• 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

Cost: 4250 USD

Duration: 5 Days

• Define and apply principles of threat and vulnerability management
• Assess and prioritise threats using vulnerability assessment tools
• Design and implement secure authentication and authorisation mechanisms
• Explain key components of effective cyber security governance
• Differentiate between firewall technologies and broader network security controls
• Strengthen asset, configuration, change, and patch management processes
• Manage enterprise identity, access, and information security
• Identify and evaluate application security controls

Cost: 4250 USD

Duration: 5 Days

• Implement standards-based, proven methodologies for assessing and managing organisation's information infrastructure risks.
• Select and implement security controls that ensure compliance with applicable laws, regulations, policies, and directives.
• Extend security protection to ICS (Industrial Control Systems) and the cloud.
• Understand the fundamentals of cyber security risk, including threats, vulnerabilities, and impacts on business operations
• Identify and assess cyber risks using structured risk assessment frameworks and methodologies
• Apply risk treatment strategies to reduce, transfer, avoid, or accept cyber risks
• Align cyber security risk management with enterprise risk management and governance structures
• Understand relevant standards and frameworks such as ISO 27001, NIST, and other leading practices
• Enhance organisational resilience through effective monitoring, reporting, and continuous improvement of cyber risk controls
•  

Cost: 4250 USD

Duration: 5 Days

• 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

• 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

• The Process of Auditing Information Systems
• Governance & Management of IT
• Information Systems Acquisition, Development, and Implementation
• Information Systems Operations, Maintenance, and Support
• Protection of Information Assets

Cost: 4250 USD

Duration: 1 Day

• Understand the fundamental principles and concepts of cybersecurity
• Identify common cyber threats, vulnerabilities, and attack vectors
• Apply best practices and security controls to protect digital assets and networks
• Conduct risk assessments and implement mitigation strategies for cyber threats
• Develop effective incident response and recovery plans
• Ensure compliance with relevant regulations, standards, and organizational policies
• Promote a culture of cyber security awareness within the organization
• Integrate cyber security practices into day-to-day operations to safeguard information and maintain business continuity

Cost: 4250 USD

Duration: 5 Days

• Understand the architecture and vulnerabilities of industrial control systems.
• Identify and assess cybersecurity threats specific to process control environments.
• Apply security measures to protect operational technology networks and systems.
• Develop incident response and risk mitigation strategies.
• Promote a culture of cybersecurity awareness within industrial operations.
• Perform security countermeasures to protect process control networks and assets.
• Utilize diagnostics and troubleshooting tools to monitor and respond to cybersecurity incidents.
• Establish security governance practices, including management of change and compliance measures.

Cost: 4250 USD

Duration: 5 Days

• 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

• The need for Information Security
• Information Security Management System (ISMS) concepts & definitions
• Policies, standards & procedures: Delivering a balanced ISMS, security procedures
• Information risk management
• Corporate governance
• Organisational responsibilities

Cost: 4250 USD

Duration: 5 Days

• Document capture, scanning, and indexing
• Secure storage and retrieval of information
• Version control and audit trails
• Workflow automation and process management
• Collaboration tools for teams across departments
• Compliance with regulatory standards and data governance policies
• Integration with other enterprise applications for seamless operations

Cost: 4250 USD

Duration: 5 Days

• 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

• 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 USD

Duration: 5 Days

Cost: 4250 USD

Duration: 5 Days

Cost: 4250 USD

Duration: 5 Days

• Learn how to integrate DevOps practices with Agile methodologies.
• Understand the principles of continuous integration (CI), continuous delivery (CD), and release on demand.
• Gain the ability to scale Agile practices across the enterprise and deliver business value effectively.
• Develop a culture of shared responsibility and continuous improvement within teams.
• The SAFe® DevOps course is essential for professionals looking to enhance collaboration and agility in organizations

• Master DevOps Principles: Gain in-depth knowledge of DevOps practices and how they fit into Agile.
• Real-World Application: Engage in hands-on activities, workshops, and simulations for practical learning.
• Global Recognition: Earn the SAFe® DevOps certification, a credential respected worldwide.
• Leadership Opportunities: Equip yourself with skills for leadership roles in the Agile and DevOps space.
• Increase Business Value: Learn how to optimize workflows, reduce time-to-market, and deliver systems reliably at scale.
• Flexible Learning: Access online learning options and pay in easy installments for your convenience.

