Artificial Intelligence & Machine Learning - United Kingdom

Artificial Intelligence & Machine Learning

The Artificial Intelligence and Machine Learning Courses explores the fundamentals of AI, machine learning algorithms, and their real-world applications. Delegates will gain hands-on experience with data analysis, and implementing AI solutions across various industries.

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Learn to apply industry-relevant knowledge in Machine Learning and Artificial Intelligence (AI)
Enhance your skill set with our Artificial Intelligence and Machine Learning Courses
Gain ability to increase productivity, save time and money through automation
Learn about AI application areas and related individual fields within AI
Master AI tools and frameworks used in real-world industry projects and innovations

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Artificial Intelligence & Machine Learning

Duration

Online Instructor-led (1 days)

Classroom (1 days)

Online Self-paced (8 hours)

Introduction to Artificial Intelligence Course Outline

Module 1: What is Artificial Intelligence (AI)?

Introduction to Artificial Intelligence
- Types of Artificial Intelligence
- Various Kinds of Technologies
AI Approaches

Module 2: Application Areas of AI

AI in Healthcare
AI in Education
AI in Business
AI in Finance
AI in Law
AI in Manufacturing
Parents Disciplines of AI

Module 3: Artificial Intelligence and Related Fields

Logical AI
Search
Pattern Recognition
Knowledge Representation
Planning
Epistemology
Ontology

Module 4: Foundation of AI – Machine Learning

New Foundation
Machine Learning
Strengths and Limitations of Machine Learning Based AI
Machine Learning Methods
- Supervised Machine Learning Algorithms
- Unsupervised Machine Learning Algorithms
- Semi-Supervised Machine Learning Algorithms
- Reinforcement Machine Learning Algorithms

Module 5: Agents and Environments

Agents
Agent Terminology
Structure of Intelligent Agents
Types of Agents
Nature of Environments
Properties of Environment

Module 6: Concept of Rationality

Rationality
Rational Agents
Perfect Rationality

Module 7: Fuzzy Logic Systems

About Fuzzy Logic
Purpose of Fuzzy Logic
Fuzzy Logic Systems Architecture (FLS)
Application Areas of Fuzzy Logic
Fuzzy Logic Systems Advantages

Module 8: Overview of Robotics

Machine Learning in ANNs
Aspects of Robotics
Robot Locomotion
Components of a Robot
Applications of Robotics

Module 9: Natural Language Processing

Introduction to Natural Language Processing
Components of Natural Language Processing
Natural Language Processing Terminology
Steps in Natural Language Processing

Module 10: Neural Networks

Artificial Neural Networks
What is a Neural Network?
Types of Artificial Neural Networks
Working of Artificial Neural Networks

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Who should attend this Introduction to Artificial Intelligence Training Course?

The Introduction to Artificial Intelligence Course is a comprehensive course designed to equip delegates with the foundational knowledge and skills required to understand, adapt, and harness future AI technologies. The following professionals can benefit from this course:

Software Developers
Data Analysts
Business Analysts
Healthcare Practitioners
Marketing Professionals
Data Scientists
Financial Analysts

Prerequisites of the Introduction to Artificial Intelligence Training Course

There are no formal prerequisites for the Introduction to Artificial Intelligence Course.

Introduction to Artificial Intelligence Course Overview

Artificial Intelligence (AI) stands at the forefront of technological evolution, shaping our future in unprecedented ways. This Artificial Intelligence Course delves into the intricate world of AI and Machine Learning, offering a comprehensive understanding of its mechanisms and impacts. As a rapidly advancing field, AI’s relevance spans various sectors, making it a pivotal area of study and application.

Understanding AI is crucial, particularly for professionals in tech, business, and innovation-driven fields. The Artificial Intelligence Course is designed not just for tech enthusiasts but also for strategists and decision-makers aiming to integrate AI into their operations. Mastery of AI principles is increasingly becoming a necessity, rather than an option, in the modern digital landscape.

The Knowledge Academy's 1-day AI Training provides a concise yet profound exploration of AI. Delegates will gain insights into AI's foundational concepts and real-world applications. This Artificial Intelligence Course is a gateway to harnessing the power of AI, equipping delegates with the knowledge to drive innovation and efficiency in their respective domains.

Course Objectives

To provide an understanding of Artificial Intelligence and Machine Learning concepts
To equip delegates with the skills to identify AI opportunities in their professional fields
To enhance problem-solving capabilities using AI-driven approaches
To foster an understanding of ethical considerations and challenges in AI applications
To offer insights into the latest AI trends and future prospects
To develop a strategic mindset for integrating AI into business solutions

Upon completing this Artificial Intelligence Course, delegates will emerge with a robust understanding of AI, ready to apply their knowledge in practical scenarios. This empowerment will enable them to be innovators and leaders in the AI space, driving positive change and advancement in their respective fields.

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What’s included in this Introduction to Artificial Intelligence Training Course?

World-Class Training Sessions from Experienced Instructors
Introduction to Artificial Intelligence Certificate
Digital Delegate Pack

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Duration

Online Instructor-led (1 days)

Classroom (1 days)

Online Self-paced (8 hours)

Machine Learning Course Outline

Module 1: Machine Learning - Introduction

What is Machine Learning?
Main Elements of Machine Learning
Traditional Programming Vs Machine Learning
Real Time Applications of Machine Learning

Module 2: Importance of Machine Learning and its Techniques

Importance of Machine Learning
Types of Machine Learning
How Machine Learning Works?

Module 3: Machine Learning Mathematics

What is Machine Learning Mathematics?
Why Mathematics is Significant for Machine Learning?

Module 4: Data Pre-Processing

What is Data Pre-Processing?
Way to Handling Missing Values

Module 5: Supervised Learning

Introduction to Supervised Learning

Module 6: Classification

Introduction to Classification
Types of Learners
Support Vector Machines (SVM)
How does SVM Work?
Discriminant Analysis
Naive Bayes
Nearest Neighbour

Module 7: Regression

Introduction to Regression
Regression Models
Linear Regression and GLM
SVR
Decision Tree
Neural Networks

Module 8: Unsupervised Learning

What is Unsupervised Learning?
Difference Between Supervised and Unsupervised Learning

Module 9: Clustering

Introduction to Clustering
K-Means
K-Medoids
Fuzzy
Hierarchal
Gaussian Mixture
Hidden Markov Model

Module 10: Deep Learning

Introduction to Deep Learning
Importance of Deep Learning
How Deep Learning Works?

