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====== AI in business ======


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Designing a course on AI for business owners requires a comprehensive outline that covers various aspects of artificial intelligence and its practical applications in business. Below is a sample course outline for an AI for Business Owners course:


**Module 1: Introduction to AI in Business**

- **1.1 Overview of Artificial Intelligence**

  - Definition and key concepts

  - Historical development of AI

  - Types of AI: Narrow AI vs. General AI



- **1.2 Importance of AI for Business Owners**

  - Enhancing efficiency and productivity

  - Gaining a competitive edge

  - Identifying business opportunities with AI



- **1.3 Common AI Terminology**

  - Machine learning, deep learning, natural language processing, etc.

  - AI applications: Robotics, computer vision, recommendation systems, etc.



**Module 2: AI Technologies and Tools Overview**

- **2.1 Machine Learning Basics**

  - Supervised learning, unsupervised learning, reinforcement learning

  - Training and testing data



- **2.2 Deep Learning**

  - Neural networks

  - Deep neural networks and their applications



- **2.3 Natural Language Processing (NLP)**

  - Understanding and processing human language

  - NLP applications in business



- **2.4 Tools and Platforms**

  - Overview of popular AI frameworks (TensorFlow, PyTorch)

  - Cloud-based AI services (AWS, Azure, Google Cloud)



**Module 3: AI Implementation in Business**

- **3.1 Identifying Business Problems Suitable for AI**

  - Case studies of successful AI implementations

  - Assessing feasibility and ROI



- **3.2 Data Collection and Preprocessing**

- Importance of quality data

- Data cleaning and preparation



- **3.3 Building AI Models for Business**

- Selecting the right algorithm

- Training and fine-tuning models



**Module 4: Ethical Considerations in AI**



- **4.1 Ethical Issues in AI**


- Bias and fairness

- Transparency and accountability

- Privacy concerns


- **4.2 Implementing Ethical AI Practices in Business**

- AI ethics policies

- Responsible AI development and deployment

**Module 5: Integration of AI into Business Operations**

- **5.1 AI in Marketing and Sales**

- Customer segmentation

- Personalization and recommendation engines

- **5.2 AI in Operations and Supply Chain Management**

- Inventory optimization

- Predictive maintenance


- **5.3 AI in Finance and Decision-making**

- Fraud detection

- Risk assessment

**Module 6: Overcoming Challenges in AI Adoption**

- **6.1 Addressing Resistance and Cultural Shift**

- Change management strategies

- Employee training and upskilling


- **6.2 Managing Security Risks in AI Systems**

- Cybersecurity considerations

- Protecting sensitive data

**Module 7: Future Trends in AI and Business**

- **7.1 Emerging Technologies**

- Quantum computing

- Edge computing

- **7.2 Continuous Learning and Adaptation**

- Staying updated on AI advancements

- Future-proofing AI implementations

**Module 8: Capstone Project and Case Studies**

- **8.1 Applying AI Concepts to Real-world Business Challenges**

- Group projects

- Analysis of successful AI implementations in various industries

**Conclusion and Graduation**

- **Closing Remarks**

- Recap of key learnings

- Opportunities for further exploration in AI for business

 


**Benefits of this course**


Ability to assess the implications and applications of AI in your industry and build a business case for its implementation

[[products:ict:ai:framework_for_ai|Robust framework to critically examine the social implications and ethics of AI
]]



[[https://cyber.harvard.edu/events/accounting-ai-comparison-methods|
Accounting for AI — a Comparison of Methods]]


[[https://cyber.harvard.edu/story/2021-09/open-access-resources-ai-schools|
Open Access Resources for AI in Schools]]


[[https://cyber.harvard.edu/story/2021-08/new-approach-experiential-learning-scholars-inform-city-helsinki-ethical-ai|
A New Approach to Experiential Learning: Scholars inform the City of Helsinki on ethical AI applications for schools during BKC’s AI Policy Research Clinic]]


[[https://cyber.harvard.edu/story/2023-03/how-ai-could-write-our-laws|
How AI could write our laws]]


[[https://cyber.harvard.edu/story/2023-02/ai-generated-works-artists-and-intellectual-property|
On AI-Generated Works, Artists, and Intellectual Property]]


[[https://cyber.harvard.edu/story/2023-02/can-we-people-keep-ai-check|
Can ‘we the people’ keep AI in check?]]


