Laimoon.com

Artificial Intelligence(AI), Business and Future Work - GBA -Professional London Training Center , Australia, Germany, India, Netherlands, Turkey, UAE, United Kingdom, Dubai, Delhi, Mumbai, Sydney, London, Istanbul, Frankfurt, Munich, The Hague

Wed, 24 Dec 2025 22:02:46 +04

Overview

The Artificial Intelligence (AI), Business, and the Future of Work training course is designed for professionals aiming to remain competitive in a rapidly evolving business environment. By leveraging AI technologies, organisations can improve operational efficiency and develop innovative business models. This course equips participants with up-to-date AI knowledge and practical skills, preparing them to drive digital transformation and lead their organisations confidently into the future of work.

This training programme explores the transformative role of Artificial Intelligence (AI) in modern business and its impact on the future of work. Participants will gain insights into how AI technologies are reshaping operations, decision-making, and organisational models across industries.

The course covers practical applications of AI, strategies for integrating AI into business processes, and the skills required to lead digital transformation initiatives. By the end of the programme, attendees will understand how to harness AI to drive innovation, improve efficiency, and adapt to the evolving workplace landscape.

Key Highlights

Real-world AI implementation strategies
Latest trends in AI and machine learning
AI’s impact on decision-making processes
Ethical considerations in AI deployments
Enhancing customer experience through AI

Cost: 4250 USD

Duration: 5 Days

Artificial Intelligence (AI) for Admins - GBA -Professional London Training Center , Australia, Germany, India, Netherlands, Turkey, UAE, United Kingdom, Dubai, Delhi, Mumbai, Sydney, London, Istanbul, Frankfurt, Munich, The Hague

Wed, 24 Dec 2025 21:43:17 +04

Overview

AI training for administrators focuses on equipping admin professionals with the skills and knowledge to leverage AI technologies in their daily tasks, boosting efficiency, productivity, and overall job performance. This training often covers topics like understanding AI principles, using AI-powered tools, and navigating the ethical implications of AI.

This course introduces administrative professionals to the practical use of Artificial Intelligence (AI) in modern office environments. It focuses on how AI tools can streamline administrative tasks, improve efficiency, and support better decision-making. Participants will explore applications such as automation of routine processes, intelligent scheduling, document management, data handling, and AI-powered communication tools. By the end of the programme, attendees will understand how to confidently use AI to enhance productivity, accuracy, and value in administrative and support roles.

Cost: 4250 USD

Duration: 5 Days

Financial Analysis through Artificial Intelligence (AI) - GBA -Professional London Training Center , Australia, Germany, India, Netherlands, Turkey, UAE, United Kingdom, Dubai, Delhi, Mumbai, Sydney, London, Istanbul, Frankfurt, Munich, The Hague

Tue, 23 Dec 2025 20:15:09 +04

Overview

AI technologies are revolutionizing the operations of financial institutions by providing deeper insights into market trends and customer behavior. By leveraging tools such as machine learning algorithms and deep learning networks, organisations can achieve more accurate financial forecasting and strengthen their capabilities in detecting and preventing fraud.

This programme explores how Artificial Intelligence (AI) is transforming financial analysis, enabling organisations to make faster, more accurate, and data-driven decisions. Participants will gain an understanding of AI techniques and tools used to analyse financial statements, forecast performance, assess risk, and uncover insights that traditional methods may overlook.

Key Areas

Introduction to AI concepts and their applications in finance
Using machine learning and predictive analytics for financial forecasting and trend analysis
Automating financial data processing, anomaly detection, and reporting
Enhancing risk assessment, credit analysis, and investment decision-making through AI models

Objectives

Implement various machine learning techniques, such as regression, classification, and clustering, to solve real-world financial problems.
Understand the fundamentals of AI and its applications in financial analysis
Learn how machine learning, deep learning, and predictive analytics can improve financial forecasting
Apply AI techniques to automate financial data processing and enhance reporting accuracy
Use AI-driven tools to detect anomalies, identify risks, and strengthen fraud prevention
Analyse market trends and consumer behaviour through AI-powered insights

Cost: 4250 USD

Duration: 5 Days

ISO/IEC 42001 Artificial Intelligence Management Systems - GBA -Professional London Training Center , Australia, Germany, India, Netherlands, Turkey, UAE, United Kingdom, Dubai, Delhi, Mumbai, Sydney, London, Istanbul, Frankfurt, Munich, The Hague

Wed, 17 Dec 2025 20:09:24 +04

ISO/IEC 42001 is the world’s first international management system standard for artificial intelligence (AI). It provides a structured framework for establishing, implementing, maintaining, and continually improving an AI management system within an organisation. This course is designed to equip professionals with the practical skills and strategic understanding to apply ISO/IEC 42001 effectively.

