a 2-week extension for submitting assignments. Participants will continue to have access to course material on the platform during this time.

WhatsApp an Advisor on +65 8014 3066
Have questions? Our Advisor will assist you promptly.

What Will This Programme Do For You?

  • Define business strategies underlying a digital transformation
  • Make data-driven decisions using data insights to create business strategies
  • Build and deploy AI and ML solutions to implement business strategies
  • Recognise the purpose of ethics and key challenges in the implementation of digital transformation business strategies
  • Create a strategy for innovation with digital networks leading to business transformation

Programme Highlights

Comprehensive Programme Design

Industry Relevant Curriculum

Recorded Videos and 5+ Live sessions with faculty

Recorded Videos and 5+ Live sessions with faculty

Career Acceleration with one of the World's Premium Universities

Networking Opportunities

SMU Associate Alumni Benefits

Tools

Tableau

Tableau

Visualization tool that helps analyse data and understand customer preference

Weka

Data mining tool that supports with data analysis and predictive modelling coupled with graphical user interface

XLSTAT

leading data analysis and statistical solution using Microsoft excel

Note: All brand, product and company names are trademarks™ or registered® trademarks of their respective holders.
Use of them does not imply any afliation with, endorsement by, or association of any kind between them and programme owners.

Programme Modules

Anchored by the overall theme of Planning and Executing the Digital Transformation, the programme is organised according to 3 Key Pillars:

  1. Digital Transformation
  2. Data Science & Analytics for Strategic Decisions
  3. Artificial Intelligence (AI) - Led Business Strategies

It is holistically curated to help you master basic through to advanced skill levels in various tools and technologies related to Data Science, Machine Learning, Deep Learning and Artificial Intelligence and provide you with a roadmap to achieve a successful digital transformation.

  • Module 1: The State of Disruption

    • Discuss the use of specific emergent technology for improving business performance
    • Identify how new technologies can disrupt existing industries and enable digital transformation
    • Explain the power of networks and how to use them for business purpose
    • Recognise the ways to harness emergent technologies to benefit businesses and enable disruption
    Module 2: Business Strategy Under Digital Transformation

    • Discuss the history and importance of business strategies
    • Describe the consequences of digitalisation of business strategies
    • Assess business strategy cases with process innovation and product and service innovation
    • Examine the future of business strategies in a fast-changing environment
    Module 3: Digital Business Models for a Digital Age

    • Identify opportunities that enable a firm to deliver greater values to its customers
    • Explain how segmentation enables a company to remap customers for digital growth
    • Create a value proposition for a company/brand
    • Evaluate the value proposition of a firm and reimagine it to achieve higher growth
    • Outline a plan for an organisation to create new values or grow more values for customers
    Module 4: Digital Business Implementation: Challenges and Risks

    • Evaluate the effectiveness of a new business model implementation by an organisation
    • Describe how organisations use emotions to create a reflex reaction to make customers aware of their digital solution
    • Identify how reflective communication enables customers to believe that a brand can deliver on its emotional promise
    • Create a matrix of solution expectations and experiences by segment for an organisation
    • Create a customer journey for a customer segment using the customer journey framework
    Module 5: Business Model Innovation

    • Explain the concept of business model innovation and how it transforms the entire organisation
    • Outline the growth plan of a business using the business model canvas
    • Identify the different triggers used by technology to enable a business model innovation
    Module 6: Business Model Innovation with Digital Networks

    • Draw the ecosystem of a company and discover the ways to enhance its value proposition with the help of new partners
    • Identify the appropriate approach to be an ecosystem builder/effective leader in digital business ecosystems
    • Outline an action plan to kickstart and grow a business ecosystem for an organisation
    Module 7: The Digital Organisation

    • Define your organisation - design, resources, people
    • Discuss the key barriers to the success of digital transformation
    • Create an executive summary for an organisation to adopt digitalisation
    • Examine your strengths to organisational understanding
  • Module 8: Leveraging Data as a Competitive Edge

    • Define the key terminologies of Data Science
    • Illustrate the different levels of Data Analytics and their significance to decision-making
    • Evaluate the applications of Data Analytics and its role in creating new business opportunities
    • Explore the features of data and data-enabled insights to attain sustainable competitive advantage
    Module 9: Data Analytics in Action