[[https://cyber.harvard.edu/story/2023-02/chatgpt-and-beyond-whats-behind-ai-boom|
ChatGPT And Beyond: What’s Behind The AI Boom?]]


[[https://cyber.harvard.edu/story/2023-02/expert-warns-ai-tools-potential-threat-democracy|
Expert warns of AI tools’ potential threat to democracy]]


[[https://cyber.harvard.edu/story/2023-02/chatgpt-could-be-useful-ai-tool-so-how-are-we-regulating-it|
ChatGPT could be a useful AI tool. So how are we regulating it?]]


[[https://cyber.harvard.edu/story/2023-01/meet-three-artists-behind-landmark-lawsuit-against-ai-art-generators|
Meet The Three Artists Behind A Landmark Lawsuit Against AI Art Generators]]


[[https://cyber.harvard.edu/story/2023-01/how-chatgpt-hijacks-democracy|
How ChatGPT Hijacks Democracy]]


[[https://cyber.harvard.edu/projects/ai-algorithms-and-justice|
AI: Algorithms and Justice]]


[[https://cyber.harvard.edu/programs/bkc-policy-practice-artificial-intelligence|
BKC Policy Practice: Artificial Intelligence]]


[[https://aiethicsinitiative.org/|
The Ethics and Governance of Artificial Intelligence Initiative]]



[[https://cyber.harvard.edu/ethics-and-governance-ai-reading-list|
Ethics and Governance of AI Reading List]]


[[https://cyber.harvard.edu/ethics-and-governance-ai-supporters-collaborators-and-friends|
Ethics and Governance of AI Supporters, Collaborators, and Friends]]


[[https://www.youtube.com/playlist?list=PL68azUN8PTNjTUsspsam0m0KmmUZ6l1Sh|
Ethics & Governance of Artificial Intelligence 
The Berkman Klein Center for Internet & Society
38 videos 2,210 views Last updated on 11 Jul 2018]]


[[https://hls.harvard.edu/today/morality-in-the-machines/|
Morality in the Machines]]


[[https://www.bostonmagazine.com/news/2017/11/12/ai-research-boston/|
The Robots Are Coming]]


[[https://hbr.org/2022/03/ethics-and-ai-3-conversations-companies-need-to-be-having|
Ethics and AI: 3 Conversations Companies Need to Have]]


[[https://news.harvard.edu/gazette/story/2020/10/ethical-concerns-mount-as-ai-takes-bigger-decision-making-role/|
Great promise but potential for peril]]


[[https://venturebeat.com/ai/the-state-of-ai-ethics-the-principles-the-tools-the-regulations/|
The state of AI ethics: The principles, the tools, the regulations]]


[[https://cguttmann.medium.com/an-overview-of-artificial-intelligence-ethics-and-regulations-917859fdcb77|
An Overview of Artificial Intelligence Ethics and Regulations]]


[[products:ict:ai:concepts_of_ai|Conceptual understanding of machine learning algorithms, deep learning and neural networks
]]


Guidance from leading industry experts 


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===== Topics =====


**[[products:ict:ai:ai_ecosystem|Artificial Intelligence ecosystem.
]]**

Explore the history and potential of AI within the context of the digital ecosystem. 


**[[products:ict:ai:ai_as_a_blackbox|AI and machine Learning: Understanding the black box.]]**

Delve into the mechanics of the three main types of machine learning: supervised, reinforcement, and unsupervised learning.


**[[products:ict:ai:deep_learning|Understanding deep learning and neural networks.]]**

Understand what deep learning is and how it is powering the modern approach to AI. 


