Associate AI/ML Developer

Course Duration : 2 days

Course Overview

Learn how to code using Python, participants with no prior experience in programming can learn the basics and fundamentals of coding in Python.

Course Outline

Lesson 1: Foundations of Python

• Python Programming and IDEs
• Basics of Python Programming
• Advanced Data Types

Lesson 2: Functions and Control Flow

• Flow Control in Python
• User-Defined Modular Functions

Lesson 3: Working with External Data and Files

• Importing External Data from CSV Files
• Working with Text files

Lesson 4: Python Libraries, Web Scraping, and Dealing with APIs

• Libraries and Functions
• Pandas and Matplotlib Libraries
• APIs for Web Scraping
• Use cases of advanced Python programming in various industries.
• Additional practice exercises

Course Duration : 2 days

Course Overview

Understanding and analyzing data is one of the key skills required in the industry today. This course focuses on the various aspects of data analytics using Python. Participants will be taught to use and be taken through the key libraries for data ingestion and manipulation, exploratory data analysis, model building and data visualization as well as the basic statistics knowledge required to understand the concepts in the latter courses.

Course Outline

Lesson 1: Understanding Data

• Introduction to Python packages for data manipulation
• Importing and exporting data
• Importing datasets and understanding data
• Basics of analyzing the data

Lesson 2: Data Wrangling

• Dealing with data issues and preparation in Python
• Data Formatting and conversions in Python
• Data Wrangling
• Working with Pandas

Lesson 3: Exploratory Data Analysis

• Performing descriptive statistics with Python
• Correlations, Scatter-plots, and charts with Matplotlib in Python
• Understanding data analysis with respect to various business scenarios

Lesson 4: Model Development for Analysis

• Hypothesis Testing
• Linear Regression and Multiple Regression Models
• Model Evaluation Methods
• Model selection

Lesson 5: Data Visualization

• Understanding basic metrics and KPIs
• Visualizations using Python (Seaborn, Folium)

Course Duration : 2 days

Course Overview

This course is designed to equip students with advanced skills in data analysis, statistics, and machine learning using the Python programming language. The course is suitable for individuals who have a basic understanding of Python programming and wish to further their knowledge in the area of advanced analytics and machine learning.

Throughout the course, students will explore various machine learning algorithms, such as decision trees, support vector machines, and others, and learn how to implement them in Python using popular libraries. In addition to theoretical concepts, the course emphasizes on the practical applications of advanced analytics and machine learning in real-world scenarios. Participants will work on various case studies, including data preprocessing, feature engineering, model selection, and evaluation.

Course Outline

Lesson 1: Introduction to Machine Learning with scikit-learn

• Introducing the machine learning flow and concepts
• Functions within scikit-learn
• Introduction to supervised and unsupervised machine learning

Lesson 2: Unsupervised Machine Learning

• Understanding unsupervised ML algorithms
• Introduction to clustering (k-means)
• Implementing clustering with real use cases

Lesson 3: Supervised Machine Learning

• Introduction to various supervised learning algorithms
• Understanding feature engineering and feature sets
• Understanding and implementing
• Implementing the above algorithms with real use cases

Lesson 4: Evaluating machine learning models

• Understanding model selection and evaluation methods
• Optimize machine learning models

Course Duration : 1 day

Course Overview

The global Artificial Intelligence market is expected to reach USD 35,870.0 million by 2025 from its direct revenue sources, growing at a CAGR of 57.2% from 2017 to 2025. Artificial intelligence (AI) refers to intelligent human-like behaviour exhibited by machines. It is a topic with a long history and involves various technologies, tools, and applications. Growth in AI is largely attributed to factors such as growing data, need for improving customer satisfaction.

This 1-day workshop will outline the growth of AI, the latest technologies and trends in AI, the major drivers for growth in AI across various verticals, introduce AI with various tools, both code and no-code and provide a practical experience of how to create simple Machine Learning and Deep Learning Models.

Course Outline

Lesson 1

• Introduction to Artificial Intelligence and its backbone
• Emerging Tools and Trends in Artificial Intelligence
• Discussing the major drivers for the growth of AI in various verticals

Lesson 2

• General and Industrial use cases of AI – Showcasing successful AI deployments and its advantages
• Common and Advanced AI Examples that can be applied to the industry across:
• Convergence of traditional business and artificial intelligence – How it can benefit an organization.