    • Identify appropriate analytical approach to resolve a business problem
    • Evaluate if your organisation is data-driven
    • Apply descriptive statistics to business data and obtain insights from it
    • Compare trends in data and obtain insights to leverage them for business performance
    • Analyse an organisation’s Omnichannel strategies and their impact on sales
    • Identify appropriate data/insights and determine suitable analysis approach for a business problem
    Module 10: Basic Statistics for Data Analysis

    • Illustrate hypothesis testing and types of errors
    • Apply various data analysis techniques to compare independent data sets to obtain insights
    • Apply strategic decision-making using data analysis techniques
    Module 11: Predictive Analytics

    • Apply the basics of regression to analyse the strength of variables and their impact
    • Predict variable impact using optimal model fit and regression effects
    • Build a logistic regression model to test and predict expected outcomes
    • Apply predictive analytics using logistic regression to optimise organisational efficiency
    Module 12: AI/ML for Data Analytics

    • Explain ML techniques and the ML workflow
    • Analyse Neural Networks and Deep Learning with examples
    • Evaluate the applications of AI in Retail, Healthcare and Manufacturing
    • Explain the concept of Machine Learning and its role in driving organisational productivity
    • Outline how Machine Learning algorithms can be applied to achieve optimal analytical accuracy
    • Explore the facets of Neural Networks and Deep Learning to understand how to build a programme that learns from data
    • Demonstrate how analytics can be combined with experiments to produce effective business strategies
    Module 13: Addressing Key Challenges and Risks in Data Science Projects

    • Identify the key challenges to Data Science projects and strategise solutions to overcome them
    • Identify project-level risks and examples of failed Data Science projects
    • Predict the success of your Big Data project using the DATA technique
    • Apply the DELTA Framework and the DELTA Plus Model to optimise your organisation’s Data Analytics journey
    Module 14: Data Science and the Future

    • Identify the drivers, expected outcomes and technology enablers for Industry 4.0
    • Identify the components for AI success that can be leveraged to strengthen organisational capabilities
    • Discuss the challenges in the implementation of AI in systems
    • Evaluate an organisation’s digital transformation journey and explain the ways to sustain their competitive advantage
  • Module 15: An Overview of Artificial Intelligence and Machine Learning (AI and ML)

    • Explain the concepts of Artificial Intelligence and Machine Learning along with their significance
    • Explain the significance and types of Data and Analytics in the context of business
    • Evaluate if your organisation is data-driven
    • Analyse the best-practices of undertaking a data-driven transformation
    Module 16: AI and ML Technologies Survey

    • Explain the principles of Supervised and Unsupervised Learning and describe the differences between them
    • Explain the difference between Regression and Classification
    • Explore the facets of Neural Networks and build a programme that learns from data
    • Explain how Convolutional Neural Networks apply to images and computer vision problems
    • Survey unsupervised learning algorithms such as clustering, matrix factorisation and representation learning
    • Describe Recurrent Neural Networks and Transformer-based architectures and explain how they impact language understanding
    Module 17: AI/ML Applications and Trends

    • Evaluate the applications of AI in finance, energy, education, and security sectors
    • Discuss the benefits and limitations of AI
    • Describe the application of AI framework for business
    • Analyse how AI can be leveraged as a driver for digital transformation
    Module 18: AI Led-Business Transformation

    • Describe the process for AI strategy creation and identify potential reasons for failure
    • Evaluate the Buy vs Build platforms for optimising AI-led business transformations
    • Identify AI opportunities and understand how to align them with digital business strategies
    • Explore various facets of the future of AI
    • Compare correlation and causality and describe their significance to enhance business performance
    • Apply experimentation to business problems to make effective inferences
    • Explain Multivariate, A/B and Multi-Armed Bandit testing and their significance in understanding user behaviour
    • Evaluate the effectiveness of a firm’s experimental design to make data-informed recommendations for business growth
    Module 19: Framework for Model Evaluation and Deployment of AI and ML