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Who should attend this Machine Learning Training Course?

The Machine Learning Course is an intensive and comprehensive course designed to provide a deep dive into the fundamental concepts and applications of Machine Learning. The following are some professionals who can benefit greatly from this course:

Data Scientists
Data Analysts
Software Engineers
Business Analysts
Operations Managers
HR Professionals
Project Managers
Customer Service Managers

Prerequisites of the Machine Learning Training Course

Delegates must have a basic understanding of Python Programming and Statistics.

Machine Learning Course Overview

Embark on an immersive exploration of Machine Learning, a transformative field at the intersection of computer science and artificial intelligence. As the digital landscape evolves, the relevance of Machine Learning in extracting insights from data and powering intelligent systems becomes increasingly vital.

Mastery of Machine Learning is imperative for professionals in data science, software development, and business analytics. Those aspiring to harness the potential of data for informed decision-making should aim to master Machine Learning techniques. The Machine Learning Course is tailored for individuals seeking to elevate their analytical skills and stay ahead in an era driven by data-driven innovations.

The Knowledge Academy's 1-day Machine Learning Course equips delegates with practical knowledge and hands-on experience in deploying Machine Learning algorithms. The training delves into the essentials of data analysis, model building, and predictive analytics, ensuring delegates gain a comprehensive understanding of Machine Learning applications. By the end of the course, delegates will be well-versed in leveraging Machine Learning tools to extract meaningful insights and drive informed decision-making.

Course Objectives

To comprehend the fundamental principles of Machine Learning for data-driven insights
To understand the significance of Machine Learning in enhancing analytical and predictive capabilities
To gain hands-on experience in deploying Machine Learning algorithms for real-world applications
To enhance analytical skills through practical application of Machine Learning concepts
To empower professionals to leverage data effectively for informed decision-making
To stay ahead in the dynamic landscape of data-driven innovations

Upon completion, delegates will benefit from enhanced analytical skills and a deep understanding of Machine Learning applications. They will be equipped to apply Machine Learning techniques to real-world scenarios, extracting valuable insights from data and driving informed decision-making in their respective professional domains.

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What’s included in this Machine Learning Training Course?

World-Class Training Sessions from Experienced Instructors
Machine Learning Certificate
Digital Delegate Pack

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Duration

Online Instructor-led (1 days)

Classroom (1 days)

Online Self-paced (8 hours)

Deep Learning Course Outline

Module 1: Machine Learning Basics

What is Machine Learning?
Need for Machine Learning
Types of Machine Learning

Module 2: Introduction to Deep Learning

Importance of Deep Learning
How Deep Learning Works?
Difference Between Deep Learning and Machine Learning

Module 3: Artificial Neural Network

Introduction
Characteristics of Artificial Neural Network

Module 4: Deep Neural Networks

Feedforward Networks
Convolutional Neural Networks
Recurrent Neural Networks

Module 5: Linear Algebra

Mathematical Objects
Computational Rules in Linear Algebra
Matrix Multiplication Properties

Module 6: Probability

Terminology
Random Variables
Probability Distributions
Marginal Probability
Conditional Probability
Chain Rule of Conditional Probabilities
Baye’s Rule

Module 7: Auto Encoders

Need of Auto Encoder
Architecture of Auto Encoders
Applications of Auto Encoders

Module 8: Computational Graphs

What are Computational Graphs?

Module 9: Monte Carlo Methods

Introduction
Machine Learning in Monte Carlo Method

Module 10: Deep Generative Models

Introduction
Boltzmann Machines
- Functioning of Boltzmann Machines

Module 11: Deep Learning Applications

Applications of Deep Learning

Module 12: Libraries and Frameworks

Libraries
Framework
- Features of Deep Learning Framework

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Who should attend this Deep Learning Course?

This Deep Learning Training Course aims at equipping individuals with knowledge of Natural Language Processing, Robotics, and even Healthcare. This course will teach Deep Learning algorithms, technologies, and applications providing delegates the skills needed to implement and adapt Deep Learning models for different tasks. This course can be beneficial for a wide range of professionals, including:

Data Scientists
Machine Learning Engineers
Research Scientists
Software Developers
Artificial Intelligence (AI)/Machine Learning (ML) Product Managers
Business Analysts
Finance Professionals

Prerequisites of the Deep Learning Course

To attend this Deep Learning Training Course, delegates should have a basic understanding of Python, Linear Algebra, and Probability.

Deep Learning Course Overview

Deep Learning is a subset of Artificial Intelligence (AI) that focuses on algorithms inspired by the structure and function of the human brain's neural networks. It's pivotal in revolutionising industries like healthcare, finance, and technology by enabling machines to learn from data, recognise patterns, and make intelligent decisions autonomously.

Proficiency in Deep Learning Course is crucial for Data Scientists, AI Engineers, Software Developers, and Researchers. Mastering this field empowers professionals to create innovative image and speech recognition solutions, natural language processing, autonomous vehicles, and predictive analytics. It is essential for those aiming to stay competitive and drive technological advancements across various industries.

This intensive 1-day Deep Learning Training equips delegates with fundamental concepts and practical skills in deep learning. Through hands-on workshops and expert-led sessions, delegates comprehensively understand neural networks, convolutional and recurrent neural networks, and their applications. Delegates learn to implement deep learning models, interpret results, and optimise algorithms for diverse real-world scenarios.

Course Objectives

To understand the foundational principles of neural networks
To explore various deep learning architectures, including CNNs and RNNs
To apply Deep Learning algorithms in image and speech recognition tasks
To analyse and interpret profound learning model results effectively
To optimise and fine-tune neural networks for improved performance
To comprehend ethical considerations in deploying deep learning solutions
To develop practical skills through hands-on exercises and case studies
To foster confidence in applying deep learning techniques in real-world projects

After completing the Deep Learning Training, delegates receive a certification validating their proficiency in deep learning fundamentals. This certification attests to their understanding of neural network concepts, ability to design and implement deep learning models, and skills in utilising these techniques to solve practical problems effectively.

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What’s included in this Deep Learning Course?