Course Objectives

To understand the structure and purpose of ISO/IEC 42001
To gain insight into the development and evolution of AI governance standards
To explore the integration of ISO/IEC 42001 with existing management systems
To learn how to implement and audit an Artificial Intelligence Management System (AIMS)
To identify and mitigate risks associated with AI implementation
To ensure ethical, safe, and compliant use of AI within organisational contexts
To develop strategies that add value and enhance decision-making using ISO/IEC 42001

Cost: 4250 USD

Duration: 5 Days

ISO/IEC42001 Artificial Intelligence Management Systems - GBA -Professional London Training Center , Australia, Germany, India, Netherlands, Turkey, UAE, United Kingdom, Dubai, Delhi, Mumbai, Sydney, London, Istanbul, Frankfurt, Munich, The Hague

Thu, 11 Dec 2025 20:56:36 +04

To understand the structure and purpose of ISO/IEC 42001
To gain insight into the development and evolution of AI governance standards
To explore the integration of ISO/IEC 42001 with existing management systems
To learn how to implement and audit an Artificial Intelligence Management System (AIMS)
To identify and mitigate risks associated with AI implementation
To ensure ethical, safe, and compliant use of AI within organisational contexts
To develop strategies that add value and enhance decision-making using ISO/IEC 42001

Cost: 4250 USD

Duration: 5 Days

Artificial Intelligence Management System - GBA -Professional London Training Center , Australia, Germany, India, Netherlands, Turkey, UAE, United Kingdom, Dubai, Delhi, Mumbai, Sydney, London, Istanbul, Frankfurt, Munich, The Hague

Thu, 11 Dec 2025 20:51:34 +04

Introduction:

The course provides comprehensive guidance on implementing ISO/IEC 42001:2023, the international standard for Artificial Intelligence Management System (AIMS). Participants will gain practical insights into establishing, implementing, and maintaining an AIMS within their organisations to ensure responsible AI development and use

Objectives:

Understand the key principles and requirements of ISO/IEC 42001:2023.
Develop strategies for establishing and implementing an AIMS within their organisations.
Gain practical skills to identify, assess, and manage AI-related risks and opportunities.
Learn how to ensure compliance with legal, regulatory, and ethical standards governing AI technologies.
Explore best practices and case studies for successful AIMS implementation.

Cost: 4250 GBP

Duration: 5 Days

ISO 42001 Lead Auditor - Opportunities Workshop , UAE, United Kingdom, Dubai, Online, London

Tue, 22 Apr 2025 16:58:29 +04

TRECCERT ISO/IEC 42001 Lead Auditor is an expert-level course developed to equip trainees with a practical understanding of the Artificial Intelligence Management System (AIMS) audit approach based on the requirements of the ISO/IEC 42001 and ISO 19011 standards.

The training course provides a comprehensive overview of the AIMS audit following the ISO 19011 guidelines for MS auditing and related concepts, processes, methods and techniques.

The ISO/IEC 42001 Lead Auditor training course is developed for professionals responsible for the audit and maintenance of the AIMS, for example: Information Security Specialists, Cybersecurity Specialists, Compliance Officers, External and/or Internal Auditors, Security Analysts.

Learning Outcomes:

Know and understand artificial intelligence management fundamental concepts, standards, best practices
and laws/regulations.
Know and understand ISO/IEC 42001 requirements, and describe their function and operation.
Know and understand ISO/IEC 42001 – Annex A controls, and describe their purposes and auditing methods.
Know, understand and be able to participate in AIMS auditing projects and related activities.
Know, understand and be able to audit AIMS projects and related activities.

COURSE OUTLINE

1. Introduction to AIMS

Introduction to AI
AI Management System Overview
AI Governance Frameworks and Regulations

2. ISO/IEC 42001 Requirements

Context of the Organization
Leadership
Planning
Support
Operation
Performance Evaluation
Improvement

3. AI Controls

Policies Related to AI
Internal Organization
Resources for AI systems
Assessing Impacts of AI Systems
AI System Life Cycle
Data for AI Systems
Information for Interested Parties of AI Systems
Use of AI Systems
Third Party Relationships

4. Introduction to Audit

MS Audit and Audit Types
Audit Principles
Auditor Competence and Evaluation
Code of Ethics and Conflict of Interest

5. Managing an Audit Programme

Creating an Audit Programme
Establishing Audit Programme
Audit Programme Implementation
Audit Programme Monitoring and Reviewing
Conducting the AIMS Audit
Initiation of Audit
Audit Planning
Audit Execution
Audit Report
Follow-up Audit

Cost: 2000 USD

Duration: 5 Days

ISO42001 Lead Implementer - Opportunities Workshop , UAE, United Kingdom, Dubai, Online, London

Tue, 22 Apr 2025 16:55:08 +04

TRECCERT AI Management System ISO/IEC 42001 Lead Implementer is an expert-level course developed to equip trainees with a practical understanding of the AIMS implementation approach based on the requirements of the ISO/IEC 42001 standard.

The training course provides a comprehensive overview of the AIMS implementation based on the Plan-Do-Check-Act model and related concepts, processes, methods, and techniques.

Learning Objectives:

Know and understand artificial intelligence management fundamental concepts, standards, best practices and laws/ regulations.
Know and understand ISO/IEC 42001 requirements, and describe their function and operation.
Know, understand and be able to define a framework for implementing a AI Management System (AIMS) within an organisation.
Know, understand and be able to interpret ISO/IEC 42001 controls and implement the AIMS based on the defined framework.
Know, understand and be able to support the implementation team to continually improve the implemented management system.