**[[products:ict:ai:working_with_intelligent_machines|Working with intelligent machines.]]**

Explore the concept of intelligence in machines and the impact of AI in the labour market. 


**[[products:ict:ai:ethics|The ethics of artificial intelligence.]]**

Explore the hierarchy of ethical and legal considerations around AI.

**[[products:ict:ai:how_to_drive_ai_in_business|How to drive AI in your business.]]**

Identify the potential business opportunity of AI in a specific context.


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[[https://aibusiness.com/|AI Business is the leading content portal for artificial intelligence and its real-world applications.]]


[[https://www.youtube.com/watch?v=IBe2o-cZncU|Who Invented A.I.? - The Pioneers of Our Future]]



[[https://www.youtube.com/watch?v=AXgjEW2nA9I|The 10 Best Examples Of Artificial Intelligence (AI) And Machine Learning In Practice]]

[[https://www.youtube.com/watch?v=IBe2o-cZncU|Who Invented A.I.? - The Pioneers of Our Future]]

[[https://www.youtube.com/watch?v=Y46zXHvUB1s|Top 10 Applications Of Artificial Intelligence in 2021 | Artificial Intelligence Training | Edureka]]


[[https://www.businessnewsdaily.com/9402-artificial-intelligence-business-trends.html|How Artificial Intelligence Will Transform Businesses]]

[[https://aiforbusiness.withgoogle.com/en-GB_uk/|Grow your business with AI]]

[[https://www.youtube.com/watch?v=N_eHmaRf9T4|How to Apply AI in Business]]


[[https://www.youtube.com/watch?v=dNZXLH4xeAs|How to Insert AI into business processes and what are the critical factors to consider?]]



Artificial Intelligence might sound like something from the future, but it’s already helping thousands of organisations grow their revenue and work more efficiently. Use our check-up tool to see how it could benefit your business. 

[[https://connect.comptia.org/blog/using-ai-in-business| Using AI in Business: Examples of Artificial Intelligence Application in Business ]]

[[https://www.youtube.com/watch?v=fUiezSdnYZ0|MIT Bootcamps: How to identify business opportunities with AI]]


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[[https://www.coursera.org/specializations/ai-for-business-wharton|AI For Business Specialization]]

[[https://www.nibusinessinfo.co.uk/content/examples-artificial-intelligence-use-business|
Artificial intelligence in business
Examples of artificial intelligence use in business]]

[[https://levity.ai/blog/8-uses-ai-business|7 Applications of Artificial Intelligence in Business]]

[[https://www.techtarget.com/searchenterpriseai/tip/9-top-applications-of-artificial-intelligence-in-business|9 top applications of artificial intelligence in business]]




[[https://eit.europa.eu/sites/default/files/emerging_ai_and_data_driven_business_models_in_europe_final.pdf|
EMERGING AI AND DATA DRIVEN BUSINESS MODELS IN EUROPE]]



[[https://executivecourses.com/lists/top-10-executive-courses-in-ai-and-machine-learning|
Top 10 Executive Courses in AI and Machine Learning
]]

[[https://executivecourses.com/schools/usa/massachusetts/massachusetts-institute-of-technology-mit-sloan-school-of-management-executive-education|Massachusetts Institute of Technology (MIT) - Sloan School of Management - Executive Education]]

AN INTRODUCTION TO ARTIFICIAL INTELLIGENCE

This introductory module guides you through the evolution of key
AI technologies and how they have developed to transform industry
and business practice. The relationship between AI and collective
intelligence, as well as the implications of this partnership for
business strategy and society are also introduced. As part of
an ongoing project, you’ll begin to consider your own organization
in terms of the application of AI technologies.


MACHINE LEARNING IN BUSINESS

In this module, you’ll explore the core concepts of machine
learning – an AI technology which aims to design, understand,
and use computer programs to learn from experience. Discover
how machine learning can be successfully integrated into business
functions through rich case studies and faculty-led videos that
examine the opportunities that this subfeld of AI affords.
For your ongoing project, you’ll propose ideas for the application
of machine learning in a business context of your choice.