• Introducing DevOps
• Mapping the Continuous Delivery Pipeline
• Gaining Alignment with Continuous Exploration

• Building Quality with Continuous Integration
• Reducing Time-to-Market with Continuous Deployment
• Delivering Business Value with Release on Demand
• Taking Action to Deliver Business Value with DevOps

• Experienced Trainers: Learn from certified trainers with real-world expertise in Agile and DevOps.
• Practical Approach: Focus on real-world applications through team-based workshops and simulations.
• Global Recognition: The SAFe® DevOps certification you earn is globally recognized and will enhance your career prospects.
• Tailored Learning: Flexible online learning options to fit your schedule and learning preferences.
• Continuous Support: Full support throughout your learning journey to ensure your success.

Cost: 5000 AED

Duration: 16 Hours

• Understand the Fundamentals of Data Management and Governance
• Effectively Integrate Data Architecture with Modern Technologies
• Implement Data Management Strategies
• Master Key Data Management Skills
• Navigate Advanced Data Management Topics

• Data management: relation with DAMA-DMBOK and the role of data governance
• Introduction of knowledge areas
• Data architecture: business, functional and technical architecture and the relation with enterprise and application architecture
• Data architecture in relation with big data, data lakes, Data Warehouses (DWH), data virtualization and analytics/data science
• Positioning, coherence and added value of the business and IT
• Examples, use cases

• The new role of data: ‘data as an asset’
• Action plans for implementation based on context diagrams
• DMBOK as framework: backgrounds
• Introduction and in-depth discussion of knowledge areas metadata, reference & master data, Data Warehousing (DWH) & Business Intelligence (BI)

• Introduction and in-depth discussion of data modelling and design, data quality, data integration, storage, security

• Introduction and in-depth discussion of documents and content management, big data and data science, data privacy and ethics
• Introduction and application of the DAMA Data Management Maturity Model
• CDMP exam preparation

Cost: 4760 USD

Duration: 4 Days

• 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.

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

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

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

• 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

• 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.

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

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

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

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

Cost: 5995 USD

Duration: 4 Days

• 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.

• 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

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

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

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

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

Cost: 5995 USD

Duration: 5 Days

• 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.

• 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

• 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

• 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

• 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

• 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

• 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.

• 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

• 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

• 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

• 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

• Master industrial cybersecurity management
• Implement security policies per national and international laws
• Protect networks using IEC 62443 guidelines
• Apply various cybersecurity standards
• Comply with the new European NIS2 Directive

• Trends in ICT and Industrial Control Systems (ICS)
• Relevant standards and frameworks (IEC 62443, NIST SP 800-82)
• Industrial Control Systems (ICS): Overview
• Examples and topologies
• Embedding risk management in your organisation
• Special points of attention regarding Industrial Control Systems (ICS)

• How to develop a business case
• Required expertise and skills
• Defining a scope
• Policy, standards and procedures
• Awareness

• Logical network segmentation
• Firewalls
• TCIP/IP protocol suite
• Defense-in-Depth architecture
• RESTful APIs and JSON (JavaScript Object Notation)
• Specific SCADA and ICS protocols
• Remote Support Access (RSA), Incident response

• Integration of risk management and Industrial Control Systems (ICS)
• Awareness
• Audits
• Configuration management
• Business Continuity Management (BCM)
• Protection of storage media
• Physical security, Privacy controls.