COURSE OUTLINE

1. Introduction to AIMS

Introduction to AI
AI Management System Overview
AI Governance Frameworks and Best Practices

2. ISO/IEC 42001 Requirements

Context of the Organization
Leadership
Planning
Support
Operation
Performance Evaluation
Improvement

3. AI Controls

Policies Related to AI
Internal Organisation
Resources for AI Systems
Assessing Impacts of AI systems
AI System Life Cycle
Data for AI Systems
Information for Interested Parties of AI Systems
Use of AI Systems
Third Party Relationships

4. AIMS Initiation

Develop the Project Charter
Ensure Management Commitment
Identify the Interested Parties
Conduct a Gap Analysis
Prepare the PDCA Cycle

5. Establishment Phase

Establish the Context of the Organization
Define the AIMS Scope
Establish the Objectives, Processes, and Procedures
Establish the AIMS Policy
Define the Risk Assessment Approach
Create the AIMS Implementation Plan
Management Authorization to Implement and
Operate the AIMS

6. Implementation and Operation Phase

AI Risk Management
Implement the AI Management Policies and Procedures
Manage AIMS Operations
Awareness and Training
Resource Management and Documented Information

7. Monitor and Review Phase

Monitor the AIMS
Conduct Internal Audits
Review the AIMS

8. Maintenance and Improvement Phase

Implement the Identified Improvements
Corrective and Preventive Actions
Communicate the Actions and Improvements
Ensure Continual Improvement of AIMS

Cost: 2000 USD

Duration: 5 Days

Python for Data Analysis - Opportunities Workshop , UAE, United Kingdom, Dubai, Online, London

Tue, 22 Apr 2025 14:20:53 +04

In this course, you’ll learn to code with Python.

Python is a general-purpose programming language used for a variety of purposes, including web, software, and game development, artificial intelligence, machine learning, and data analysis.

The course begins with fundamental programming concepts, such as functions and statements. We then cover several of the Python libraries most relevant for data management and manipulation (, NumPy, Pandas, Seaborn, and Matplotlib).

You’ll also learn about extracting, transforming, and loading data (ETL) techniques and operations, as well as what is known as “data wrangling”.

Module 1: Introduction to Programming with Python
Getting Started with Python; Performing Operations with Complex Data Types; Working with “If” Statements, Loops, and Comprehensions; Defining, Configuring, and Invoking Functions; Leveraging Functions with Lambdas, Generators, Closures, and
Decorators

Module 2: Python for Data Science
Introduction to NumPy for Multi-dimensional Data; Advanced Operations with NumPy Arrays; Manipulating and Analysing Data in Pandas Dataframes; Data Wrangling with Pandas; Data
Visualisation Using Seaborn

Module 3: Operations with petl
Petl: Introduction; Basic Data Transformations; Advanced Extractions and Transformations

Module 4: Data Science Statistics
Using Python to Compute and Visualise Statistics; Applied Inferential Statistics

Cost: 1500 USD

Duration: 3 Days

ISO42001 Practitioner - Opportunities Workshop , UAE, United Kingdom, Dubai, Online, London

Tue, 22 Apr 2025 14:11:12 +04

Validate your knowledge and expertise in artificial intelligence governance with the ISO/IEC 42001 Practitioner Certification.

Designed for professionals who wish to demonstrate their understanding of Artificial Intelligence Management Systems (AIMS), this certification attests to your proficiency in key concepts, principles, and compliance frameworks in alignment with ISO/IEC 42001 standards.

Establish yourself as a knowledgeable professional capable of contributing to the responsible management and ethical oversight of AI technologies, paving the way for trusted and effective AI implementation in your organisation.

Cost: 550 USD

Duration: 1 Day

Generative AI for Business Users - Opportunities Workshop , UAE, United Kingdom, Dubai, Online, London

Tue, 22 Apr 2025 14:08:03 +04

A major milestone in business automation has been reached—generative AI. Despite its recency, it has already started having a significant impact on our lives. But, the rapid pace at which generative AI is growing can be overwhelming. And, there are so many facets to this field that it can be difficult to know how to use it effectively to improve the business.

This course is designed to demystify generative AI for business professionals, as well as to trace its power to actionable, real-world business goals. It will give you the essential knowledge of generative AI you'll need to elevate the organisation in these exciting course is primarily designed for business leaders, consultants, product and project managers, and other decision makers who are interested in unlocking new business opportunities and augmenting existing business processes using generative AI. It's also a great starting point for any business professionals who want to investigate generative AI solutions for their own individual tasks and workflows.

Cost: 550 USD

Duration: 1 Day

Certified Data Science Practitioner - Opportunities Workshop , UAE, United Kingdom, Dubai, Online, London

Tue, 22 Apr 2025 14:02:02 +04

The Certified Data Science Practitioner™ (CDSP) is an industry-validated certification which helps professionals differentiate themselves from other job candidates by demonstrating their ability to put data science concepts into practice. Data can reveal insights and inform—by guiding decisions and influencing day-to-day operations. This calls for a robust workforce of professionals who can analyse, understand, manipulate, and present data within an effective and repeatable process framework.

This certification validates candidates’ ability to use data science principles to address business issues, use multiple techniques to prepare and analyse data, evaluate datasets to extract valuable insights, and design a machine learning approach. In addition, it will validate skills to design, finalize, present, implement, and monitor a model to address issues regardless of business sector.

Cost: 1999 USD

Duration: 5 Days

Certified Ethical Emerging Technologist (CEET) - Opportunities Workshop , Online, Dubai, United Arab Emirates, London, United Kingdom,Bahrain,Malaysia,Oman,Qatar,Saudi Arabia,Singapore

Tue, 25 Mar 2025 18:14:04 +04

Course Overview:

This three-day intensive programme provides delegates with the knowledge, skills, and abilities required to:

Apply foundational ethical principles
Follow industry-standard frameworks
Identify and mitigate risks
Navigate ethical organizational governance
Devise and maintain ethical, trusted, and inclusive data-driven technologies

Key Topics Covered:

The Certified Ethical Emerging Technologist™ (CEET) course and exam cover the following five core areas:

Fundamental Concepts for Data-Driven Technology Ethics
Ethical Frameworks
Risk Identification and Mitigation
Communication
Organizational Policy and Governance

Certification & Exam:

This course fully equips delegates to successfully sit for the CertNexus Certified Ethical Emerging Technologist (CEET) exam and earn the accompanying certification.