[[products:ict:ai:natural_language_processing_in_business|NATURAL LANGUAGE PROCESSING IN BUSINESS]]

This module is devoted to natural language processing (NLP),
an AI technology developed to intelligently process human
language. Through rich case studies and faculty-led videos, which
explore functions such as machine translation, summarization,
and sentiment analysis, you’ll learn how NLP can be skillfully
deployed in a series of business contexts. For the next part of your
project, the focus will shift to NLP and its strategic implementation
in a business context of your choice.


ROBOTICS IN BUSINESS

[[https://www.cnbc.com/video/2023/03/21/rise-of-the-robots-nvidia-and-adobe-announce-ai-partnership.html|
Rise of the Robots: Nvidia and Adobe announce A.I. partnership]]


This module delves into the key elements of robotics as a
transformative AI technology, with a focus on automating
processes and tasks. Through rich case studies and faculty-
led videos that survey robots and autonomous vehicles, you’ll
learn how robotics can beneft an organization. You’ll have the
opportunity, once more, to submit ideas regarding the potential
for robotics to be deployed in a business context of your choice




[[https://www.businessinsider.com/hyundai-electric-car-charging-robot-ioniq-6-tesla-snake-2023-3|
Watch: Hyundai revealed a one-armed robot that charges your electric car for you]]






ARTIFICIAL INTELLIGENCE IN BUSINESS AND SOCIETY

[[https://www.youtube.com/watch?v=Xz2kaQWQSJk|
Artificial Intelligence’s Impact on Business]]


In this module, you’ll see examples of other kinds of AI as well
as return to collective intelligence and the human-machine
relationship. Here you’ll also consider the impact of AI on jobs,
and the ethical and social implications of AI integration.
You’ll be tasked with anticipating and planning for the risks
and considerations that may apply to integrating AI in a business
context of your choice.


[[https://www.youtube.com/watch?v=P6vwNM_ecFk|
What Are The Negative Impacts Of Artificial Intelligence (AI)?]]



THE FUTURE OF ARTIFICIAL INTELLIGENCE

[[https://www.youtube.com/watch?v=dctcfxw13AQ|
Beyond ChatGPT: what chatbots mean for the future]]



This module will allow you to imagine the future of AI and its
potential use in your organization. Using what you have learned
from the previous modules, you’ll create a business roadmap for
the strategic implementation of AI and collective intelligence into
an organization of your choice.

 



[[https://executive.mit.edu/course/artificial-intelligence/a056g00000URaa3AAD.html|
Artificial Intelligence: Implications for Business Strategy
]]


[[https://executive.mit.edu/on/demandware.static/-/Sites-master-catalog-msee/default/dwaa8ddbd9/brochures/ai-online-program-brochure.pdf|ARTIFICIAL INTELLIGENCE: IMPLICATIONS FOR BUSINESS STRATEGY]]


[[https://www.mckinsey.com/business-functions/mckinsey-analytics/our-insights/an-executives-guide-to-ai|An executive’s guide to AI]]

[[https://www.es.unisg.ch/en/programme/artificial-intelligence-executives| Artificial Intelligence for Executives
Develop the Mindset, Knowledge, and Skills for the Digital Age ]]


**AI Business Models**

[[https://www.forbes.com/sites/forbestechcouncil/2021/05/05/10-business-models-that-reimagine-the-value-creation-of-ai-and-ml/?sh=24eb725368e9|
10 Business Models That Reimagine The Value Creation Of AI And ML]]

[[https://emerj.com/ai-executive-guides/ai-business-models-part-1/|
Comparing 5 AI Business Models – Part 1 – Transformation or Near-Term Value?]]