Cost: 4700 USD

Duration: 4 Days

• Explain key cybersecurity concepts and components
• Identify components of cybersecurity network architecture
• Describe risk management processes
• Identify security tools, threats, and vulnerabilities
• Describe different classes of attacks
• Explain emerging technologies
• Analyze threats and risks
• Assess cybersecurity incidents

• Cyber security objectives
• Cyber security roles
• Differences between information security and cyber security
• Confidentiality, integrity, and availability
• Authentication and non-repudiation

• Lifecycle management landscape
• Security architecture processes
• Security architecture tools
• Intermediate lifecycle management concepts
• Basics of risk management
• Operational threat environments
• Classes of attacks

• Incident categories
• Incident response
• Incident recovery
• New and emerging IT and IS technologies
• Mobile security issues, risks, and vulnerabilities
• Cloud concepts around data and collaboration

• During the exam preparation day you will learn the critical skills to perform many of the technical tasks vital to your success in the field of IT.
• In the morning you will practice hands-on with performance-based questions.
• In the afternoon you will practice with knowledge-based questions.

Cost: 4730 USD

Duration: 4 Days

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: 5995 USD

Duration: 5 Days

• After completing this courseyou will be able to:
• Understand Sharepoint and it's operative nature
• Manage to collaborate data and successfully analyse file hosting
• Understand business intelligence in modern world
• Perform Power BI desktop data transformation and to describe Power BI desktop modelling.
• Understand to create a Power BI desktopvisualisation and Power BI embedding
• Create BI embedded solutions to implement the Power BI service.
• Describe the nature of connect to Excel data.
• Connect directly to data stores.
• Understand Mobile networking and connection with BI

• History of Sharepoint and Microsoft.
• Various editions of SharePoint.
• SharePoint Server and its affects.
• Current Standards of Sharepoint.
• Application of Sharepoint.
• Collaboration and file hosting.

• Power BI
• The Power BI service
• Power BI mobile apps
• Labs

• Using Excel as a Power BI data source
• Using databases as a Power BI data source
• The Power BI service
• Labs

Module 4. Shaping and Combining Data

• Power BI desktop queries
• Shaping data
• Combining data
• Labs

Module 5. Data

• Consistent analysis across your organisation
• Interactive data and BI reports
• Cloud data with BI
• The development API
• Power BI Mobile
• Power BI Mobile Apps

Cost: 4900 USD

Duration: 5 Days

• Comprehend the detrimental impact that a lack of IT confidence and competence has on productivity and well-being at an individualteam and organisational level - and use the benefits of addressing this issue for continued motivation
• Understand psychological and physiological stress responses to IThow these impact both your confidence and competence and how to overcome your blockages
• Learn how to use The Polyvagal Theorythe Voice Dialogue model and other methods to tackle your IT barriers and become an IT-confident and competent professional
• Apply your learning and experience to your IT tasks and activities in the workplace and keep developing your confidence and competence in line with the emergence of new IT advancements
• This is not an IT skills coursebut includes IT practice sessions to allow you to face your particular discomfort and blockages and build your confidence in real timewith support and encouragement.

• Introduction: why so many people find using technology challenging and the impact this can have on productivity and well-being at an individual team and organisational level
• Understanding common psychological barriers to using IT and how this impacts confidence and competence
• Reflection on your blockages and the resulting impact
• How labels like 'Technophobe' and 'Luddite' can get in the way of overcoming blockages around using technology and how to avoid this trap
• Using the many benefits of building your IT confidence to help motivate you
• Inspiring case study examples

• Introduction to the Polyvagal Theory for understanding your stress response to working with technology
• Why learning how to consciously regulate your autonomic nervous system is essential for IT competence and how to become more regulated
• Exercise: mapping your own autonomic nervous system for a deeper understanding of your own personal stress responses
• Understanding the fight-flight response to IT: what happens physiologically when anxiety starts to take over and how to bring calmness and competence back on board
• Understanding the freeze response: what actually happens in your brain and body when you start to 'zone out' or your mind goes blank and how to bring your thinking brain back on board
• Exercise: setting manageable IT goals in partnership with your autonomic nervous system to prevent overwhelm build your confidence and increase your capabilities

• Introduction to the Voice Dialogue model for understanding our system of parts or selves and our subconscious and using this approach to overcome IT blockages and confidence and capability issues
• Understanding the parts of you that sabotage and work against you and how to overcome them
• Using Voice Dialogue in the workplace to access your confidence and develop your IT and related professional capabilities
• Voice Dialogue Practice Session: working with your own unique system of parts and subconscious for personal transformation and IT competence
• How to bring psychological reframing and physiological orientation together to tackle your IT blockages and become more competent
• Introduction to IT Practice Sessions