Lesson 3

• Understanding the code and no-code tools in the market for AI and its branches
• Learning how to craft an AI architecture or blueprint for business cases
• Understand the different types of machine learning

Lesson 4

• Hands-on to create simple machine learning prototype models using no-code and code-based tools
• Demonstration of Deep Learning and other popular models
• Creating an AI-driven mindset

Course Duration : 1 day

Course Overview

This 1-day course on ChatGPT for Non-Tech Professionals provides an introduction to the field of generative artificial intelligence for text using ChatGPT, covering key concepts, use cases, and applications in different industries. The course is designed for non-technical professionals who want to learn the basics of ChatGPT and how it can be used in their respective fields. Additionally, the course will have hands-on experience in prompt engineering, where you will learn how to craft prompts to generate specific types of text..

This 1-day workshop will outline the growth of AI, the latest technologies and trends in AI, the major drivers for growth in AI across various verticals, introduce AI with various tools, both code and no-code and provide a practical experience of how to create simple Machine Learning and Deep Learning Models.

Course Outline

Lesson 1: Introduction to Generative AI

• Overview of generative AI and its potential applications
• Real-world applications and use cases for business professionals
• The future of generative AI and its potential impact on industries
• Understanding the different types of generative AI models and how they work

Lesson 2: Introduction to ChatGPT

• What is ChatGPT and its evolution?
• How does ChatGPT work?
• What are the applications of ChatGPT?
• How was ChatGPT trained?

Lesson 3: Content Creation with ChatGPT

• How to generate text with ChatGPT?
• What are some examples of text generated by ChatGPT?
• Text generation, summarization, and personalization
• Using ChatGPT for qualitative insights in data analysis
• How to fine-tune ChatGPT for specific tasks?

Lesson 4: Prompt Engineering for Effective Communication

• Principles of effective prompt design
• Techniques for crafting high-quality prompts
• Examples of prompt engineering for various tasks (e.g., summarization, question-answering, creative writing)
• Tailoring prompts for specific business use cases

Lesson 5: Ethical Considerations when Using ChatGPT

• What are the ethical considerations when using ChatGPT?
• How to avoid bias in ChatGPT?
• How to use ChatGPT responsibly?

Course Duration : 3 days

Course Overview

This 3-day course on Generative AI provides an introduction to the field of generative artificial intelligence, covering key concepts, use cases, and applications in different industries. The course is designed for non-technical professionals who want to learn the basics of generative AI and how it can be used in their respective fields. Participants will learn how to use generative AI tools for content generation, audio synthesis, avatar creation, qualitative data analysis, market research, and prompt engineering, helping them add value to their work across various industries.

Course Outline

Lesson 1: (Recap) Introduction to Generative AI

• Overview of generative AI and its potential applications
• Real-world applications and use cases for business professionals
• The future of generative AI and its potential impact on industries
• Understanding the different types of generative AI models and how they work

Lesson 2: More Practice: Generative Text and Prompt Engineering

• Text generation, summarization, and personalization
• Using ChatGPT for qualitative insights in data analysis
• Tailoring prompts for specific business use cases

Lesson 3: Image Generation with DALL-E, Stable Diffusion and GANs

• Overview of Generative AI for Image Generation
• Understanding how to use Generative AI for Image Generation
• Using Generative AI for image generation in advertising and e-commerce

Lesson 4: Generative Media: Audio and Video

• Overview of Generative AI for audio and video synthesis
• Using Audio and Video Synthesis for Marketing & Advertising
• Generating lifelike avatars using Generative AI Tools

Lesson 5: Leveraging Generative AI for Market Research

• Identifying trends and opportunities with AI-driven analysis
• Enhancing customer segmentation and targeting
• Gathering and analyzing consumer feedback with ChatGPT

Lesson 6: Generative AI using Python

• Generative Text using APIs in Python
• Image Generation, Style Transfer and Neural Art Generation in Python
• Data Augmentation for Computer Vision using Python APIs
• Video and Animation Generation using Generative AI APIs

Lesson 7: Ethical Considerations and Future Implications

• Responsible AI usage for non-technical professionals
• Privacy and data protection concerns
• The evolving landscape of jobs and the future of work
• Job displacement and creation due to AI advancements

Lesson 8: Case Studies

• Overview of recent developments and advancements in generative AI
• Review of relevant case studies of generative AI applications in different industries

Course Duration : 2 days

Course Overview

This course gives learners an overview of working of neural network for predictive analytics and its use in performing advanced machine learning and building artificial intelligent systems. The learners get to work on advanced libraries such as TensorFlow and Keras developed by Google.

