Executive Mini Master in Applied Artificial Intelligence

Course Dates :

06/01/25

21/02/25

Course ID:

250106001003553LUI

Course Fees GBP:

£31,586.98

Course Category:

Executive Mini Masters

Leadership, Artificial intelligence

Course Certified By:

* LondonUni
For Executive Management Training

* Executive Mini Masters Certificate

Leading to
Executive Masters Certificate

Certification Will Be Issued From :

United Kingdom

Please Note : Your £250.00 Deposit will be deducted from the total invoice Amount.
To commence the registration process for your training course, please follow the link provided and proceed with; Upon successful payment, we will promptly contact you to finalize your enrollment and issue a confirmation of your guaranteed placement.

Course Information

Introduction

The Executive Mini Master in Applied Artificial Intelligence is designed to provide professionals with an in-depth understanding of Artificial Intelligence (AI) and its practical applications. As AI becomes an integral part of business strategies and operations, the demand for skilled professionals capable of leveraging AI technologies is rapidly increasing. This course is tailored to equip participants with the knowledge and skills necessary to navigate the complexities of AI, from foundational principles to advanced applications in business.

Throughout the program, students will gain comprehensive insights into key AI concepts, such as machine learning, data science, and ethical considerations. Additionally, the course focuses on the practical aspects of AI, helping students develop programming proficiency in Python, understand the principles of machine learning, explore the ethical implications of AI technologies, and leverage big data for intelligent decision-making. By combining theoretical learning with hands-on applications, participants will be empowered to apply AI concepts effectively in their careers.

The course is structured to ensure that participants not only understand AI from a technical perspective but also recognize its transformative potential in various sectors. The curriculum emphasizes both the theoretical underpinnings and the real-world applications of AI, making it suitable for those who aim to lead AI-driven innovation in their organizations. Upon completion, graduates will be well-prepared to navigate the fast-evolving landscape of artificial intelligence and apply their knowledge to solve complex business problems.

Course Structure

The Executive Mini Master in Applied Artificial Intelligence consists of six core modules, each designed to address key aspects of AI. The modules are structured to provide a clear progression from basic concepts to more advanced topics, enabling participants to build their knowledge incrementally. The six courses in the program are as follows:

Introduction to Artificial Intelligence
This module provides an overview of AI, its history, key concepts, and future directions. It covers essential topics such as AI techniques, algorithms, and applications across different industries.

Programming for AI with Python
Python is one of the most widely used programming languages in AI development. This course focuses on Python programming essentials and demonstrates how to apply it in the context of AI development, including libraries and frameworks commonly used in AI projects.

Machine Learning Basics
In this module, participants will explore the fundamentals of machine learning, including supervised and unsupervised learning techniques, regression models, classification, and clustering. This module lays the groundwork for more advanced machine learning topics.

AI Ethics and Policy
As AI continues to permeate various sectors, understanding its ethical implications becomes essential. This module covers AI ethics, privacy concerns, fairness, transparency, and policy considerations that professionals must navigate when implementing AI technologies.

Big Data and AI
AI and big data are intricately linked. This module explores how big data fuels AI advancements and how AI algorithms can be used to extract meaningful insights from large data sets. Participants will gain practical knowledge on how to manage and analyze big data to support AI applications.

AI in Business Applications
This course focuses on applying AI in real-world business contexts. Participants will explore case studies, tools, and strategies for using AI in business functions such as marketing, operations, customer service, and decision-making processes.

The course duration spans 30 days, with an additional five days allocated for preparing the final thesis, which should be between 15,000 and 20,000 words. The thesis will allow participants to demonstrate their understanding of the concepts covered in the program and showcase how they can apply AI in a business or organizational context.

Conclusion

The Executive Mini Master in Applied Artificial Intelligence is an advanced, intensive program designed for professionals seeking to deepen their knowledge of AI and its applications. With a combination of theoretical learning and practical training, the course equips participants with the skills needed to implement AI technologies in real-world business scenarios. By the end of the program, participants will be capable of understanding complex AI concepts, programming for AI applications, analyzing big data, addressing ethical challenges, and leveraging AI to drive business success.

By enrolling in this program, participants will gain the tools and expertise necessary to apply AI in their professional roles and contribute meaningfully to the development and implementation of AI solutions within their organizations.

Objectives

The objectives are:

To provide participants with a solid understanding of AI principles and its application in business contexts.
To develop practical skills in AI programming, specifically using Python.
To explore the ethical and policy challenges surrounding AI technologies.
To equip participants with the knowledge to leverage big data in AI applications.
To enable participants to apply machine learning techniques to solve real-world problems.
To foster an understanding of how AI can be utilized to drive innovation and efficiency in business.

Who Should Attend?

This course aims at:

Mid-to-senior level professionals who are looking to expand their knowledge of AI and its applications in business.
Managers, team leaders, and decision-makers who want to integrate AI into their organizational strategies.
IT and data science professionals seeking to enhance their technical skills and transition into AI roles.
Business executives and entrepreneurs interested in understanding the potential of AI to improve business operations and decision-making.
Individuals who aspire to become leaders in the rapidly growing field of artificial intelligence.