[[https://emerj.com/ai-executive-guides/near-term-ai-trends-a-guide-for-mid-size-business-leaders/|
Near-Term AI Trends – A Guide for Mid-Size Business Leaders]]

 

[[https://emerj.com/ai-executive-guides/ai-career-gap/|
The AI Career Gap – AI Knowledge as a Career Accelerator]]

 

[[https://viso.ai/deep-learning/ml-ai-models/|
The Ultimate Guide to Understanding and Using AI Models (2023)]]
 

[[https://www.clickworker.com/customer-blog/ai-new-business-models/|
AI Creates New Business Models]]


[[https://medium.com/predict/choosing-the-right-ai-business-model-df5d81420d74|
Choosing The Right AI Business Model]]













Personal Impact Mission (13 October 2021)

Yukiko Kobayashi

Big Data & Data Management (18 October 2021, 15:00-17:00)

Prof. Dr. Thomas Hofmann, ETH Zurich & Dr. Jürgen Galler, CEO 1plusX

AI & Machine Learning (27 October 2021)

Prof. Dr. Damian Borth, University of St.Gallen

The Platform Economy (03 November 2021)

Dr. Holger Schmidt




Nicole Büttner, Co-founder & CEO Merantix Labs

AI, Ethics and Regulations (17 November 2021)

Prof. Dr. Valentin Jeutner, University of Lund & Nanda Bergstein, Director Corporate Responsibility - Tchibo

AI-based Leadership (23 November 2021)

Prof. Dr. Miriam Meckel, University of St.Gallen & Léa Steinacker, Co-Founder and Chief Operations Officer of ada


Learning objectives

 
Learn existing functions within banks to uncover potential inefficiencies

Compare and contrast how standard versus digital banks perform given functions in your country

Determine the best tactics to attract new customers for loans and identify the holes in the way customers are currently found

Consider which functions would be better utilised with machine learning or artificial intelligence

Understand the limitations of ML and AI and how to use them to analyse results and determine risk factors


[[https://www.genome.gov/about-genomics/educational-resources/fact-sheets/artificial-intelligence-machine-learning-and-genomics|
Artificial Intelligence, Machine Learning and Genomics]]

[[https://www.ibm.com/cloud/blog/ai-vs-machine-learning-vs-deep-learning-vs-neural-networks|
AI vs. Machine Learning vs. Deep Learning vs. Neural Networks: What’s the Difference?]]


[[https://towardsdatascience.com/the-limitations-of-machine-learning-a00e0c3040c6|
The Limitations of Machine Learning]]


[[https://www.machinelearningpro.org/limitations-of-machine-learning/|
Limitations Of Machine Learning: Facts You Should Know]]

[[https://resources.experfy.com/ai-ml/limitations-of-machine-learning/|
The Limitations of Machine Learning]]



Apply the concepts and applications of ML and AI to real-world scenarios

Determine situations that should utilise cryptocurrency versus digital fiat currency

Sort risks according to whether they apply to fintech or regular financial institutions

Predict which functionalities will remain in banks or switch to an outside entity

Develop a plan for integration of fintech within a financial organisation

What you will learn

Module 1: Digital Transformation and Financial Services

Module 2: Personal Banking

Module 3: Lending Markets

Module 4: Applications of Machine Learning in Fintech; Risk Management and Credit Scoring

Module 5: Digital Distributed Ledger: Blockchain and Cryptocurrencies

Module 6: Regulations

Module 7: Fintech Capstone Project


[[https://www.accenture.com/sg-en/insight-explained-guide-executives|A guide to AI for executives]]

EXPLAINED a guide to AI for executives

The single biggest technology revolution the world has ever seen


Is AI anything more than the latest technology buzzword?

So what is AI anyway?


AI as we know it isn’t really a technology in its own right at all.

Wait, haven’t we been there before?

AI is far from a new idea, with a term coined as long ago as 1956, how far have we come?

Ok, I’m sold. But what do I actually need to do now?

In such a fast-moving field, it can be hard to see the wood for the trees.

Hold on, we haven’t talked about the risks involved

It pays to begin an AI journey with a clear sighted vide of the risks involved.

And what about the bigger picture?