Cost: 2999 USD

Duration: 3 Days

Certified Artificial Intelligence (AI) Practitioner - Opportunities Workshop , Online, Dubai, United Arab Emirates, London, United Kingdom,Bahrain,Malaysia,Oman,Qatar,Saudi Arabia,Singapore

Tue, 25 Mar 2025 17:44:43 +04

Course Overview:

This five-day intensive programme equips participants with the knowledge, skills, and abilities required to achieve the globally recognized Certified Artificial Intelligence Practitioner certification from CertNexus. The course covers four core domains essential for mastering AI and machine learning applications in business.

Key Topics Covered:

The Certified Artificial Intelligence Practitioner™ (CAIP) course and exam cover the following four key areas:

1. Understanding the Artificial Intelligence Problem

Describe how artificial intelligence and machine learning are used to solve business (including commercial, government, public interest, and research) problems
Analyze the use cases of ML algorithms to rank them by their success probability
Research Learning Systems [Identify business case for image recognition; NLP; Speech recognition; Predictive & recommendation systems; Discovery & diagnostic systems; Robotics and autonomous systems]
Analyze machine learning system use cases
Communicate with stakeholders
Identify potential ethical concerns

2. Engineering Features for Machine Learning

Recognize relative impact of data quality and size to algorithms
Explain data collection/transformation process in ML workflow (transformations include standardization; normalization; log, square-root, and logit transformations)
Work with textual, numerical, audio, or video data formats
Transform numerical and categorical data
Address business risks, ethical concerns, and related concepts in data exploration/ feature engineering

3. Training and Tuning ML Systems and Models

Design machine and deep learning models [Differentiate types of ML algorithms; differentiate types of DL algorithms; design for pattern recognition in predictive models]
Optimize the algorithm (, structure, run time, tuning hyperparameters)
Train, validate, and test data subsets
Evaluate the model
Address business risks, ethical concerns, and related concepts in training and tuning

4. Operationalizing ML Models

Deploy a model
Secure a pipeline (includes maintenance)
Maintain the model postproduction
Address business risks, ethical concerns, and related concepts in operationalizing the model

Certification & Exam:

This course fully prepares participants to successfully sit for the CertNexus Certified Artificial Intelligence Practitioner exam and earn the accompanying certification.

Classes are delivered as live online, instructor-led tuition.

Cost: 1999 USD

Duration: 5 Days

Data Science & Machine Learning - IOMH - Institute of Mental Health , Online,United Kingdom

Mon, 14 Oct 2024 16:09:45 +04

Data science is transforming industries, but many feel overwhelmed by the sheer complexity of algorithms and machine learning models. Without a clear path, even the most motivated learners can struggle to get started. Imagine confidently handling machine learning models, data preparation, and algorithm evaluations using Data Science & Machine Learning techniques. This course bridges the gap between confusion and confidence, providing a structured, step-by-step introduction to Data Science & Machine Learning. Through foundational Python libraries and advanced evaluation methods, you’ll develop the skills to understand and work with complex data sets. With this Data Science & Machine Learning course, you’ll gain the expertise to tackle data science challenges, positioning yourself for success in a rapidly growing field.

Learning Outcomes

Understand the fundamentals of Data Science & Machine Learning.
Learn how to prepare, clean, and manipulate datasets.
Master key Python libraries such as NumPy, Pandas, and Matplotlib.
Develop skills in algorithm evaluation and selection.
Gain expertise in feature selection and data preparation.
Explore ensemble techniques for performance improvement.

Course Curriculum

Module 01: Course Overview & Table of Contents
Module 02: Introduction to Machine Learning - Part 1 - Concepts, Definitions, and Types
Module 03: Introduction to Machine Learning - Part 2 - Classifications and Applications
Module 04: System and Environment Preparation - Part 1
Module 05: System and Environment Preparation - Part 2
Module 06: Learn Basics of Python - Assignment
Module 07: Learn Basics of Python - Assignment
Module 08: Learn Basics of Python - Functions
Module 09: Learn Basics of Python - Data Structures
Module 10: Learn Basics of NumPy - NumPy Array
Module 11: Learn Basics of NumPy - NumPy Data
Module 12: Learn Basics of NumPy - NumPy Arithmetic
Module 13: Learn Basics of Matplotlib
Module 14: Learn Basics of Pandas - Part 1
Module 15: Learn Basics of Pandas - Part 2
Module 16: Understanding the CSV Data File
Module 17: Load and Read CSV Data File Using Python Standard Library
Module 18: Load and Read CSV Data File Using NumPy
Module 19: Load and Read CSV Data File Using Pandas
Module 20: Dataset Summary - Peek, Dimensions, and Data Types
Module 21: Dataset Summary - Class Distribution and Data Summary
Module 22: Dataset Summary - Explaining Correlation
Module 23: Dataset Summary - Explaining Skewness - Gaussian and Normal Curve
Module 24: Dataset Visualization - Using Histograms
Module 25: Dataset Visualization - Using Density Plots
Module 26: Dataset Visualization - Box and Whisker Plots
Module 27: Multivariate Dataset Visualization - Correlation Plots
Module 28: Multivariate Dataset Visualization - Scatter Plots
Module 29: Data Preparation (Pre-Processing) - Introduction
Module 30: Data Preparation - Re-scaling Data - Part 1
Module 31: Data Preparation - Re-scaling Data - Part 2
Module 32: Data Preparation - Standardizing Data - Part 1
Module 33: Data Preparation - Standardizing Data - Part 2
Module 34: Data Preparation - Normalizing Data
Module 35: Data Preparation - Binarizing Data
Module 36: Feature Selection - Introduction
Module 37: Feature Selection - Uni-variate Part 1 - Chi-Squared Test
Module 38: Feature Selection - Uni-variate Part 2 - Chi-Squared Test
Module 39: Feature Selection - Recursive Feature Elimination

……...And more.