Course Outline

Lesson 1: Introduction to AI and Basics of Neural Networks

• Introduction to AI and Deep Learning
  • What is AI and Deep Learning?
  • Role of AI and Deep Learning in businesses today
  • What can you do with deep learning?
• Neural Networks
  • Building Blocks of neural networks
  • Multilayer perceptron for deeper networks
  • Activity 1: Creating a simple NN
  • Activity 2: Creating NN for multiple outputs
  • Activation Functions and Cost Functions
  • Gradient Descent Backpropagation
  • Hyperparameters of an NN architecture
  • Activity 3: Manual neural network classification task

Lesson 2: Introduction to TensorFlow

• Python libraries for Deep Learning
• TensorFlow basics
• TensorFlow graphs, variables and placeholders
• Creating NN with TensorFlow
• Regression using TensorFlow
• Classification using TensorFlow
• Activity 1: Developing a regression model using TensorFlow
• Activity 2: Developing a classification model using TensorFlow
• Saving and restoring models
• Deployment of inference ft. Gradio

Lesson 3: Convolutional Neural Networks

• Understanding CNNs and Architecture of a CNN
• MNIST data – Overview
• Image classification using CNN
• Activity: Developing CNN model to classify MNIST CNN dataset
• Real-world industry examples of CNNs in action

Lesson 4: Recurrent Neural Networks

• Understanding RNNs
• Architecture of an RNN and Implementing RNN using Python
• Introduction to LSTM and GRU
• RNN with TensorFlow API
• Activity: Time series forecasting using RNN
• Real-world industry examples of RNNs in action

Lesson 5: Object Detection and Deep Fakes

• Introduction to AutoEncoders
• Introduction to Generative Adversarial Networks (GAN)
• How deep fakes are created?
• Activity: Object detection using GANs
• Real-world industry examples of GANs in action

Course Duration : 2 days

Course Overview

The AI for Business Innovation program is designed for professionals with existing knowledge of artificial intelligence. This course delves deeper into advanced AI applications, focusing on specific business domains, such as process automation, customer experience enhancement, decision-making, and more. Participants will explore industry-specific AI strategies, ethical considerations, real-world case studies, and the distinctions between traditional AI and generative AI.

Course Outline

Lesson 1: Understanding AI in Business Domains

• Traditional AI vs. Generative AI
  • Distinctions between traditional rule-based AI and generative AI models.
  • Business applications of traditional and generative AI.
  • Group discussion: Identifying when to use each approach in specific business contexts.
• Industry-Specific AI Strategies
  • Formulating AI strategies tailored to specific business domains.
  • AI's role in transforming and innovating various business processes.
  • Case studies: Successful AI-driven transformations in different business domains.

Lesson 2: AI for Process Automation

• Automating Business Processes with AI
  • Understanding AI's role in automating repetitive and rule-based tasks.
  • Industry-specific use cases for process automation.
  • Practical exercise: Identifying automation opportunities in a business context.
• Implementing AI-Driven Process Automation
  • Strategies for successful implementation of AI-based process automation.
  • Group activity: Designing an AI-driven process automation solution for a specific business process.
  • Case study: Real-world examples of AI process automation.

Lesson 3: AI for Customer Experience Enhancement

• AI-Enhanced Customer Interactions
  • Leveraging AI to enhance customer interactions and support.
  • Personalization and customer experience improvements with AI.
  • Hands-on: Designing AI-enhanced customer interactions.
• Measuring and Optimizing Customer Experience with AI
  • Using AI for measuring customer satisfaction and sentiment analysis.
  • Strategies for optimizing customer experience using AI insights.
  • Case studies: Successful AI-driven customer experience enhancement.

Lesson 4: AI for Data-Driven Decision-Making

• AI-Enhanced Decision Support
  • The role of AI in providing data-driven insights for decision-makers.
  • Decision-making support systems powered by AI.
  • Interactive workshop: Using AI for data-driven decision-making.
• AI-Driven Strategic Decision-Making
  • AI's impact on strategic decision-making and business planning.
  • Group discussions: Analyzing AI's influence on business strategy in different domains.
  • Case studies: Successful AI-driven strategic decision-making in business.

