Professional Certificate in Digital Transformation Programme

Digital Transformation is Business Transformation

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Course Dates

STARTS ON

30 March 2023

Course Duration

DURATION

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

Course Fee

Applications close on 11 February 2023

Apply before 11 February 2023 to enjoy US$300 off the programme fee.
Use code APAC300TA during payment.

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.

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

Associate Alumni status and benefits

Associate Alumni status and 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

This module covers the basics of technologies that can disrupt existing industries and enable digital transformation for improving business performance and growth.

Module 2:

Business Strategy Under Digital Transformation

This module is about evolution and importance of business strategies across different industries – process, product, and service innovation and the need to change strategies for the digital world

Module 3:

Digital Business Models for a Digital Age

The module focusses on ways to enhance customer willingness to buy in the digital world. This module also emphasises on creating and evaluating the value proposition for a brand to achieve business growth.

Module 4:

Leveraging Data as a Competitive Edge

This module explains the basics of data and data science along with how data-enabled insights help leverage growth opportunities.

Module 5:

Data Analytics in Action

This module describes the different data types and data analytics. The module also introduces the different data analytical strategies and their usage to gain a competitive advantage.

Module 6:

Basic Statistics for Data Analysis

This module explains basic statistical concepts and how they help in strategic decision-making in a business.

Module 7:

Predictive Analytics

This module focusses on predictive analytics and their applications. The try-it activities in this module help reinforce the predictive analytic skills learnt in and identifying optimal models.

Module 8:

An Overview of Artificial Intelligence and Machine Learning (AI and ML)

This module describes concepts of artificial intelligence and machine learning and their significance. The module also describes the business data types and the best practices for data-driven transformation.

Module 9:

AI and ML Technologies Survey

This module focusses on the principles of supervised and unsupervised learning and the differences between the two.

Module 10:

ML for Data Analytics

This module explains machine learning (ML) and how it can help in increasing business performance. The module also describes the various Artificial intelligence (AI) and ML applications and trends.

Module 11:

AI/ML Applications and Trends

This module describes the AI applications in different sectors such as finance, energy, education, and security. It also describes the benefits and limitations of AI.

Module 12:

AI Led-Business Transformation

This module deals with creating an AI strategy. It describes AI-led business transformations and how these platforms align with digital business strategies

Module 13:

Development and Deployment of AI and ML Technologies

This module explores the machine learning life cycle and feature engineering. The module also discusses how to evaluate and deploy a machine learning model.

Module 14:

Addressing Key Challenges and Risks in Data Science

This module addresses the key challenges, risks in data science, and discusses failed data science projects and explains how to predict the success of a project.

Module 15:

Ethics

This module is about ethics and explains the main challenges involved in the application of ethics in various industries.

Module 16:

Privacy and Regulations in AI and ML

This module describes the ethical guidelines for AI, along with personal data protection, AI-specific regulations, and the extent of regulatory governance.

Module 17:

Data Science and the Future

This module explores the technology enablers for Industry 4.0. It also describes the components that are responsible for AI success while highlighting the challenges in AI implementation.

Module 18:

Digital Business Implementation: Challenges and Risks

This module focusses on how organisations use reflective communication to make customers aware of their digital solution. The module discusses frameworks that can help in implementing digital transformation plans successfully.

Module 19:

Business Model Innovation

This module discusses the importance of business model innovation for business growth. The module explains how technology can enable business model innovation and help transform an organisation.

Module 20:

Business Model Innovation with Digital Networks

This module helps outline an action plan to grow a business ecosystem for an organisation and create a digital business ecosystem. This module also enlists ways to enhance the value proposition of business ecosystem.

Module 21:

The Digital Organisation

This module covers the key barriers to the success of the digital transformation and guides on how to overcome those barriers.

Module 1:

The State of Disruption

This module covers the basics of technologies that can disrupt existing industries and enable digital transformation for improving business performance and growth.

Module 12:

AI Led-Business Transformation

This module deals with creating an AI strategy. It describes AI-led business transformations and how these platforms align with digital business strategies

Module 2:

Business Strategy Under Digital Transformation

This module is about evolution and importance of business strategies across different industries – process, product, and service innovation and the need to change strategies for the digital world

Module 13:

Development and Deployment of AI and ML Technologies

This module explores the machine learning life cycle and feature engineering. The module also discusses how to evaluate and deploy a machine learning model.

Module 3:

Digital Business Models for a Digital Age

The module focusses on ways to enhance customer willingness to buy in the digital world. This module also emphasises on creating and evaluating the value proposition for a brand to achieve business growth.

Module 14:

Addressing Key Challenges and Risks in Data Science

This module addresses the key challenges, risks in data science, and discusses failed data science projects and explains how to predict the success of a project.

Module 4:

Leveraging Data as a Competitive Edge

This module explains the basics of data and data science along with how data-enabled insights help leverage growth opportunities.

Module 15:

Ethics

This module is about ethics and explains the main challenges involved in the application of ethics in various industries.

Module 5:

Data Analytics in Action

This module describes the different data types and data analytics. The module also introduces the different data analytical strategies and their usage to gain a competitive advantage.

Module 16:

Privacy and Regulations in AI and ML

This module describes the ethical guidelines for AI, along with personal data protection, AI-specific regulations, and the extent of regulatory governance.

Module 6:

Basic Statistics for Data Analysis

This module explains basic statistical concepts and how they help in strategic decision-making in a business.

Module 17:

Data Science and the Future

This module explores the technology enablers for Industry 4.0. It also describes the components that are responsible for AI success while highlighting the challenges in AI implementation.

Module 7:

Predictive Analytics

This module focusses on predictive analytics and their applications. The try-it activities in this module help reinforce the predictive analytic skills learnt in and identifying optimal models.

Module 18:

Digital Business Implementation: Challenges and Risks

This module focusses on how organisations use reflective communication to make customers aware of their digital solution. The module discusses frameworks that can help in implementing digital transformation plans successfully.

Module 8:

An Overview of Artificial Intelligence and Machine Learning (AI and ML)

This module describes concepts of artificial intelligence and machine learning and their significance. The module also describes the business data types and the best practices for data-driven transformation.

Module 19:

Business Model Innovation

This module discusses the importance of business model innovation for business growth. The module explains how technology can enable business model innovation and help transform an organisation.

Module 9:

AI and ML Technologies Survey

This module focusses on the principles of supervised and unsupervised learning and the differences between the two.

Module 20:

Business Model Innovation with Digital Networks

This module helps outline an action plan to grow a business ecosystem for an organisation and create a digital business ecosystem. This module also enlists ways to enhance the value proposition of business ecosystem.

Module 10:

ML for Data Analytics

This module explains machine learning (ML) and how it can help in increasing business performance. The module also describes the various Artificial intelligence (AI) and ML applications and trends.

Module 21:

The Digital Organisation

This module covers the key barriers to the success of the digital transformation and guides on how to overcome those barriers.

Module 11:

AI/ML Applications and Trends

This module describes the AI applications in different sectors such as finance, energy, education, and security. It also describes the benefits and limitations of AI.

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Why Enrol in Professional Certificate in Digital Transformation?

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 Professional Certificate in Digital Transformation 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.

USD 1.05 Tn

Digital spending in Asia/Pacific to reach USD 1.05 trillion by 2026.

Source: IDC, 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

Example image of certificate that will be awarded after successful completion of this program

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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