The actions we take when it comes to AI can reverberate way beyond the boundaries of a single organisation.

It’s time to get smart and get started

As it gains critical mass, AI will change how we work and live, forever.



----


Unlocking the power of artificial intelligence in the digital age

Artificial intelligence (AI) is empowering significant and rapid change for businesses across almost all sectors and industries. In particular, machine learning – a computer’s capacity to improve its performance without human instruction – is driving the development of new applications that can accelerate productivity and competitive edge for companies.

From the automation of different aspects of business to forecasting patterns in data, AI can accomplish tasks with far greater accuracy and speed than human beings – transforming not only what businesses and managers can do, but how they do it. Healthcare, finance, retail and travel organisations are delivering completely new customer experience thanks to chatbots, intelligent voice assistants and conversational AI. Meanwhile, an array of new machine learning applications are giving businesses access to deep analysis of key internal data (such as employee engagement, networks and departures) for organisation redesign.

Transforming Your Business with AI gives you a deep understanding of how AI is deployed in business, so that you can see what it can (and cannot) do for you and your organisation. The programme equips you with practical frameworks and templates to work with data scientists and programmers, showing you how to commission analysis and analyse the results you receive.

**How you benefit**

Gain solid, jargon-free understanding of AI, Machine Learning and the opportunities for your organisation.

[[https://www.forbes.com/sites/cindygordon/2021/04/29/understanding-ai-and-machine-learning-concepts-to-build-your-ai-leadership-brain-trust/?sh=468f19d126a3|
Understanding AI And Machine Learning Concepts To Build Your AI Leadership Brain Trust.]]


Explore how different applications work across functional areas.

[[https://www.techtarget.com/searchenterpriseai/tip/9-top-applications-of-artificial-intelligence-in-business|
9 top applications of artificial intelligence in business]]



Master the skills and vocabulary to work effectively with data scientists.

[[https://www.techtarget.com/searchenterpriseai/feature/3-in-demand-AI-skills-that-boost-data-scientists-development|
3 in-demand AI skills that boost data scientists' development]]

[[https://www.tableau.com/learn/articles/data-science-skills|
10 Essential Skill Sets For Data Scientists]]

[[https://www.techtarget.com/searchenterpriseai/tip/11-data-science-skills-for-machine-learning-and-AI|
11 data science skills for machine learning and AI]]


[[https://www.indeed.com/career-advice/resumes-cover-letters/data-scientist-skills|
Data Scientist Skills: Definitions and Examples]]

[[https://www.tableau.com/en-gb/learn/articles/data-science-skills|
10 skill sets every data scientist should have]]


Bias in Data

[[https://www.nist.gov/news-events/news/2022/03/theres-more-ai-bias-biased-data-nist-report-highlights|
There’s More to AI Bias Than Biased Data, NIST Report Highlights]]

[[https://nvlpubs.nist.gov/nistpubs/SpecialPublications/NIST.SP.1270.pdf|
Towards a Standard for Identifying and Managing Bias in Artificial Intelligence]]

[[https://www.nist.gov/itl/ai-risk-management-framework|
AI RISK MANAGEMENT FRAMEWORK]]





Understand the risks and limits of relying blindly on algorithms.


[[https://hbr.org/2021/05/5-rules-to-manage-ais-unintended-consequences|
5 Rules to Manage AI’s Unintended Consequences]]




Learn how to build AI capabilities for your organisation.


[[https://www.forbes.com/sites/forbesbusinesscouncil/2021/07/22/15-ways-to-leverage-ai-in-customer-service/?sh=844331020bbd|
15 Ways To Leverage AI In Customer Service]]

[[https://hbr.org/2019/07/building-the-ai-powered-organization|
Building the AI-Powered Organization]]




Work on individual or group Action Learning Projects, with feedbacks from Learning Coaches, to solve real business problems within the context of your actual job and organisation.