• IT Practice Session: facing your discomfort with support and encouragement
• IT Situational role-play
• Using visualisation and powerful exercises for 'stepping into' and fully embodying a more confident and competent IT version of yourself in the workplace

• IT Practice Session
• Leading by example and supporting others with IT confidence
• Identifying appropriate further IT training and supporting your ongoing development
• Action plan for bringing your learning personal insights and inner changes to the workplace and applying them practically to your IT tasks and activities

Cost: 4900 USD

Duration: 5 Days

• Understand the difficulties of aligning IT to business priorities
• Develop a practical framework for IT-to-business alignment Identify prioritised business needs and the role of IT's sponsors and stakeholders in aligning with IT
• Develop a realistic model of IT governance and align IT strategy with business strategy
• Build successful business relationship plans and work with sponsorsstakeholdersand critical users
• Communicate technology to non-technical audiences and handle difficult situations
• Deliver operational excellence and effective project management
• Develop strategies for effective IT team leadership and coaching techniques

• IT professionals and managers seeking to develop a deeper understanding of IT business management
• Business owners and entrepreneurs interested in aligning IT to business priorities and improving operational excellence
• Project managers responsible for managing IT projects
• Anyone interested in learning more about the benefits and risks associated with IT business management.

• Overview of IT business management and the difficulties of aligning IT to business priorities
• Best practices for aligning IT to business and a practical framework for IT to business alignment
• Identifying prioritised business needs and the role of IT's sponsors and stakeholders in aligning with IT
• A practical model of IT governance and aligning IT strategy with business strategy
• Developing an alignment strategy?

• Building successful business relationship plans including the business relationship management sales cycle and assessing political power and leverage
• Working with sponsors stakeholders and key users and techniques for identifying the real needs of customers
• Communication styles and the skills of the actor for presenting technology to non-technical audiences
• Handling difficult situations including difficult staff and structuring group presentations?

• Delivering operational excellence including the Continual Service Improvement Model and using continual improvement frameworks to gain business advantage
• Techniques of root cause analysis to resolve problems and examples and guidelines of success
• Project management excellence including starting well making project reporting do the work and effective management of project steering

• Developing strategies for excellence in managing IT teams including choosing good people and getting the best from your team
• The importance of team dynamics and its effect on team performance and setting goals and vision to enhance performance
• Effective coaching techniques and developing staff in real-time and playing to strengths
• Round table reflections and action.

• Review and summary of IT business management concepts and best practices
• Practical exercises to apply IT business management concepts to real-world problems
• Future trends in IT business management and their implications for business

Cost: 4900 USD

Duration: 5 Days

• Domain 1 - Cyber security concepts
• Domain 2 - Cyber security architecture principles
• Domain 3 - Security of networks systems applications and data
• Domain 4 - Incident response
• Domain 5 - Security implications and adoption of evolving technology

• understand basic cyber security concepts and definitions
• understand basic security architecture principles
• understand security of networkssystemsapplications and data
• define types of incidents and identify elements of an incident response plan
• explain the core Information Assurance (IA) principles
• identify the key components of cyber security network architecture
• apply cyber security architecture principles
• describe risk management processes and practices
• identify security tools and hardening techniques
• distinguish system and application security threats and vulnerabilities
• describe different classes of attacks
• define types of incidents including categoriesresponses and timelines for response
• describe new and emerging IT and Information Security (IS) technologies
• analyze threats and risks within the context of the cyber security architecture
• appraise cyber security incidents to apply appropriate response
• evaluate decision making outcomes of cyber security solutions
• access additional external responses to supplement knowledge of cyber security

• Cyber security concepts
• Cyber security principles used to manage risks related to the use processing storage and transmission of information or data
• Security management
• Risk management processes including steps and methods for assessing risk
• Threat actors
• Cyber security roles
• Common Adversary Tactics Techniques and Procedures (TTPs)  Relevant laws policies procedures and governance requirements 
• Cyber security controls