Cost: 9.99 GBP

Duration: Upto 10 Hours

Python from Scratch - IOMH - Institute of Mental Health , Online,United Kingdom

Mon, 14 Oct 2024 14:53:51 +04

Are you ready to learn Python from the ground up? This course is designed for anyone who wants to understand the basics of Python. You don’t need any prior experience. Our clear and simple lessons will guide you through everything you need to know.

Throughout the course, you'll learn important skills like working with variables, lists, and strings. You'll also discover how to use loops and functions to make your code more efficient. Each section builds on the last, ensuring you feel confident as you progress.

By the end of this course, you will have a strong foundation in Python. You will be able to write your own programs and solve problems easily. Join us and start your journey in programming with Python today!

Learning Outcomes

Understand fundamental concepts and features of Python.
Master essential data types and operations for effective coding.
Learn to control program flow with conditional statements and loops.
Explore object-oriented programming principles and applications in Python.
Gain proficiency in utilizing modules and packages to enhance functionality.
Develop a solid foundation to solve programming challenges confidently.

Course Curriculum

Module 1: Python Course Introduction
Module 2: Python Course Curriculum Overview
Module 3: Python Whats New
Module 4: Command Line Basics in Python
Module 5: Python Installation
Module 6: Pycharm-CE IDE Installation
Module 7: Setting up Environment
Module 8: Running Python Code
Module 9: Git and GitHub Overview
Module 10: Python Data Types
Module 11: Python Arithmetic Operators Numbers
Module 12: Variable Assignments
Module 13: Strings Introduction
Module 14: Indexing and Slicing with Strings
Module 15: String Properties and Methods
Module 16: Formatting Strings in Python
Module 17: Lists in Python
Module 18: Dictionaries in Python
Module 19: Tuples in Python
Module 20: Comparison Operators in Python
Module 21: Logical Operators in Python
Module 22: If, Elif, and Else Statements in Python
Module 23: For Loops in Python
Module 24: While Loops in Python
Module 25: Functions in Python
Module 26: Methods in Python
Module 27: List Methods in Python
Module 28: Nested Loop in Python
Module 29: 2D Lists using Nested Loop in Python
Module 30: Introduction to Object Oriented Programming in Python
Module 31: Attributes and Class Keyword
Module 32: Class Object, Attributes, and Methods in Python
Module 33: Inheritance
Module 34: Encapsulation in Python
Module 35: Polymorphism OOP in Python
Module 36: Pypi and Pip
Module 37: Modules in Python
Module 38: Packages in Python

………...And more.

Cost: 9.99 GBP

Duration: Upto 9 Hours

Deep Learning for Business Applications - AiinoX , Netherlands, UAE, United Kingdom, Dubai, London, Amsterdam,United Kingdom

Tue, 13 Aug 2024 14:21:38 +04

Overview

This course explores deep learning techniques and their practical applications in business contexts. Participants will gain hands-on experience in building and deploying deep learning models for tasks such as image recognition, natural language processing, and recommendation systems.

Objective

Understand the architecture and principles of deep neural networks.
Implement deep learning models using libraries such as TensorFlow and PyTorch.
Apply deep learning techniques to solve business challenges in areas such as image classification and sentiment analysis.
Fine-tune pre-trained models for specific business domains and use cases.
Explore advanced topics in deep learning, including generative adversarial networks (GANs) and reinforcement learning.
Develop strategies for deploying and scaling deep learning solutions in production environments.

Who Should Attend

Data scientists, software engineers, AI researchers, and professionals interested in leveraging deep learning to drive business innovation and competitive advantage.

Outlines

DAY 1: Introduction to Deep Learningg

Fundamentals of Neural Networks
Introduction to TensorFlow and Keras
Hands-on: Building Your First Neural Network

DAY 2: Convolutional Neural Networks (CNNs)

Understanding CNN Architecture
Image Classification with CNNs
Case Studies: CNN Applications in Business

DAY 3: Recurrent Neural Networks (RNNs)

Introduction to RNNs and LSTM Networks
Natural Language Processing (NLP) with RNNs
Hands-on: Sentiment Analysis with RNNs

DAY 4: Advanced Deep Learning Techniques

Introduction to GANs and Reinforcement Learning
Case Studies: Advanced Deep Learning Applications
Deploying Deep Learning Models in Production Environments.

Cost: 5995 USD

Duration: 4 Days

AI Strategy and Implementation - AiinoX , Netherlands, UAE, United Kingdom, Dubai, London, Amsterdam,United Kingdom

Tue, 13 Aug 2024 14:21:38 +04

Overview

This course provides a strategic framework for planning and implementing AI initiatives within organisations. Participants will learn how to develop AI roadmaps, assess organisational readiness, manage AI projects, and navigate challenges associated with AI adoption.