World-Class Training Sessions from Experienced Instructors
Deep Learning Certificate
Digital Delegate Pack

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Duration

Online Instructor-led (1 days)

Classroom (1 days)

Online Self-paced (8 hours)

Deep Learning with TensorFlow Course Outline

Module 1: Introduction to TensorFlow

Tensors
TensorFlow
Installation of TensorFlow
Two Computation Phrases
Variables
Operations
A Computational Graph with TensorBoard
Linear Regression

Module 2: Artificial Neural Network

Introduction
Characteristics of Artificial Neural Network

Module 3: Activate Functions

Introduction Activation (Transfer) Functions
Types of Activate Functions
Unit Step (Threshold)
Sigmoid
Piecewise Linear
Gaussian
Linear

Module 4: Deep Learning Techniques

Introduction
Convolutional Neural Networks
Recurrent Neural Networks

Module 5: Deep Learning Applications

Applications of Deep Learning

Module 6: Computing Gradients

Introduction
Steps for Computing Gradients

Module 7: Single-Layer and Multi-Layer Perceptron

Perceptron
- Single-Layer Perceptron
- Multi-Layer Perceptron (MLP)

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Who should attend this Deep Learning with TensorFlow Training Course?

The Deep Learning with TensorFlow Course is a specialised course focused on advanced Machine Learning techniques using TensorFlow, one of the most widely used open-source libraries for numerical computation and Machine Learning. The following professionals will benefit greatly from this course:

Machine Learning Engineers
Data Scientists
Artificial Intelligence (AI) Researchers
Software Developers
Natural Language Processing Engineers
Automotive Engineers
Robotics Engineers

Prerequisites of the Deep Learning with TensorFlow Training Course

Delegates should have a basic understanding of Python Programming and Machine Learning.

Deep Learning with TensorFlow Course Overview

Deep Learning with TensorFlow is a comprehensive course designed to teach professionals how to build and deploy deep learning models using the TensorFlow framework. This course is essential for those looking to harness the power of neural networks to solve complex problems and drive innovation in fields like healthcare, finance, and technology.

Proficiency in TensorFlow and deep learning is crucial for Data Scientists, AI Engineers, Software Developers, and Researchers. Mastering this field empowers professionals to develop cutting-edge solutions in image and speech recognition, natural language processing, autonomous systems, and predictive analytics. It is vital for anyone aiming to stay competitive and lead technological advancements in their industry.

This intensive 1-day course equips delegates with a thorough understanding of deep learning concepts and practical skills using TensorFlow. Through hands-on workshops and expert-led sessions, delegates gain insights into neural network architectures, including convolutional and recurrent neural networks, and their applications. Delegates learn to implement deep learning models, interpret their results, and optimise them for various real-world scenarios.

Course Objectives

To understand the foundational principles of neural networks
To explore TensorFlow and its capabilities in building deep learning models
To apply deep learning algorithms in image and speech recognition tasks
To analyse and interpret deep learning model results effectively
To optimise and fine-tune neural networks for improved performance
To comprehend ethical considerations in deploying deep learning solutions

Upon completing this course, delegates will have acquired the knowledge and skills necessary to implement and optimise deep learning models using TensorFlow, making them invaluable assets in their professional fields.

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What’s included in this Deep Learning with TensorFlow Training Course?

World-Class Training Sessions from Experienced Instructors
Deep Learning with TensorFlow Certificate
Digital Delegate Pack

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Duration

Online Instructor-led (2 days)

Classroom (2 days)

Online Self-paced (16 hours)

Natural Language Processing (NLP) Fundamentals with Python Course Outline

Module 1: Introduction to NLP

What is Natural Language Processing?
Why is Natural Language Processing Important?
Applications of Natural Language Processing
Challenges in Natural Language Processing
Tools and Resources for Natural Language Processing

Module 2: Text Preprocessing

Text Cleaning and Normalisation
Tokenisation
Part of Speech Tagging
Named Entity Recognition
Stop Word Removal

Module 3: Text Representation

Bag of Words
Term Frequency-Inverse Document Frequency (TF-IDF)
Word Embeddings
Topic Modelling

Module 4: Text Classification

Supervised Learning
Naive Bayes
Support Vector Machines (SVM)
Decision Trees
Evaluation Metrics for Text Classification

Module 5: Advanced Natural Language Processing Techniques

Sequence Labelling
Language Modelling
Neural Machine Translation
Sentiment Analysis
Text Summarisation

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Who should attend this Natural Language Processing (NLP) Fundamentals with Python Course?

The Natural Language Processing (NLP) Fundamentals with Python Course can be beneficial for a wide range of individuals who are interested in understanding and working with text data. The following are some professionals who can benefit from this course:

Software Developers
Data Scientists
Machine Learning Engineers
Data Analysts
Artificial Intelligence (AI) Researchers
Product Managers
Business Analysts

Prerequisites of the Natural Language Processing (NLP) Fundamentals with Python Course

Delegates should have a basic knowledge and understanding of Python.

Natural Language Processing (NLP) Fundamentals with Python Course Overview

Natural Language Processing (NLP) is a branch of Artificial Intelligence (AI) that focuses on the interaction between computers and human language. It is pivotal in transforming industries like customer service, healthcare, and finance by enabling machines to understand, interpret, and generate human language in a valuable way.

Proficiency in NLP with Python is crucial for Data Scientists, AI Engineers, Software Developers, and Linguists. Mastering this field empowers professionals to create innovative text analysis solutions, sentiment analysis, language translation, and chatbots. It is essential for those aiming to stay competitive and drive advancements in technology across various sectors.

This intensive 2-day course equips delegates with fundamental concepts and practical skills in natural language processing using Python. Through hands-on workshops and expert-led sessions, delegates comprehensively understand text preprocessing, tokenisation, and sentiment analysis. Delegates learn to implement NLP models, interpret results, and optimise algorithms for diverse real-world scenarios.

Course Objectives

To understand the foundational principles of natural language processing
To explore various NLP techniques, including text preprocessing and tokenisation
To apply NLP algorithms in sentiment analysis and language translation tasks
To analyse and interpret NLP model results effectively
To optimise and fine-tune NLP algorithms for improved performance
To comprehend ethical considerations in deploying NLP solutions

Upon completing this course, delegates will have acquired the knowledge and skills necessary to implement and optimise NLP models using Python, making them invaluable assets in their professional fields.