    • Identify the key challenges to Data Science projects and strategise solutions to overcome them
    • Identify project-level risks and examples of failed Data Science projects
    • Predict the success of your Big Data project using the DATA technique
    • Apply the DELTA Framework and the DELTA Plus Model to optimise your organisation’s Data Analytics journey
    Module 20: Ethics

    • Define the concept of ethics and explain its significance in the context of organizations and technology
    • Establish the purpose and relevance of ethics with regard to AI/ML, and define the corresponding ethical codes and guidelines
    • Analyse the main challenges involved in ethics and industry applications
    • Explore the values and ideas related to AI/ML, technology, data, and ethics
    • Evaluate how challenges relating to ethics and its industry applications can be addressed
    Module 21: Privacy and Regulations in AI and ML

    • Explain the guidelines for ethics and trust related to AI
    • Examine the AI-specific regulations in law and the extent of regulatory governance.
    • Analyse the concept of Personal Data Protection and the impact of AI on data rights and obligations
    • Describe the role of AI in eCommerce and the legality of Electronic Advertising and Marketing
    • Outline a plan that can help an organisation improve its compliance with AI ethical guidelines and law

Why Enrol in Strategic Business Transformation using AI/ML?

Digital transformation is an evolving trend, and organisations need to understand that everything will constantly (but digitally) change. The most significant investment in Digital Transformation is not in the technology but people. Digital transformation depends upon the digital qualifications of the leaders and professionals who need to roll out the processes and services for transformation. With data analytics becoming a core and essential capability for every organisation, enhancing skills and organisational structures for competitive digital transformation will be critical.

The Strategic Business Transformation using AI/ML programme is expertly designed to endow business leaders and professionals with a keen understanding of the new digital paradigm that represents the technological revolution we live in today and the key technologies behind the revolution.

50%

Forbes reports that 50% of enterprises plan to spend more on AI and machine learning in 2021 and 20% report significant increases to their budgets.

SOURCE: THE STATE OF AI IN BUSINESS, 2022

16.5%

The global digital transformation market size is expected to grow from USD 469.8 billion in 2020 to USD 1009.8 billion by 2025, at a Compound Annual Growth Rate (CAGR) of 16.5% during the forecast period.

SOURCE: RESEARCH AND MARKETS, 2021

86%

of CEOs report that AI is considered mainstream technology in their office as of 2021.

SOURCE: THE STATE OF AI IN BUSINESS, 2022

Programme Faculty

DR MARKUS KARNER

SMU Academic Director, Executive Development

DR LES BUCKLEY

SMU Affiliated Faculty of Strategic Management

DR SHANTANU BHATTACHARYA

SMU Professor of Operations Management

DR ARNOUD DE MEYER

Former SMU President, Professor Emeritus of Operations Management

DR FLOCY JOSEPH

SMU Programme Director, Executive Development

DR SANDEEP R. CHANDUKALA

Associate Professor of Marketing

DR MICHELLE CHEONG

Professor of Information Systems (Education); Associate Dean, SCIS Post-Graduate Professional Education; Director, Doctor of Engineering

DR HADY W. LAUW

Associate Professor of Computer Science; Director, BSc (Computer Science) Programme; Lee Kong Chian Fellow

DR DAI BING TIAN

Assistant Professor of Computer Science Education; Director, MITB Artificial Intelligence Programme

PROFESSOR GARY CHAN KOK YEW

Professor of Law

PROFESSOR WARREN B. CHIK

Associate Professor of Law; Deputy Director, Centre for AI and Data Governance

Who Is This Programme For?

The programme is applicable across leadership, managerial, operations, and consultancy functions; in major industries such as Banking & Finance, Healthcare, IT Product & Services, Consulting. It is suited for both technical and non-technical audiences, and does not require prior coding knowledge.

This programme is designed for senior professionals and leaders who want to lead digital transformation in their organisation by:

  • Transforming their business models to suit a digital customer
  • Incorporating strategic digital transformation in their function/organisation
  • Creating competitive advantage through business model innovations

Certificate

Certificate

Upon successful completion of the programme, participants will be awarded a verified digital certificate by Singapore Management University.

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All certificate images are for illustrative purposes only and may be subject to change at the discretion of Singapore Management University.

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