Objective

Understand the strategic importance of AI for business competitiveness and growth.
Develop an AI strategy aligned with organisational goals, priorities, and capabilities.
Assess organisational readiness for AI adoption, including data infrastructure, talent, and culture.
Plan and execute AI projects using best practices and methodologies, managing risks and uncertainties effectively.
Monitor and measure the impact of AI initiatives on business performance, iterating and refining strategies as needed.
Foster a culture of innovation and continuous learning, driving organisational transformation and agility.

Who Should Attend

C-suite executives, strategy consultants, project managers, and decision-makers responsible for driving AI transformation initiatives within their organisations.

Outlines

DAY 1: Strategic Importance of AI

AI Landscape: Trends and Opportunities
Developing an AI Strategy Aligned with Business Goals
Case Studies: Successful AI Transformation Stories

DAY 2: Assessing Organisational Readiness

Evaluating Data Infrastructure and Talent
Identifying AI Use Cases and Priorities
Overcoming Barriers to AI Adoption

DAY 3: Planning and Executing AI Projects

Developing AI Roadmaps and Implementation Plans
Project Management Best Practices for AI Initiatives
Building Cross-functional Teams for AI Projects

DAY 4: Monitoring and Optimising AI Initiatives

Measuring AI Impact: KPIs and Metrics
Continuous Improvement and Iteration
Closing Remarks: Building a Culture of AI Innovation.

Cost: 5995 USD

Duration: 4 Days

Unlocking the Future: A Beginner's Guide to Artificial Intelligence - AiinoX , Netherlands, UAE, United Kingdom, Dubai, London, Amsterdam,United Kingdom

Tue, 13 Aug 2024 14:21:38 +04

Overview

This comprehensive training course is designed to demystify the world of Artificial Intelligence (AI) and provide you with a solid foundation for understanding and engaging with this transformative technology. Whether you are a curious novice or looking to expand your professional skill set, this course will equip you with the knowledge and insights needed to navigate the AI landscape.

Objective

Identify key AI applications in various industries.
Understand the core principles and limitations of machine learning.
Define rational agents and their decision-making processes.
Grasp the basics and applications of fuzzy logic.
Gain an Overview of robotics and AI integration.
Comprehend key concepts and challenges in NLP.
Understand the fundamentals and applications of neural networks.

Who Should Attend

Professionals Seeking New Skills.
Leaders & Managers who want to understand how AI can be leveraged to optimise their operations and gain a competitive edge.

Outlines

DAY 1: Applications of AI

AI in healthcare, finance, transportation, entertainment
Real-world use cases and societal impact
Strengths and Limitations of Machine Learning
Core principles of machine learning
Limitations: data dependency, interpretability

DAY 2: Concepts of Rationality

Rational agents in AI
Defining rationality in AI
Implications for decision-making
Fuzzy Logic
Approximate reasoning with fuzzy logic
Applications in uncertainty handling

DAY 3: Robotics

Introduction to robotics
AI integration in robots
Robot perception, motion planning, navigation

DAY 4: Natural Language Processing (NLP)

Enabling machines to understand human language
Key concepts: text analysis, language generation
Challenges in conversational agents

DAY 5: Neural Networks

Neural networks as AIs backbone
Brain-inspired models
Uses: image recognition, speech processing, gaming.

Cost: 5995 USD

Duration: 5 Days

Strategic Alignment of Artificial Intelligence (A.I.) - AiinoX , Netherlands, UAE, United Kingdom, Dubai, London, Amsterdam,United Kingdom

Tue, 13 Aug 2024 14:21:38 +04

Overview

This Strategic Alignment of Artificial Intelligence () course is crafted to equip professionals with the tools and insights to effectively align AI strategies with business goals, driving innovation and sustainable growth in their organisations. Over five days, the course covers the spectrum from understanding AI's role in enhancing operational efficiency to fostering an AI-driven culture within organisations.

This course is ideal for professionals seeking to harness AI technologies to enhance business efficiencies, innovate new processes, and lead transformational change within their organisations. It is also beneficial for those looking to upskill in AI applications and strategic management to advance into higher leadership roles.

Participants will learn to assess AI's impact, develop AI skills across their teams, and align AI initiatives with long-term business Objectives, ensuring that their investments in AI translate into measurable business outcomes.

The course employs various teaching methods, including expert-led presentations, interactive discussions using real-world case studies, and peer learning activities to ensure a comprehensive and practical learning experience.

Objective

Understand AI's capabilities and limitations within a business context.
Develop strategies to leverage AI for competitive advantage.
Identify the necessary skills and capabilities needed to support AI initiatives.
Foster an AI-ready culture within organisations to facilitate seamless adoption.
Measure and optimise the impact of AI through appropriate metrics and KPIs.
Navigate ethical considerations and sustain responsible AI practices in business.

Who Should Attend

Business leaders, strategic planners, operations managers, HR professionals involved in training and development, and IT managers overseeing technological integrations with AI.
Attendees should have a general understanding of AI technologies, experience in managing business operations or strategic projects, and a basic proficiency in handling data-driven decision-making processes.