• Cyber security architecture principles
• Network design processes to include understanding of security objectives operational objectives and trade-offs
• Security system design methods tools and techniques
• Network access Identity and Access Management (IAM)
• IT security principles and methods
• Network security architecture concepts including technology protocols components and principles
• Malware analysis concepts and methodology
• Intrusion detection methodologies and techniques for detecting host and network-based intrusions via intrusion detection technologies
• Defense in depth principles and network security architecture
• Encryption algorithms
• Cryptography
• Encryption methodologies
• The process of traffic flows across the network ( transmission and encapsulation)
• Network protocols dynamic host configuration protocol and directory services

• Security of networks systems applications and data
• Vulnerability assessment tools and their capabilities
• Basic system administration network and operating system hardening techniques
• Risk associated with virtualizations
• Penetration testing
• Network systems management principles modules methods and tools
• Remote access technology
• Unix command line
• System and application security threats and vulnerabilities
• System life cycle management principles including software security and usability
• Local specialized system requirements for safety performance and reliability
• System and application security threats and vulnerabilities u Social dynamics of computer attackers in a global context u Secure configuration management techniques
• Capabilities and applications of network equipment including hubs routers switches bridges servers transmission media an related hardware
• Communication methods principles and concepts that support the network infrastructure
• Common networking protocols and services and how they interact to provide network communications
• Different types of network communication
• Virutalisation technologies and virtual machine development and maintenance
• Application security
• Risk threat assessment

• Incident response
• Incident categories and response
• Business continuity/disaster recovery
• Incident response and handling methodologies
• Security event correlation tools
• Processes for seizing and preserving digital evidence
• Types of digital forensics data
• Basic concepts and practices of processing digital evidence
• Anti-forensics tactics techniques and procedures (TTPS)
• Common forensic tool configuration and support applications
• Network traffic analysis methods
• Which system files contain relevant information and where to find those system files

• Security implications and adoption of evolving technology
• Emerging technology and associated security issues risks and vulnerabilities
• Risk associated with mobile computing
• Cloud concepts around data and collaboration
• Risk of moving applications and infrastructure to the cloud
• Risk associated with outsourcing
• Supply chain risk management processes and practices

Cost: 4900 USD

Duration: 5 Days

• Understand essential strategic tools, including STEEP, PEST, SWOT, Porter's Five Forces, and more.
• Explore customer-centric models like the Kano Model and Quality Function Deployment.
• Develop skills to analyse and respond to customer requirements effectively.
• Learn data analysis techniquesincluding data distributioncorrelationsand regression analysis.
• Apply strategic and customer tools to improve business decision-making.
• Identify key success factorsindustry signalsand opportunities for your organisation.
• Enhance your strategic thinking and problem-solving abilities.

• Managers, supervisors and data analytic personnel who will use this in their day-to-day role.
• Anyone who wishes to have a greater understanding of analytics and analysis.

• Introduction to Strategic Thinking
• Overview of STEEP and PEST Models
• Practical exercises on conducting external environmental scans
• Dive into Porter's Five Forces Model
• Application of SWOT Analysis

• Introduction to Ansoff Matrix
• Practical exercises to evaluate market strategies
• SPACE Matrix explained

• Introduction to Customer-Centric Thinking
• Overview of the Kano Model
• Application of customer segmentation for strategic focus
• Assigning values to customers and ranking based on expectations
• Quality Function Deployment model for customer requirements

• Introduction to the Buyer Utility Map
• Exercises in generating new customer satisfaction strategies
• Conducting customer surveys and data collection techniques

• Introduction to Data Analysis with Statistics
• Recognising data analysis approaches
• Basics of quality control and reducing errors
• Overview of Quantitative vs. Qualitative data and levels of measurement
• Designing ways of expressing data distributions visually
• Identifying necessary measures for describing data distributions
• Representing correlations in data and introduction to regression analysis

Cost: 4900 USD

Duration: 5 Days

• Prepare data for PivotTable reporting and create PivotTables from various data sources
• Analyse Data Using PivotTables
• Work with Pivot Charts