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What’s included in this Natural Language Processing (NLP) Fundamentals with Python Course?

World-Class Training Sessions from Experienced Instructors
Natural Language Processing (NLP) Fundamentals with Python Certificate
Digital Delegate Pack

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Duration

Online Instructor-led (1 days)

Classroom (1 days)

Online Self-paced (8 hours)

Artificial Intelligence (AI) for Project Managers Course Outline

Module 1: Introduction to Artificial Intelligence

Overview
Aim and Purpose
Scope of Research
AI Within the Corporate Context

Module 2: Theoretical Framework

Industry 4.0
Types of AI Systems
Project Management Fundamentals
Future of Project Management
AI for Project Management
SWOT Analysis

Module 3: Methodology

Research Strategy
Research Design
Research Process
Research Quality – Reliability, Replicability, and Validity
Ethical Considerations

Module 4: Results – Surveys

Introduction
Artificial Intelligence
Project Management
Organisational Business

Module 5: Results – Interviews

Interviews
Project Management
Artificial Intelligence

Module 6: Analysis and Discussion

Project Management Community Requirements
Awareness of AI Systems
Building AI Systems for Project Managers
Implementing AI for Project Managers in the Organisation

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Who should attend this Artificial Intelligence (AI) for Project Managers Course?

The Artificial Intelligence (AI) for Project Managers Training Course is tailored for individuals working in the Business Analysis field to help them analyse business operations thoroughly and help in strategy development. The following are some professionals for whom this course can be beneficial:

Business Analysts
Data Analysts
Project Managers
Product Managers
UX/UI Designers
Software Engineers
Operations Managers

Prerequisites of the Artificial Intelligence (AI) for Project Managers Course

There are no formal prerequisites for this Artificial Intelligence (AI) for Project Managers Course.

Artificial Intelligence (AI) for Project Managers Course Overview

Artificial Intelligence (AI) is revolutionising project management by automating routine tasks, improving decision-making, and enhancing overall project efficiency. AI technologies such as machine learning, natural language processing, and predictive analytics empower project managers to plan, execute, and deliver projects more effectively by leveraging data-driven insights and intelligent automation.

Proficiency in AI is crucial for Project Managers, Programme Managers, PMO Directors, and other professionals involved in project delivery. Mastering AI tools and techniques enables these professionals to streamline project workflows, foresee risks, optimise resource allocation, and improve stakeholder communication. It is essential for those aiming to stay competitive and drive innovation in project management practices across various industries.

This intensive 1-day course equips delegates with fundamental concepts and practical skills in applying AI to Project Management. Through hands-on workshops and expert-led sessions, delegates gain a comprehensive understanding of AI applications in project management, including task automation, predictive analytics, and intelligent decision support systems. Delegates learn to implement AI-driven tools, interpret AI insights, and integrate AI solutions into their project management processes effectively.

Course Objectives

To understand the foundational principles of AI and its relevance to Project Management
To explore various AI tools and techniques used in automating Project Management tasks
To apply machine learning algorithms for predictive project analytics
To analyse and interpret AI-generated insights for improved decision-making
To optimise project workflows and resource management using AI technologies
To comprehend ethical considerations in deploying AI solutions in Project Management

Upon completing this course, delegates will have acquired the knowledge and skills necessary to implement and optimise AI-driven Project Management practices, making them invaluable assets in their professional fields.

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What’s included in this Artificial Intelligence (AI) for Project Managers Course?

World-Class Training Sessions from Experienced Instructors
Artificial Intelligence (AI) for Project Managers Certificate
Digital Delegate Pack

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More information

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Duration

Online Instructor-led (1 days)

Classroom (1 days)

Online Self-paced (8 hours)

Artificial Intelligence (AI) for Business Analysts Course Outline

Module 1: Introduction to Artificial Intelligence

Overview
Need for Artificial Intelligence
AI Approaches

Module 2: Use of Artificial Intelligence (AI)

In Banking and In Finance
In Investment

Module 3: AI and Its Relevance to Banking

Overview
How is AI Firming Up the Competitiveness of Banks?

Module 4: AI Applications in the Banking Industry

AML Pattern Detection
Chatbots
Algorithmic Trading
Fraud Detection

Module 5: Impact of Artificial Intelligence on Investing

Overview
How can You Use AI and ML for Trading/Investing?

Module 6: AI and Its Impact on Finance Industry

Introduction

Module 7: Future Evolution of Business Analyst

Introduction
How Will Business Analysis Evolve with Artificial Intelligence?

Module 8: Hybrid Roles for Future Business Analyst

Business Analyst/Project Manager
Product Owner
Programmer/Analyst
Data Analyst and User Experience Designer (UX)

Module 9: How AI Change the Face of Business?

Overview
Superior Enterprise Mobility Through AI
Marketing and Advertising
Increased Efficiency and Higher Precision at Lower Costs
Help to Integrate and Consolidate Business Operations
Stronger Cyber Security

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Who should attend this Artificial Intelligence (AI) for Business Analysts Course?

The Artificial Intelligence (AI) for Business Analysts Training Course is tailored for individuals working in the Business Analysis field to help them analyse business operations thoroughly and aid in strategy development. The following are some professionals for whom this course can be beneficial:

Business Analysts
Data Analysts
Project Managers
Product Managers
UX/UI Designers
Software Engineers
Operations Managers

Prerequisites of the Artificial Intelligence (AI) for Business Analysts Course

There are no formal prerequisites for this Artificial Intelligence (AI) for Business Analysts Training Course.

Artificial Intelligence (AI) for Business Analysts Course Overview

Artificial Intelligence (AI) is revolutionising business analysis by automating routine tasks, improving decision-making, and enhancing overall operational efficiency. AI technologies such as machine learning, natural language processing, and predictive analytics empower business analysts to analyse data, derive insights, and develop strategies more effectively by leveraging data-driven insights and intelligent automation.

Proficiency in AI is crucial for Business Analysts, Data Analysts, Project Managers, and other professionals involved in business operations. Mastering AI tools and techniques enables these professionals to streamline analytical workflows, foresee market trends, optimise resource allocation, and improve stakeholder communication. It is essential for those aiming to stay competitive and drive innovation in business analysis practices across various industries.