Outlines

DAY 1: Understanding AI in Business Contexts

Introduction to AI: Overview of AI technologies and their fundamental concepts
AI in Operations: How AI can optimise operational efficiency, from manufacturing to services
Interactive Session: Identifying AI opportunities in participants operations

DAY 2: AI for Strategic Advantage

AI and Business Strategy: Integrating AI into business strategy for competitive advantage
Case Studies: Real-world examples of strategic AI integration
Workshop: Developing AI-aligned strategies for hypothetical businesses

DAY 3: Building AI Skills and Capabilities

Skills Assessment: Identifying required AI skills and capabilities within a business
Training Programs: Designing and implementing training for AI proficiency across roles
Group Activity: Mapping out a skills development plan for an AI-driven business

DAY 4: Cultivating an AI-Driven Culture

Cultural Change: Strategies for fostering an AI-ready culture in the workplace
Leadership in AI: Role of top management in driving AI initiatives
Discussion: Barriers to AI adoption and how to overcome them

DAY 5: Measuring Success and Sustaining Growth

AI and ROI: Metrics and KPIs to measure AI impact
Sustainability and Ethics: Ensuring responsible AI use in business practices
Panel Discussion: Future of AI in business with industry experts

Cost: 5995 USD

Duration: 5 Days

Artificial Intelligence (AI) Technical Implementation Programme - AiinoX , Netherlands, UAE, United Kingdom, Dubai, London, Amsterdam,United Kingdom

Tue, 13 Aug 2024 14:21:38 +04

Overview

Welcome to the immersive AI Technical Implementation Programme! Over four intensive days, this programme unlocks the practical application of Artificial Intelligence within industrial settings. Explore foundational AI principles, advanced machine learning techniques, and hands-on deployment of cutting-edge models using popular frameworks like TensorFlow and PyTorch. Dive into real-world scenarios, leveraging pre-built services from industry-leading vendors to craft AI solutions. Discover the latest trends shaping the field and gain expertise in implementing AI to drive innovation and tackle challenges across diverse industries. Join us to master AI's practical implementations and propel your skills into the future.

Objective

Understanding AI Technologies and Frameworks: Gain a comprehensive understanding of AI, Machine Learning (ML), and Deep Learning (DL) concepts, along with proficiency in using popular AI frameworks like TensorFlow, PyTorch, and Scikit-Learn.
Application of Advanced AI Techniques: Acquire practical knowledge of advanced ML algorithms such as Neural Networks, Transfer Learning, and Natural Language Processing (NLP) to solve real-world problems across various industries.
Deployment and Optimization Strategies: Learn techniques for deploying AI models in production environments and optimizing these models through strategies like hyperparameter tuning and model pruning for enhanced performance.
Utilization of AI Services from Vendors: Explore and apply pre-built AI services from leading vendors (AWS, Azure, GCP) for practical implementations in domains like Computer Vision, Speech Recognition, and Recommendation Systems.
Ethical Considerations in AI: Understand the ethical considerations associated with AI development and deployment, including addressing bias in algorithms, ensuring fairness, and leveraging open-source AI tools/platforms.
Application of AI in Industry Contexts: Apply AI technologies specifically within industrial contexts, identifying challenges and opportunities across sectors like manufacturing, supply chain, logistics, and predictive maintenance.
Future Trends and Continuous Learning: Explore emerging trends in AI, such as Explainable AI, AutoML, and AI in Edge Computing, while fostering an understanding of the impact of AI on industries and society. Additionally, access resources for continuous learning and staying updated in the evolving field of AI.

Who Should Attend

This programme on Artificial Intelligence is suitable for a technical audience that includes IT, Project, and Business professionals and those who want to gain a deeper technical understanding of AI, including its subfields, applications, and ethical considerations.

Outlines

DAY 1: Introduction to AI Technical Implementations

Overview of AI, Machine Learning (ML), and Deep Learning (DL)
Types of AI: Narrow vs. General AI
Practical applications and industries benefiting from AI
Overview of popular AI frameworks: TensorFlow, PyTorch, Scikit-Learn
Hands-on: Setting up the environment and running basic ML/DL models using TensorFlow or PyTorch
Case Study: Image Classification using TensorFlow or PyTorch

DAY 2: Advanced AI Techniques and Algorithms

Deep Dive into Neural Networks: CNNs, RNNs, and their applications
Transfer Learning and its significance in various industries
AI vendors and their specialised offerings (, IBM Watson, Google Cloud AI)
Fundamentals of NLP and its applications (Sentiment Analysis, Named Entity Recognition)
Hands-on: Text Generation or Sentiment Analysis using NLP tools (NLTK, spaCy)
Case Study: Implementing NLP for Customer Sentiment Analysis using AWS Comprehend or Google Cloud Natural Language

DAY 3: Deployment, Optimization, and AI Services

Techniques for deploying models in production environments
Model optimisation approaches (Hyperparameter tuning, Model pruning)
AI service providers and their deployment platforms (AWS, Azure, GCP)
Hands-on: Utilizing pre-built AI services from vendors like AWS Rekognition, Azure Cognitive Services, or Google Cloud Vision API
Case Study: Implementing a Recommendation System using AI services from AWS or Azure

DAY 4: Ethical AI and Future Trends

Ethical considerations in AI development and deployment
Addressing bias in AI algorithms and ensuring fairness
Open-source AI tools and platforms (TensorFlow Extended, Hugging Face Transformers)
Emerging trends in AI (Explainable AI, AutoML, AI in Edge Computing)Emerging trends in AI (Explainable AI, AutoML, AI in Edge Computing)
Discussion on the impact of AI on various industries and society
Course Conclusion, Q&A, and Resources for Continuous Learning.