• Preparing Data and Creating PivotTables
• Prepare Data.
• Create a PivotTable from a Local Data Source.
• Create a PivotTable from Multiple Local Data Sources.
• Create a PivotTable from an External Data Source.
• Analysing Data Using PivotTables
• Summarize PivotTable Data
• Organize PivotTable Data
• Filter PivotTable Data
• Format a PivotTable
• Refresh and Change PivotTable Data
• Working with Pivot Charts
• Create a PivotChart
• Manipulate PivotChart Data
• Format a PivotChart

Cost: 4900 USD

Duration: 5 Days

• Improved Data Analytics Skills
• Career Advancement
• Better Decision Making
• Competitive Advantage
• Increased Earning Potential
• Overalltaking a course on big data analysis can provide individuals with valuable skills and knowledge that are in high demand across many industriesleading to improved career prospectsbetter decision-makingand a competitive advantage for their organisations.

1. 1. Data analysts and data scientists who want to learn new techniques and tools for analysing large data sets.
2. 2. Business analysts who want to use data-driven insights to make better decisions and improve business performance.
3. 3. IT professionals are responsible for managing and maintaining large databases and data warehouses.
4. 4. Developers who want to learn how to build scalable and efficient data processing systems.
5. 5. Managers and executives who want to better understand big data technologies and how they can be used to drive business innovation and growth. Overall, anyone who wants to learn how to work with big data and extract valuable insights from it can benefit from attending a course on big data analysis.

• Introduction to Big Data & Big Data Analysis
• Understanding Big Data & its Importance
• Characteristics of Big Data
• Data Analysis and its role in big data

• Big Data Technology
• Introduction to Big Data Technologies
• Hadoop and its ecosystem
• Spark and its ecosystem

• Data Storage and Retrieval
• Data Storage and Retrieval technologies
• NoSQL Databases (MongoDB Cassandra)
• Distributed File Systems (HDFS Amazon S3)

• Data Processing and Analysis
• Data Processing analysis technologies
• Data Modelling and preparation
• Data Analysis Techniques (statistical analysis machine learning)

• Data Visualisation and Business Intelligence
• Data Visualisation and its importance
• Visualisation tools and techniques
• Introduction to business intelligence and analytics

Cost: 4900 USD

Duration: 5 Days

• Profound insight into the statistical underpinnings of artificial intelligence.
• Comprehensive understanding of machine learning principles and their practical applications.
• Mastering deep learning modelsactivation functionsweights initialisation strategiesand regularisation techniques.
• In-depth comprehension of Natural language processing NLP.
• Hands-on experience through engagement in a practical project.
• Exploration of diverse AI applications within the realm of businesses.
• Gain expertise in discerning and leveraging business opportunitiesadeptly crafting compelling use cases.

• Data Analysts
• Data Scientists
• Business Analysts & Researchers
• Machine Learning Professionals
• Anyone with an Interest in Deep Learning

• Understand data and exploratory data analysis (EDA).
• Measures of central tendency dispersion and correlation.
• Introduction to Machine Learning.
• Introduction to supervised learning algorithms.
• Introduction to unsupervised learning.
• Introduction to reinforcement learning.
• Complete ML workflow.

• Introduction to Deep Learning
• Neural Networks (NN).
• Feedforward neural networks.
• Activation functions.
• Backpropagation.
• Regularisation.
• Dropout.
• Optimisation algorithms.
• Weight initialisation.
• Batch normalisation.
• Hyper parameter tuning.

• Introduction to Natural Language Processing (NLP).
• Understand NLP tasks.
• Understand NLP cycle.
• Bag of Words (BoW).
• Word Embeddings.
• Word2Vec.
• Contextualised word embeddings.
• BERT.

• Deep Learning project.
• Problem identification.
• Value identification.
• Project setup.
• Project implementation.
• Evaluation.

• Discriminative AI applications.
• Generative AI applications.
• Building a business use case.
• Course wrap-up.