This intensive 1-day course equips delegates with fundamental concepts and practical skills in applying AI to Business Analysis. Through hands-on workshops and expert-led sessions, delegates gain a comprehensive understanding of AI applications in business analysis, including data automation, predictive analytics, and intelligent decision support systems. Delegates learn to implement AI-driven tools, interpret AI insights, and integrate AI solutions into their business analysis processes effectively.

Course Objectives

To understand the foundational principles of AI and its relevance to Business Analysis
To explore various AI tools and techniques used in automating Business Analysis tasks
To apply machine learning algorithms for predictive analytics
To analyse and interpret AI-generated insights for improved decision-making
To optimise business workflows and resource management using AI technologies
To comprehend ethical considerations in deploying AI solutions in Business Analysis

Upon completing this course, delegates will have acquired the knowledge and skills necessary to implement and optimise AI-driven Business Analysis practices, making them invaluable assets in their professional fields.

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What’s included in this Artificial Intelligence (AI) for Business Analysts Course?

World-Class Training Sessions from Experienced Instructors
Artificial Intelligence (AI) for Business Analysts Certificate
Digital Delegate Pack

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Duration

Online Instructor-led (1 days)

Classroom (1 days)

Online Self-paced (8 hours)

Artificial Intelligence (AI) for DevOps Course Outline

Module 1: Introduction to Artificial Intelligence and DevOps

What is Artificial Intelligence (AI)?
Why AI is Important in Modern Tech
Business Benefits and Use Cases of AI
Introduction to DevOps
Objectives and Values of DevOps
Challenges in Scaling DevOps
How AI Complements DevOps

Module 2: AI in DevOps Automation

DevOps Automation as an Ideal Use Case for AI
AI-Driven Automation in DevOps
Key Tools & Software Stacks for AI in DevOps
Required Systems for AI-Driven DevOps
Phases of DevOps Maturity

Module 3: Transforming DevOps with AI

Intelligent Release Orchestration and Management
AI in Quality Assurance and Control
Software Testing Enhancements
Swifter Failure Forecasting
Faster Root Cause Analysis
Improved Data Access and Feedback Loops
Time Alerts and Anomaly Detection

Module 4: The Future of DevOps with AI

Smarter Resource Management
Efficient Team Collaboration
Future Trends in AI for DevOps
How DevOps and AI Operate Together

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Who should attend this Artificial Intelligence (AI) for DevOps Course?

The Artificial Intelligence (AI) for DevOps Training Course is tailored for individuals working in the DevOps field to help them enhance their operations and improve efficiency through AI technologies. The following are some professionals for whom this course can be beneficial:

DevOps Engineers
Systems Administrators
Cloud Engineers
Software Developers
IT Managers
Operations Managers
Infrastructure Engineers

Prerequisites of the Artificial Intelligence (AI) for DevOps Course

There are no formal prerequisites for this Artificial Intelligence (AI) for DevOps Training Course.

Artificial Intelligence (AI) for DevOps Course Overview

Artificial Intelligence (AI) is revolutionising DevOps by automating routine tasks, improving decision-making, and enhancing overall operational efficiency. AI technologies such as machine learning, natural language processing, and predictive analytics empower DevOps professionals to plan, execute, and manage operations more effectively by leveraging data-driven insights and intelligent automation.

Proficiency in AI is crucial for DevOps Engineers, Systems Administrators, IT Managers, and other professionals involved in DevOps processes. Mastering AI tools and techniques enables these professionals to streamline operations, foresee risks, optimise resource allocation, and improve system reliability. It is essential for those aiming to stay competitive and drive innovation in DevOps practices across various industries.

This intensive 1-day course equips delegates with fundamental concepts and practical skills in applying AI to DevOps. Through hands-on workshops and expert-led sessions, delegates gain a comprehensive understanding of AI applications in DevOps, including task automation, predictive analytics, and intelligent decision support systems. Delegates learn to implement AI-driven tools, interpret AI insights, and integrate AI solutions into their DevOps processes effectively.

Course Objectives

To understand the foundational principles of AI and its relevance to DevOps
To explore various AI tools and techniques used in automating DevOps tasks
To apply machine learning algorithms for predictive analytics in DevOps
To analyse and interpret AI-generated insights for improved decision-making
To optimise operational workflows and resource management using AI technologies
To comprehend ethical considerations in deploying AI solutions in DevOps

Upon completing this course, delegates will have acquired the knowledge and skills necessary to implement and optimise AI-driven DevOps practices, making them invaluable assets in their professional fields.

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What’s included in this Artificial Intelligence (AI) for DevOps Course?

World-Class Training Sessions from Experienced Instructors
Artificial Intelligence (AI) for DevOps Certificate
Digital Delegate Pack

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More information

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Duration

Online Instructor-led (1 days)

Classroom (1 days)

Online Self-paced (8 hours)

Artificial Intelligence (AI) for IT Professionals Course Outline

Module 1: Introduction to Artificial Intelligence (AI).

What is Artificial Intelligence?

Module 2: Building Blocks of AI.

Machine Learning.
Deep Learning.

Module 3: AI vs Machine Learning vs Deep Learning.

Difference Between AI, Machine Learning, and Deep Learning.

Module 4: How to Train AI?

Overview.
Steps in the Process of AI Training.

Module 5: Implementing AI in an Organisation.

Identify AI Opportunities.
Develop an AI Roadmap.
Identify AI Based Solutions.
Identify Data Requirements.

Module 6: AI Use Cases in Information Management.

Supervision of AI.
Implementation Areas of AI.
Cognitive Computing.

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Who should attend this Artificial Intelligence (AI) for IT Professionals (AI4IT) Course?

The Artificial Intelligence (AI) for IT Professionals (AI4IT) Course is tailored for individuals working in the IT field to help them integrate AI technologies into their workflows and enhance system efficiencies. The following are some professionals for whom this course can be beneficial:

IT Managers
Data Scientists
Software Engineers
System Administrators
Network Engineers
Database Administrators
Cybersecurity Analysts

Prerequisites of the Artificial Intelligence (AI) for IT Professionals (AI4IT) Course

There are no formal prerequisites for this Artificial Intelligence (AI) for IT Professionals Course.