Cost: 6400 USD

Duration: 4 Days

Certified Artificial Intelligence (AI) Practitioner - AiinoX , Netherlands, UAE, United Kingdom, Dubai, London, Amsterdam,United Kingdom

Tue, 13 Aug 2024 14:21:38 +04

Overview

Artificial intelligence (AI) and machine learning (ML) have become essential parts of the toolset for many organizations. When used effectively, these tools provide actionable insights that drive critical decisions and enable organizations to create exciting, new, and innovative products and services. This course shows you how to apply various approaches and algorithms to solve business problems through AI and ML, all while following a methodical workflow for developing data-driven solutions.

Objective

Solve business problems with AI and ML
Prepare and process data for ML
Train, evaluate, and tune ML models
Build and deploy various ML models (regression, classification, clustering, neural networks)
Operate and maintain ML models in production

Who Should Attend

This course is suitable for anyone looking to expand their knowledge of machine learning algorithms and how they can help create intelligent decision-making products that bring value to the business

Outlines

Day 1: Solving Business Problems Using AI and ML including Preparing Data, Training, Evaluating, and Tuning a Machine Learning Model

Identify AI and ML Solutions for Business Problems
Formulate a Machine Learning Problem
Select Approaches to Machine Learning
Collect DataTransform DataEngineer Features
Work with Unstructured Data
Train a Machine Learning Model
Evaluate and Tune a Machine Learning Model

Day 2: Building Linear Regression Models including, Building Forecasting Models

Build Regression Models Using Linear Algebra
Build Regularized Linear Regression Models
Build Iterative Linear Regression Models
Build Univariate Time Series Models
Build Multivariate Time Series Models

Day 3: Building Classification Models Using Logistic Regression and k-Nearest Neighbor, including Building Clustering Models

Train Binary Classification Models Using Logistic Regression
Train Binary Classification Models Using k-Nearest Neighbor
Train Multi-Class Classification Models
Evaluate Classification ModelsTune Classification Models
Build k-Means Clustering Models
Build Hierarchical Clustering Models

Day 4: Building Decision Trees and Random Forests including Building Support-Vector Machines

Build Decision Tree ModelsBuild Random Forest Models
Build SVM Models for ClassificationBuild SVM Models for Regression

Day 5: Building Artificial Neural Networks including Operationalizing Machine Learning Models, Maintaining Machine Learning Operations

Build Multi-Layer Perceptrons (MLP)
Build Convolutional Neural Networks (CNN)
Build Recurrent Neural Networks (RNN)
Deploy Machine Learning Models
Automate the Machine Learning Process with MLOps
Integrate Models into Machine Learning Systems
Secure Machine Learning Pipelines
Maintain Models in Production

Cost: 4900 USD

Duration: 5 Days

Artificial Intelligence Essentials - London Training For Excellence , Bahrain, Kuwait, Oman, Qatar, Saudi Arabia, UAE, Dubai, Abu Dhabi, Riyadh, Jeddah, Al Kuwait, Muscat, Manama, Kuwait City, Doha,Netherlands,United Arab Emirates,United Kingdom

Tue, 21 Mar 2023 15:57:37 +04

Overview
Artificial Intelligence (AI) is a branch of computer science that focuses on creating intelligent machines that can perform tasks that normally require human intelligence such as:

Perception
Reasoning
Learning
Decision making
Natural language processing.

AI can be applied in a wide range of fields including healthcare finance education transportation and entertainment. It has become an essential part of the technology industry. Research associated with artificial intelligence is highly technical and specialised.

Objective

History of Artificial Intelligence
What is Artificial Intelligence?
Application of Artificial Intelligence
Artificial Intelligence Intelligent Systems
Problems in Artificial Intelligence
Approaches used in Artificial Intelligence
Tools used in Artificial Intelligence
Different types of Artificial Intelligence Technology
Agents and Environments in Artificial Intelligence
Artificial Intelligence Expert Systems
Artificial Intelligence Robotics
What is strong and weak Artificial Intelligence?

Who Should Attend
The course on Artificial Intelligence outlined above is suitable for anyone who wants to gain a basic understanding of AI, including its subfields, applications, and ethical considerations. The course is especially useful for the following groups of individuals:

Business executives and managers who want to understand the potential of AI and how it can be leveraged to gain a competitive advantage in their industry.
IT professionals who want to learn the fundamentals of AI and how it can be integrated into their projects.
Data scientists and analysts who want to expand their knowledge and skills in AI and its subfields.
Anyone who is interested in learning about AI and its impact on society. The course is designed for individuals with little or no prior knowledge of AI, but it can also serve as a refresher for those who have some familiarity with the topic.

Course Outlines
Day 1:Introduction to AI

What is AI?
Brief history of AI
Different types of AI and their applications
Key concepts and terminology

Day 2: Machine Learning

Introduction to machine learning
Supervised unsupervised and reinforcement learning.
Classification and regression
Overfitting and underfitting
Model evaluation and selection

Day 3:Neural Networks and Deep Learning

Introduction to neural networks
Structure and working of a neural network.
Activation functions
Convolutional neural networks (CNN) and their applications
Recurrent neural networks (RNN) and their applications

Day 4:Natural Language Processing

Introduction to NLP
Tokenization stemming and lemmatisation.
Part-of-speech tagging
Named entity recognition.
Sentiment analysis

Day 5:Future of AI and Ethics

Emerging trends in AI
AI and its impact on society
Ethical considerations in AI development and use
Bias and fairness in AI
Explainable AI

Cost: 4900 USD

Duration: 5 Days