Cost: 4900 USD

Duration: 5 Days

• Gain a comprehensive understanding of data management principlesprocessesand technologies.
• Develop data collectioncleaningand integration strategies from various sources.
• Master data modelling techniques for efficient data organisation and storage.
• Learn to apply data quality control measures to ensure data accuracy and consistency.
• Explore critical concepts of data governance and data security best practices.
• Understand data analytics techniques and how they leverage managed data for insights.
• Develop skills for data visualisation to communicate data stories effectively.
• Stay ahead by exploring emerging data management and analytics trends.

• Data Analysts and Business Analysts: Learn advanced data preparation and analysis techniques.
• Data Scientists: Gain a deeper understanding of data management principles for robust data analysis projects.
• Database Administrators (DBAs): Develop robust data modelling and data security practices.
• IT Professionals: Understand how data management integrates with overall IT infrastructure.
• Business Managers and Executives: Gain insights into leveraging data for strategic decision-making.
• Marketing Professionals: Learn to use data for targeted marketing campaigns and customer insights.

• Introduction: The importance of data management in the digital age and its impact on business success.
• Data Lifecycle Management (DLM): Understanding the different stages of data from creation to archiving.
• Data Quality Fundamentals: Defining data quality standards and implementing data cleaning techniques.
• Data Governance Framework: Establishing a framework for data ownership access control and data security.

• Data Collection Techniques: Exploring various methods for data collection from internal & external sources.
• Data Integration: Mastering strategies to combine data from diverse formats and sources into a unified system.
• Data Warehousing & Business Intelligence (BI): Understanding the role of data warehouses and BI tools for data analysis.

• Data Modelling Fundamentals: Conceptual logical and physical data models for efficient data organisation.
• Entity-Relationship Diagrams (ERDs): Visual representations of data relationships between entities and attributes.
• Data Normalisation Techniques: Minimising data redundancy and corruption for optimal data integrity.

• Data Security Threats: Understanding common data security risks and implementing data protection measures.
• Access Control Mechanisms: Developing user roles and permissions for secure data access and management.
• Data Encryption & Anonymisation: Learning techniques to secure sensitive data and protect privacy.
• Data Backup & Disaster Recovery: Creating robust strategies for data backup recovery and business continuity.

• Introduction to Data Analytics: Exploring different data analytics techniques to extract valuable insights from data.
• Introduction to Data Visualisation Tools: Learning to create compelling data visualisations for effective communication.
• Storytelling with Data: Developing skills to communicate complex data insights to stakeholders clearly and concisely.
• The Future of Data Management: Emerging trends in data management including Big Data Cloud Computing and Artificial Intelligence (AI).

Cost: 4900 USD

Duration: 5 Days

Cost: 4900 USD

Duration: 5 Days

Cost: 4900 USD

Duration: 5 Days

Cost: 4900 USD

Duration: 5 Days

Cost: 4900 USD

Duration: 5 Days

Cost: 4900 USD

Duration: 5 Days

Cost: 4900 USD

Duration: 5 Days

• Perception
• Reasoning
• Learning
• Decision making
• Natural language processing.

• 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?

• 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.

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

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

• 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

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

• 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

•  Handle, manage and control risk along with providing the estimate of the project.
•  Prototyping techniques in detail.
•  Estimate the duration, effort and the cost of IT project.
•  Design a project without losing the balance of cost, quality and time.
•  Automated project management tools can help you in planning and controlling your IT project.
•  Importance of quality assurance and how to deliver the best quality project.
•  Assign responsibility to the team, motivate and manage them. Study the importance of client satisfaction.

Cost: 4500 USD

Duration: Upto 5 Days

• Understand the difficulties of aligning IT to business priorities
• Develop a practical framework for IT-to-business alignment Identify prioritised business needs and the role of IT's sponsors and stakeholders in aligning with IT
• Develop a realistic model of IT governance and align IT strategy with business strategy
• Build successful business relationship plans and work with sponsors, stakeholders, and critical users
• Communicate technology to non-technical audiences and handle difficult situations
• Deliver operational excellence and effective project management
• Develop strategies for effective IT team leadership and coaching techniques

Cost: 1750 USD

Duration: 5 Days