Artificial Intelligence (AI) for IT Professionals (AI4IT) Course Overview

Artificial Intelligence (AI) is revolutionising IT operations by automating routine tasks, improving system performance, and enhancing overall IT efficiency. AI technologies such as machine learning, natural language processing, and predictive analytics empower IT professionals to manage, optimise, and secure IT systems more effectively by leveraging data-driven insights and intelligent automation.

Proficiency in AI is crucial for IT Managers, Data Scientists, Software Engineers, and other IT professionals involved in system management and optimisation. Mastering AI tools and techniques enables these professionals to streamline IT workflows, foresee system failures, optimise resource allocation, and improve security measures.

This intensive 1-day course equips delegates with fundamental concepts and practical skills in applying AI to IT operations. Through hands-on workshops and expert-led sessions, delegates gain a comprehensive understanding of AI applications in IT, including system automation, predictive maintenance, and intelligent security systems.

Course Objectives

To understand the foundational principles of AI and its relevance to IT operations
To explore various AI tools and techniques used in automating IT tasks
To apply machine learning algorithms for predictive system analytics
To analyse and interpret AI-generated insights for improved system management
To optimise IT workflows and resource management using AI technologies
To comprehend ethical considerations in deploying AI solutions in IT

Upon completing this course, delegates will have acquired the knowledge and skills necessary to implement and optimise AI-driven IT practices, making them invaluable assets in their professional fields.

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What’s included in this Artificial Intelligence (AI) for IT Professionals (AI4IT) Course?

World-Class Training Sessions from Experienced Instructors.
Artificial Intelligence (AI) for IT Professionals (AI4IT) Certificate.
Digital Delegate Pack.

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Duration

Online Instructor-led (1 days)

Classroom (1 days)

Online Self-paced (8 hours)

Recommendation System Training Course Outline

Module 1: Introduction to Recommender Systems

What is Recommender System?
Types of Recommender Systems
How Recommender System Works?
Challenges of Recommender System

Module 2: Collaborative Recommendation Approaches

Memory Based Approaches
Model-Based Approach
Python Implementation

Module 3: Content Based Recommendation

What is Content-Based Recommendation System?
User Profile
Item Profile
Utility Matrix

Module 4: Hybrid Recommendation

Hybridisation Recommendation System
Monolithic Hybridisation Design
Parallelised Hybridisation Design
Pipeline Hybridisation Design

Module 5: Evaluating Recommender Systems

Evaluation Methods
- Experimental (Online Experiments)
- Non-Experimental (Offline Experiments)
- Simulation Experiments
Common Metrices

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Who should attend this Recommendation System Training Course?

The Recommendation System Course is tailored for individuals working in the data science and analytics field to help them understand and implement recommendation algorithms effectively. The following are some professionals for whom this course can be beneficial:

Data Scientists
Machine Learning Engineers
Data Analysts
Software Developers
Product Managers
Business Analysts
UX/UI Designers

Prerequisites of the Recommendation System Training Course

There are no formal prerequisites for this Recommendation System Course.

Recommendation System Training Course Overview

Recommendation systems are integral to many online platforms, providing personalised suggestions to users and enhancing their experience. By analysing user data and behaviour, recommendation systems help businesses increase engagement and drive sales through tailored content delivery.

Proficiency in building and optimising recommendation systems is crucial for Data Scientists, Machine Learning Engineers, and other professionals involved in data analysis and product development. Mastering recommendation algorithms and techniques enables these professionals to create systems that understand user preferences, predict user behaviour, and provide relevant recommendations.

This intensive 1-day course equips delegates with fundamental concepts and practical skills in developing recommendation systems. Through hands-on workshops and expert-led sessions, delegates gain a comprehensive understanding of collaborative filtering, content-based filtering, and hybrid recommendation approaches. Delegates learn to implement recommendation algorithms, evaluate their performance, and optimise them for diverse real-world applications.

Course Objectives

To understand the foundational principles of recommendation systems and their importance
To explore various recommendation techniques, including collaborative filtering and content-based filtering
To apply machine learning algorithms in developing recommendation systems
To analyse and interpret recommendation system outputs for improved user experience
To optimise recommendation algorithms for better accuracy and performance
To comprehend ethical considerations in deploying recommendation systems

Upon completing this course, delegates will have acquired the knowledge and skills necessary to implement and optimise recommendation systems, making them invaluable assets in their professional fields.

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What’s included in this Recommendation System Training Course?

World-Class Training Sessions from Experienced Instructors
Recommendation System Certificate
Digital Delegate Pack

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Duration

Online Instructor-led (1 days)

Classroom (1 days)

Online Self-paced (8 hours)

Neural Networks with Deep Learning Training Course Outline

Module 1: Introduction to Neural Networks

Introduction to Neural Networks
Supervised Learning with Neural Networks

Module 2: Neural Networks Fundamentals

Binary Classification
Logistic Regression
Gradient Descent and Derivatives
Computational Graph
Vectorisation
Introduction to Python
Jupyter/IPython Notebooks

Module 3: Shallow Neural Networks

Representation of a Neural Networks
Computing the Output of a Neural Network
Vectorised Implementation
- Feed Forward
- Back Propagation
Hidden Layer
Activation Functions
Gradient Descent for Neural Networks

Module 4: Deep Neural Networks

Deep L-Layer Neural Network
Forward Propagation
Computational Graphs
Backward Propagation
Neural Networks Training
Deep Representations
Building Blocks
Difference Between Parameters and Hyperparameters

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Who should attend this Neural Networks with Deep Learning Training Course?

The Neural Networks with Deep Learning Course is designed for individuals working in data science, artificial intelligence, and related fields who wish to deepen their understanding and practical skills in deep learning. The following are some professionals for whom this course can be beneficial:

Data Scientists
AI Engineers
Software Developers
Machine Learning Engineers
Researchers
Analysts
IT Professionals

Prerequisites of the Neural Networks with Deep Learning Training Course

There are no formal prerequisites for this Neural Networks with Deep Learning Course. However, a basic understanding of programming and familiarity with machine learning concepts would be beneficial.