Lesson 5: Responsible AI and Ethical Business Innovation

• Advanced AI Ethics in Business
  • Navigating complex ethical issues in business-specific AI applications.
  • Developing and implementing business-specific ethical AI guidelines.
  • Case studies: Ethical considerations in AI-driven business innovation.
• AI for Sustainable and Socially Responsible Business Innovation
  • Leveraging AI to drive sustainability and social responsibility within specific business domains.
  • Business-specific case studies on AI-driven sustainability initiatives.
  • Group activity: Designing AI-driven CSR initiatives for a business domain.

Course Duration : 1 days

Course Overview

This course introduces fundamentals concepts related to artificial intelligence (AI), and the services in Microsoft Azure that can be used to create AI solutions. It is designed to help students build awareness of common AI workloads and the ability to identify Azure services to support them.

Course Outline

Lesson 1: Explore Fundamentals of Artificial Intelligence

• Introduction to Artificial Intelligence
• Artificial Intelligence in Microsoft Azure

Lesson 2: Explore Fundamentals of Machine Learning

• Introduction to Machine Learning
• Azure Machine Learning

Lesson 3: Explore Fundamentals of Computer Vision

• Computer Vision Concepts
• Creating Computer Vision solutions in Azure

Lesson 4: Explore Fundamentals of Natural Language Processing

• Introduction to Natural Language Processing
• Building Natural Language Solutions in Azure

Course Duration : 4 days

Course Overview

This comprehensive 4-day program is designed to equip participants with the skills and knowledge to build AI models using Microsoft Azure. It covers the end-to-end process of AI model development, from data preparation to deployment. Participants will gain hands-on experience with Azure's AI services and tools, enabling them to harness the power of AI for real-world applications.

Course Outline

Lesson 1: (RECAP) Introduction to Azure and AI

• Overview of Microsoft Azure
  • Introduction to Microsoft Azure and its cloud services.
  • Key Azure features and capabilities.
• Basics of Artificial Intelligence
  • Fundamentals of artificial intelligence, machine learning, and deep learning.
  • Real-world applications of AI.

Lesson 2: Setting up Azure Workspace

• Creating an Azure Account
  • Steps to create an Azure account.
  • Accessing the Azure portal and navigating the interface.
• Configuring Azure Machine Learning Workspace
  • Setting up an Azure Machine Learning workspace.
  • Introduction to Azure tools and services for model development.

Lesson 3: Data Collection Techniques

• Methods and Sources of Data Collection
  • Data collection techniques and strategies.
  • Identifying sources for data acquisition.
• Best Practices for Data Acquisition
  • Data quality, privacy, and legal considerations.
  • Hands-on data collection using Azure services.

Lesson 4: Data Storage in Azure

• Azure Data Services for Data Storage
  • Overview of Azure Data Services for data storage.
  • Comparing storage options within Azure.
• Managing and Organizing Data in Azure
  • Best practices for managing and organizing data within Azure.
  • Hands-on exercises for data storage in Azure.

Lesson 5: Building Machine Learning Models

• Introduction to Azure Machine Learning
  • Overview of Azure Machine Learning.
  • Setting up a machine learning experiment within Azure.
• Model Training with Azure AutoML and Azure ML Designer
  • Hands-on model training using Azure AutoML.
  • Model development using Azure ML Designer.

Lesson 6: Model Evaluation and Optimization

• Model Evaluation Techniques
  • Techniques for model evaluation and performance assessment.
  • Common performance metrics for model evaluation.
• Model Fine-tuning and Hyperparameter Optimization
  • Strategies for fine-tuning and optimizing machine learning models.
  • Hands-on exercises for model optimization.

Lesson 7: Model Deployment in Azure

• Deploying Machine Learning Models as Web Services
  • Deploying machine learning models as web services in Azure.
  • Configuring and managing deployed models.
• Implementing Azure Functions and Azure Container Instances
  • Using Azure Functions and Azure Container Instances for model deployment.
  • Hands-on deployment scenarios and best practices.

Lesson 8: Advanced Topics and Applications

• Exploring Azure Cognitive Services
  • Introduction to Azure Cognitive Services for vision, language, and speech.
  • Integrating cognitive services into applications.
• Real-world Industry-specific AI Applications
  • Exploring industry-specific AI solutions and case studies.
  • Group projects: Building AI models for specific industry challenges using Azure.

Course Duration : 1 day

Course Overview

The "Artificial Intelligence Ethics and Governance" program is a one-day intensive course designed to equip professionals and organizations with a solid understanding of the ethical considerations and governance practices required in the field of artificial intelligence. Participants will explore the ethical dilemmas surrounding AI and learn how to implement responsible AI practices that ensure accountability, transparency, and fairness in AI development and deployment.