Participant profile

Transforming Your Business with AI is designed for:

[[https://www.businessnewsdaily.com/9402-artificial-intelligence-business-trends.html|
How Artificial Intelligence Will Transform Businesses]]


Senior executives who want to understand how they can make their organisations AI-ready

Leaders and senior executives seeking the comprehensive perspective they need to lead in a digital world, with a focus on the strategic, organisational and innovation implications of AI and data technologies

Senior managers seeking to build their own capabilities in strategy, leadership and innovation, while developing personalised, actionable plans
    
    
----


Learning objectives

Learn about digital technologies used in digital transformation projects

[[https://hbr.org/2022/01/the-4-pillars-of-successful-digital-transformations|
The 4 Pillars of Successful Digital Transformations]]

[[https://www.accenture.com/us-en/insights/digital-transformation-index|
What is digital transformation?]]


Explore the sources of value of digital transformations for businesses

Consider challenges of privacy and security in digital transformations

[[https://www.nortonrosefulbright.com/en/knowledge/publications/4318add0/digital-transformation-key-technology-cybersecurity-and-privacy-risks|
Digital transformation: Key technology, cybersecurity and privacy risks]]

Assess digital tools, technologies, processes and their uses

Evaluate the use of digital solutions for business problems

Suggest new business solutions that are enabled by advances in digital technologies

Apply principles of digital transformation to real-world business problems

[[https://hbr.org/2021/11/4-principles-to-guide-your-digital-transformation|
4 Principles to Guide Your Digital Transformation]]


Develop a framework for digital transformation within your organisation

Propose digital innovations that build on existing business infrastructure

Recommend appropriate approaches to infrastructure, data governance and change management to support digital transformations


**Technologies Driving Digital Transformation**

The Cloud and Mobile

The Internet of Things

Big Data Analytics

Automation and Artificial Intelligence

FinTech and Blockchain

**Implementing a Digital Transformation**

Sources of Value in a Digital World

A Framework for Implementing a Digital Transformation

Considerations of Privacy and Security


AN INTRODUCTION TO ARTIFICIAL INTELLIGENCE

This introductory module guides you through the evolution of key
AI technologies and how they have developed to transform industry
and business practice. The relationship between AI and collective
intelligence, as well as the implications of this partnership for
business strategy and society are also introduced. As part of
an ongoing project, you’ll begin to consider your own organization
in terms of the application of AI technologies.




MACHINE LEARNING IN BUSINESS

In this module, you’ll explore the core concepts of machine
learning – an AI technology which aims to design, understand,
and use computer programs to learn from experience. Discover
how machine learning can be successfully integrated into business
functions through rich case studies and faculty-led videos that
examine the opportunities that this subfeld of AI affords.
For your ongoing project, you’ll propose ideas for the application
of machine learning in a business context of your choice.



NATURAL LANGUAGE PROCESSING IN BUSINESS

This module is devoted to natural language processing (NLP),
an AI technology developed to intelligently process human
language. Through rich case studies and faculty-led videos, which
explore functions such as machine translation, summarization,
and sentiment analysis, you’ll learn how NLP can be skillfully
deployed in a series of business contexts. For the next part of your
project, the focus will shift to NLP and its strategic implementation
in a business context of your choice.








What is artificial intelligence (AI)? What does it mean for business? And how can your company take advantage of it? 
 

Through an engaging mix of introductions to key technologies, business insights, case examples, and your own business-focused project, your learning journey will bring into sharp focus the reality of central AI technologies today and how they can be harnessed to support your business needs.

Focusing on key AI technologies, such as machine learning, natural language processing, and robotics, the course will help you understand the implications of these new technologies for business strategy, as well as the economic and societal issues they raise. Examine how artificial intelligence will complement and strengthen our workforce rather than just eliminate jobs. Additionally, the program will emphasize how the collective intelligence of people and computers together can solve business problems that not long ago were considered impossible.



[[https://www.wsj.com/articles/what-ai-will-do-to-corporate-hierarchies-11554158120|What AI Will Do to Corporate Hierarchies]]