Neural Networks with Deep Learning Training Course Overview

Proficiency in Deep Learning is crucial for Data Scientists, AI Engineers, Software Developers, and Researchers. Mastering this field empowers professionals to create innovative image and speech recognition solutions, natural language processing, autonomous vehicles, and predictive analytics. It is essential for those aiming to stay competitive and drive technological advancements across various industries.

This intensive 1-day course equips delegates with fundamental concepts and practical skills in deep learning. Through hands-on workshops and expert-led sessions, delegates comprehensively understand neural networks, convolutional and recurrent neural networks, and their applications. Delegates learn to implement deep learning models, interpret results, and optimise algorithms for diverse real-world scenarios.

Course Objectives

To understand the foundational principles of neural networks
To explore various deep learning architectures, including CNNs and RNNs
To apply Deep Learning algorithms in image and speech recognition tasks
To analyse and interpret profound learning model results effectively
To optimise and fine-tune neural networks for improved performance
To comprehend ethical considerations in deploying deep learning solutions

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What’s included in this Neural Networks with Deep Learning Training Course?

World-Class Training Sessions from Experienced Instructors
Neural Networks with Deep Learning Certificate
Digital Delegate Pack

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Duration

Online Instructor-led (1 days)

Classroom (1 days)

Online Self-paced (8 hours)

AI and ML with Excel Training Course Outline

Module 1: Introducing AI in MS Excel

What is AI for Excel?
Intelligent Suggestions with Ideas
Making New Data Types
Availability
Preparing Data
Running Insights
Improving Machine Learning

Module 2: Machine Learning with Excel

Training Set Vs Test Set
Classification Models
Preparing Data in Excel
Building the Model
- Calculating Distance
- Finding Nearest Neighbour
Set Up and Running Algorithm

Module 3: Smart Spreadsheets

Artificial Intelligence Based Features in Excel
Benefits of Smart Sheets
Why Rollback?

Module 4: Dynamic Arrays in Excel

Introduction to Dynamic Arrays
Dynamic Arrays Formula
- UNIQUE
- SORT
- SORT BY
- SEQUENCE
- RANDARRAY
- FILTER
- LOOKUP

Module 5: Automated Text Analysis Using AI in Excel

What is Text Analysis?
How Can Text Analysis Help?
How to Use Text Analysis Tools in Excel?
Create Text Analysis Model
Text Analysis Use Cases and Applications

Module 6: Linear Regression Analysis in Excel

Introduction to Linear Regression
How to Add Linear Regression Data Analysis Tool in Excel?
Methods for Using Linear Regression in Excel
- Scatter Chart with a Trendline
- Analysis ToolPak Add-In Method
How to Do Regression in Excel Using Formulas?

Module 7: Cluster Analysis in Excel

Steps to Run K-Means Cluster Analysis
- Start with Dataset
- Use Scatter Graph
- Calculate Distance from Each Data Point
- Calculate Mean (Average) of Each Cluster Set
- Distance from the Revised Mean
- Graph and Summarise the Clusters

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Who should attend this AI And ML With Excel Training Course?

The AI And ML With Excel Course is tailored for individuals working in data analysis and business intelligence fields to help them leverage AI and machine learning capabilities using Excel. The following are some professionals for whom this course can be beneficial:

Business Analysts
Data Analysts
Project Managers
Product Managers
Financial Analysts
Operations Managers
Excel Power Users

Prerequisites of the AI And ML With Excel Training Course

There are no formal prerequisites for this AI And ML With Excel Course.

AI And ML With Excel Training Course Overview

Artificial Intelligence (AI) and Machine Learning (ML) are transforming how data is analysed and utilised across various industries. Integrating these advanced technologies into Excel empowers professionals to perform complex data analysis, predictive modelling, and data-driven decision-making within a familiar tool.

Proficiency in AI and ML with Excel is crucial for Business Analysts, Data Analysts, Project Managers, and other professionals involved in data-intensive roles. Mastering these tools enables these professionals to uncover deeper insights, make accurate predictions, and drive strategic initiatives. It is essential for those aiming to stay competitive and enhance their data analysis capabilities.

This intensive 1-day course equips delegates with fundamental concepts and practical skills in applying AI and ML using Excel. Through hands-on workshops and expert-led sessions, delegates gain a comprehensive understanding of AI and ML applications in data analysis, including data preprocessing, model building, and result interpretation. Delegates learn to implement AI-driven tools, interpret ML insights, and integrate these solutions into their analytical processes effectively.

Course Objectives

To understand the foundational principles of AI and ML and their relevance to data analysis
To explore various AI and ML tools and techniques available in Excel
To apply machine learning algorithms for predictive analytics using Excel
To analyse and interpret AI-generated insights for improved decision-making
To optimise data workflows and resource management using AI technologies in Excel
To comprehend ethical considerations in deploying AI and ML solutions in data analysis

Upon completing this course, delegates will have acquired the knowledge and skills necessary to implement and optimise AI-driven data analysis practices using Excel, making them invaluable assets in their professional fields.

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What’s included in this AI and ML with Excel Training Course?

World-Class Training Sessions from Experienced Instructors
AI and ML with Excel Certificate
Digital Delegate Pack

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Duration

Online Instructor-led (1 days)

Classroom (1 days)

Online Self-paced (8 hours)

OpenAI Training Course Outline

Module 1: Introduction to OpenAI

Overview of OpenAI
Core Technologies and Innovations
Introduction to APIs and Models
Understanding OpenAI's Mission and Ethics
Review of Usage Policies and Guidelines

Module 2: Utilizing Text Completion

Basics of Text Completion
Crafting Effective Prompts
Strategies for Text Insertion and Editing
Practical Examples and Applications
Advanced Prompt Engineering Techniques

Module 3: Code Completion Essentials

Introduction to Code Completion
Best Practices for Code Automation
Techniques for Inserting and Editing Code
Usage Scenarios and Case Studies
Optimizing Code Completion with Examples

Module 4: Image Generation Techniques

Fundamentals of Image Generation
Tips for Language-Specific Usage
Application Scenarios
Advanced Features and Customization Options

Module 5: Advanced Fine-Tuning

Preparing Your Dataset
Fine-Tuning Models for Specific Needs
Utilizing Weights and Biases
Advanced Techniques and Tips for Effective Fine-Tuning

Module 6: Understanding and Using Embeddings

Introduction to Embeddings
How to Generate and Retrieve Embeddings
Overview of Different Embedding Models
Use Cases and Implementation Examples
Limitations and Risks Associated with Embeddings

Module 7: Implementing Moderation

Moderation Fundamentals
Setting Up and Using the Moderation API
Best Practices for Content Moderation
Strategies for Effective Use

Module 8: Safety Best Practices

Using the Moderation API for Safety
Techniques for Adversarial Testing
Implementing Human in the Loop (HITL)
Effective Prompt Engineering for Safety
Know Your Customer (KYC) Policies
Managing User Inputs and Outputs
Enabling User Feedback on Issues
Communicating Limitations to End-Users

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Who should attend this OpenAI Training Course?