Course Outline

Lesson 1: Introduction to AI Ethics

• Defining AI ethics and its significance.
• Historical context of AI ethics.
• Ethical considerations in AI use cases.

Lesson 2: Principles of Ethical AI

• Core principles of ethical AI (fairness, transparency, accountability).
• Introduction to AI ethics frameworks and guidelines (e.g., IEEE, AI Ethics Impact Assessment).
• Practical Activity: Group discussion on AI ethics principles.

Lesson 3: AI and Society

• The societal impact of AI technologies.
• Case studies on AI's influence on society.
• Group exercise: Analyzing AI's impact on society.

Lesson 4: AI Governance and Compliance

• Overview of AI governance structures.
• Regulatory requirements for AI.
• Practical Activity: Developing a compliance checklist for AI projects.

Lesson 5: Addressing Bias and Fairness

• Understanding bias in AI and its consequences.
• Mitigating bias through responsible AI practices.
• Practical Activity: Identifying potential bias in AI algorithms.

Lesson 6: Case Studies in AI Ethics and Governance

• Real-world examples of AI successes and failures in ethics and governance.
• Group discussion and analysis of case studies.

Lesson 7: Creating an Ethical AI Action Plan

• Developing an action plan for implementing ethical AI practices within your organization.
• Group activity: Drafting an AI ethics and governance framework.

Course Duration : 8 days

Course Overview

The "Associate AI Developer – Capstone Project" is the culmination of your journey to become a certified Associate AI Developer. This capstone project provides you with an opportunity to demonstrate your AI development skills and knowledge through a real-world application. You will work on a hands-on project that encompasses the entire AI development lifecycle, from data collection and preprocessing to model training, evaluation, and deployment. This project is designed to showcase your expertise and creativity, preparing you for AI development roles in various industries.

Course Outline

Lesson 1: Project Kick-off and Idea Generation

• Understanding the capstone project requirements and guidelines.
• Brainstorming AI project ideas and selecting a suitable topic.
• Creating a project proposal and defining project objectives.

Lesson 2: Data Collection and Preprocessing

• Collecting and sourcing data for the capstone project.
• Data preprocessing, including data cleaning, transformation, and feature engineering.
• Preparing data for model training and evaluation.

Lesson 3: Model Selection and Development

• Choosing the appropriate AI model(s) for the project.
• Implementing the selected model(s) and fine-tuning hyperparameters.
• Developing and training the AI model(s) using industry-standard tools.

Lesson 4: Model Evaluation and Optimization

• Evaluating model performance using relevant metrics.
• Optimizing the model based on evaluation results.
• Addressing issues related to overfitting and underfitting.

Lesson 5: Model Deployment and Integration

• Deploying the trained AI model into a production environment.
• Integrating the AI model with other software components or systems.
• Ensuring scalability and efficiency in deployment.

Lesson 6: Testing, Validation, and Debugging

• Testing the deployed AI system for reliability and accuracy.
• Validation against real-world data and scenarios.
• Debugging and addressing potential issues.

Lesson 7: Documentation and Reporting

• Creating comprehensive documentation for the project.
• Preparing a detailed project report, including the project's methodology and outcomes.
• Presenting findings and insights to peers and instructors.

Lesson 8: Project Presentation and Showcase

• Preparing and delivering a project presentation.
• Showcasing the project to peers, instructors, and industry experts.
• Receiving feedback and making final improvements to the project.

Lesson 9: Project Submission and Evaluation

• Preparing the final project deliverables.
• Submitting the completed capstone project for evaluation.
• Assessment of the project based on predefined criteria.

Course Duration : 2 days

Course Overview

Learn how to foster innovation and growth in your organization by creating customer-centric products and services through the CENTRIC framework. This course is designed for learners in management and supervisory roles.

Course Objectives

• Use the CENTRIC framework to promote customer centric innovations
• Develop assumptions and discover insights from data
• Develop a blueprint to address challenges and opportunities
• Develop concepts and prototypes to meet customers’ requirements
• Test concepts and prototypes by collecting and analysing data metrics

Course Duration : 2 days

Course Overview

When a leader with strong executive presence speaks, people listen, feel inspired, and know that person has command of the room. They speak with conviction, confidence, and certainly. Their powerful executive presence is clear. Strong executive presence is what gives the best leaders their persuasive power, the respect of everyone in their company, and the ability to influence people at all levels—no matter what position they hold.