Training Method

• Pre-assessment
• Live group instruction
• Use of real-world examples, case studies and exercises
• Interactive participation and discussion
• Power point presentation, LCD and flip chart
• Group activities and tests
• Each participant receives a 7” Tablet containing a copy of the presentation, slides and handouts
• Post-assessment

Program Support

This program is supported by:
* Interactive discussions
* Role-play
* Case studies and highlight the techniques available to the participants.

Daily Agenda

The course agenda will be as follows:
• Technical Session 08.30-10.00 am
• Coffee Break 10.00-10.15 am
• Technical Session 10.15-12.15 noon
• Coffee Break 12.15-12.45 pm
• Technical Session 12.45-02.30 pm
• Course Ends 02.30 pm

Please Note : Your £250.00 Deposit will be deducted from the total invoice Amount.
To commence the registration process for your training course, please follow the link provided and proceed with; Upon successful payment, we will promptly contact you to finalize your enrollment and issue a confirmation of your guaranteed placement.

Part 2 / 7

Programming for AI with Python

Part 3 / 7

Machine Learning Basics

Day 1: Introduction to Machine Learning

Overview of Machine Learning and its Applications
Types of Machine Learning: Supervised, Unsupervised, and Reinforcement Learning
Key Concepts: Features, Labels, and Datasets
Setting Up a Machine Learning Environment

Day 2: Data Preprocessing and Exploration

Importance of Data Preprocessing in Machine Learning
Techniques: Cleaning, Normalization, and Feature Scaling
Data Visualization and Insights Extraction
Splitting Data: Training, Validation, and Testing Sets

Day 3: Core Machine Learning Algorithms

Linear Regression and Logistic Regression
Decision Trees and Random Forests
K-Nearest Neighbors (KNN) and Support Vector Machines (SVM)
Hands-on Session: Building a Simple Predictive Model

Day 4: Model Evaluation and Optimization

Metrics for Evaluating Model Performance (Accuracy, Precision, Recall, F1 Score)
Understanding Overfitting and Underfitting
Hyperparameter Tuning Techniques
Cross-Validation Methods

Day 5: Practical Applications and Ethical Considerations

Real-World Applications of Machine Learning (e.g., Healthcare, Finance, Marketing)
Tools and Libraries: Scikit-learn, TensorFlow, and PyTorch
Ethical Issues in Machine Learning: Bias, Fairness, and Privacy
Final Project: Developing and Evaluating a Basic Machine Learning Model

Part 4 / 7

AI Ethics and Policy

Day 1: Foundations of AI Ethics

Introduction to AI Ethics: Concepts and Importance.
Ethical Frameworks for AI: Deontology, Utilitarianism, and Virtue Ethics.
Key Challenges in AI Ethics: Bias, Fairness, and Transparency.
The Role of Human-Centered Design in Ethical AI.

Day 2: Legal and Regulatory Frameworks

Overview of Global AI Regulations and Standards.
Privacy and Data Protection in AI Systems.
Intellectual Property Rights and AI Innovations.
Developing Organizational AI Policies: Key Considerations.

Day 3: AI Governance and Accountability

Principles of Responsible AI Governance.
Establishing Accountability Mechanisms for AI Use.
Stakeholder Collaboration for Ethical AI Practices.
Monitoring and Auditing AI Systems for Compliance.

Day 4: Societal Impacts and Ethical Challenges

Addressing Bias and Inequality in AI Applications.
The Role of AI in Disinformation and Privacy Breaches.
Ethical Dilemmas in Autonomous Systems and AI Decision-Making.
Building Public Trust in AI Technologies.

Day 5: Policy Development and Practical Application

Creating Ethical AI Policies: A Step-by-Step Guide.
Real-World Case Studies in AI Ethics and Policy.
Best Practices for Policy Implementation and Continuous Improvement.
Future Trends in AI Ethics and Policy Development.

Part 5 / 7

Big Data and AI

Part 6 / 7

AI in Business Applications

Day 1: Introduction to AI in Business

Overview of AI and its evolution in the business landscape.
Key AI technologies: Machine Learning, Natural Language Processing, and Computer Vision.
Identifying AI opportunities within an organization.
Overview of industries transformed by AI: Retail, Healthcare, Finance, and Manufacturing.

Day 2: AI for Data-Driven Decision-Making

Role of predictive analytics in business strategy.
Using AI to analyze customer behavior and trends.
Introduction to AI tools for data visualization and analysis.
Case study: AI-driven decision-making in a real-world scenario.

Day 3: AI in Process Optimization

Applications of AI in supply chain and logistics.
Enhancing operational efficiency through AI-powered automation.
Exploring AI for inventory management and demand forecasting.
Case study: AI in supply chain optimization.

Day 4: AI for Enhanced Customer Experience

Personalization using AI: From marketing to customer support.
AI-driven chatbots and virtual assistants in customer engagement.
Leveraging AI for predictive customer service.
Case study: Successful AI implementation in customer experience.

Day 5: Implementing AI in Your Organization

Developing an AI implementation strategy: Tools, teams, and timelines.
Ethical considerations and challenges in AI adoption.
Building a business case for AI investment.
Workshop: Creating an AI roadmap for your organization.

Executive Mini Masters
Thesis

15,000 - 20,000 Words

Please Note : Your £250.00 Deposit will be deducted from the total invoice Amount.
To commence the registration process for your training course, please follow the link provided and proceed with; Upon successful payment, we will promptly contact you to finalize your enrollment and issue a confirmation of your guaranteed placement.