“Effective Engagement with Stakeholders” series is targeted at management level staff of organisation seeking to engage stakeholders effectively for creating buy-in for support on proposed initiatives. This series provides them with the knowledge and ability to develop an executive presence so that they can influence those around them; generate exclusive insights from analysing data to create compelling solutions; and the ability to engage through storytelling. 

The bundled titles in this series are as follows: (Learner is encouraged to but not compulsory to complete the series based on the proposed sequence as each course builds up the core knowledge and abilities in a logical sequence.)

• Improve Executive Presence
• Generate Insights, Propose Solution powered by Wiley
• Engage through Storytelling

Sense making as a critical skill is important towards the executive presence as the learner will be able to demonstrate their knowledge and ability to convey complex data into insights that matters most in an executive conversation. Conversations driven by data are fact-based and allow the learner to support their brand presence with insights from data obtained from various sources.

Knowledge of various data analytical techniques is important to derive the outcomes which will allow sense-making in the conversation. Recognizing that in negotiations, having data will allow identification of gaps.

This programme has been designed to help business professionals understand that logical insights will contribute to the personal brand and presence and allow informed decisions to be made.

Proposed Course Outline/Learning Outcomes

This programme, jointly developed with content from Wiley & Sons, a major book publisher, will help the learners gain an understanding of how to manage data and information to engage in a meaningful way and make sense of data for insights. Learners will be able to look forward to

• Evaluate viability and reliability of data
• Create linkages in the data relationship through pattern identification
• Analyze data and develop insights
• Share insights through the use of data visualization and storytelling

Course Duration : 2 days

Course Overview

Today’s world is best described by the concept of VUCA (Volatility, Uncertainty, Complexity, Ambiguity). Tumultuous events have continued to reshape our world and have created unprecedented disruption and stress at the personal level as well as for organizations and their workforces.

To thrive in a VUCA world, leaders need to be ready to disrupt and be disrupted. This requires flexibility and the ability to adapt to new circumstances. In the VUCA environment, the perception of what constitutes good leadership is also changing. To thrive in a VUCA world today, leaders need to:

• Counter Volatility with Vision by accepting and embracing that change is a constant and unpredictable feature; lead with clarity of objectives and values, and develop a clear, shared vision of the future.
• Meet Uncertainty with Understanding to develop new ways of thinking and acting in response to VUCA through better analyzing market trends to predict imminent changes and to develop a fast response.
• React to Complexity with Clarity by communicating clearly to help staff understand the team's or organization's direction; and to develop teams and promote greater collaboration.
• Fight Ambiguity with Agility by promoting flexibility, adaptability, and agility; encourage an innovative and continuous improvement culture to have a creative and agile edge in uncertain times.

“Navigate VUCA for Leaders” series is targeted at management-level staff of organizations seeking to develop essential leadership skills to lead their organization through the challenges brought about by major disruptions in today’s VUCA business climate. This series provides them with the knowledge and ability to develop self-awareness and a personal brand; inspire and drive innovations in the organizations and to communicate as an effective leader.

The bundled titles in this series are as follows: (Learner is encouraged to but not compulsory to complete the series based on the proposed sequence as each course builds up the core knowledge and abilities in a logical sequence.)

1. Getting VUCA Ready
2. Leadership Communication and Negotiation in VUCA Times powered by Wiley
3. Fuelling Innovation and Continuous Improvement through Storytelling

One of the key skills for leaders to navigate these VUCA times is to be able to communicate and negotiate effectively. This course is designed to equip leaders with the skillsets to lead communication and negotiation in VUCA times, with a strong focus on the Asia context.

Proposed Course Outline/Learning Outcomes

This course is jointly developed with Wiley & Sons, a major book publisher and it aims to equip one with the knowledge and skills to prepare, lead and manage a negotiation process, and to use a variety of tactics to process information effectively to negotiate in different situations. In particular, this course has a strong focus on negotiation processes in Asia and provides insights into the best practices and pitfalls of negotiation with business counterparts in major Asian economies. Upon completion of this course, learners will find themselves confidently equipped to tackle any negotiation situation.

At the end of the course, learners will be able to:

• Plan and prepare alternatives and outcomes to support negotiation objectives
• Apply communication and conflict resolution techniques to achieve desired negotiation outcomes
• Finalize negotiation and take necessary follow-up actions to close negotiations
• Evaluate negotiation outcomes to identify areas of improvement