The OpenAI Course is tailored for individuals working in the technology and data science fields to help them understand and implement OpenAI technologies effectively. The following are some professionals for whom this course can be beneficial:

Data Scientists
AI Engineers
Software Developers
Machine Learning Researchers
Business Analysts
IT Professionals
Product Managers

Prerequisites of the OpenAI Training Course

There are no formal prerequisites for this OpenAI Course.

OpenAI Training Course Overview

Artificial Intelligence (AI) is revolutionising numerous industries by automating complex tasks, improving decision-making, and enhancing overall efficiency. OpenAI technologies such as GPT-4 and DALL-E enable professionals to create intelligent applications, generate natural language responses, and produce high-quality content autonomously.

Proficiency in OpenAI is crucial for Data Scientists, AI Engineers, Software Developers, and other professionals involved in AI development. Mastering OpenAI tools and techniques empowers these professionals to build advanced AI models, generate insightful data analysis, and create innovative AI-driven applications. It is essential for those aiming to stay competitive and drive technological advancements in their respective fields.

This intensive 1-day course equips delegates with fundamental concepts and practical skills in applying OpenAI technologies. Through hands-on workshops and expert-led sessions, delegates gain a comprehensive understanding of OpenAI applications, including natural language processing, content generation, and AI model development. Delegates learn to implement OpenAI tools, interpret AI outputs, and integrate AI solutions into their workflows effectively.

Course Objectives

To understand the foundational principles of OpenAI and its relevance to various industries
To explore various OpenAI tools and techniques used in AI model development
To apply machine learning algorithms for natural language processing tasks
To analyse and interpret AI-generated content for improved decision-making
To optimise workflows and resource management using OpenAI technologies
To comprehend ethical considerations in deploying OpenAI solutions

Upon completing this course, delegates will have acquired the knowledge and skills necessary to implement and optimise AI-driven practices using OpenAI technologies, making them invaluable assets in their professional fields.

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What’s included in this OpenAI Training Course?

World-Class Training Sessions from Experienced Instructors
OpenAI Certificate
Digital Delegate Pack

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Duration

Online Instructor-led (1 days)

Classroom (1 days)

Online Self-paced (8 hours)

Cognitive Computing Training Course Outline

Module 1: Introduction to Cognitive Computing

What is Cognitive Computing?
Features of Cognitive Computing Solution
Working of Cognitive Computing
Cognitive Computing Vs Artificial Intelligence
Advantages of Cognitive Computing

Module 2: Computational Linguistics

Syntax and Parsing
Semantic Representation
Semantic Interpretation
Making Sense of Text
Language Generation

Module 3: Cognitive Computing – Practical Applications

Knowledge Extraction and Summarisation
Sentiment Analysis
Virtual Worlds, Games, and Interactive Fiction
Natural Language User Interfaces
Other Applications

Module 4: Introduction to Machine Learning

What is Machine Learning?
Categories of Machine Learning
Scikit-learn Algorithm
Machine Learning Skills
Artificial Neural Networks
Implementation of Machine Learning

Module 5: TensorFlow for Implementing Deep Neural Networks

Installing TensorFlow
Convolutional Deep Neural Networks for Image Classification

Module 6: Tools and Techniques – Natural Language Processing

Overview of spaCy NLP Library
spaCy for
Assigning Part of Speech Tags
Dependency Parsing
Entity Recognition
Rule-Based Matching
Overview of OpenNLP Library and Installation

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Who should attend this Cognitive Computing Training?

The Cognitive Computing Course is tailored for individuals working in the Business Analysis field to help them analyse business operations thoroughly and help in strategy development. This course will be beneficial for a wide range of professionals, including:

Business Analysts
Data Analysts
Project Managers
Product Managers
UX/UI Designers
Software Engineers
Operations Managers

Prerequisites of the Cognitive Computing Training

There are no formal prerequisites for this Cognitive Computing Course.

Cognitive Computing Training Course Overview

Cognitive Computing is revolutionising project management by automating routine tasks, improving decision-making, and enhancing overall project efficiency. Cognitive technologies such as machine learning, natural language processing, and predictive analytics empower Project Managers to plan, execute, and deliver projects more effectively by leveraging data-driven insights and intelligent automation.

Proficiency in Cognitive Computing is crucial for Project Managers, Programme Managers, PMO Directors, and other professionals involved in project delivery. Mastering Cognitive Computing tools and techniques enables these professionals to streamline project workflows, foresee risks, optimise resource allocation, and improve stakeholder communication. It is essential for those aiming to stay competitive and drive innovation in project management practices across various industries.

This intensive 1-day course by The Knowledge Academy equips delegates with fundamental concepts and practical skills in applying Cognitive Computing to Project Management. Through hands-on workshops and expert-led sessions, delegates gain a comprehensive understanding of Cognitive Computing applications in project management, including task automation, predictive analytics, and intelligent decision support systems.

Course Objectives

To understand the foundational principles of Cognitive Computing and its relevance to Project Management
To explore various Cognitive Computing tools and techniques used in automating Project Management tasks
To apply machine learning algorithms for predictive project analytics
To analyse and interpret Cognitive Computing-generated insights for improved decision-making
To optimise project workflows and resource management using Cognitive Computing technologies
To comprehend ethical considerations in deploying Cognitive Computing solutions in Project Management

Upon completing this course, delegates will have acquired the knowledge and skills necessary to implement and optimise Cognitive Computing-driven Project Management practices, making them invaluable assets in their professional fields.

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What’s included in this Cognitive Computing Training?

World-Class Training Sessions from Experienced Instructors
Cognitive Computing Certificate
Digital Delegate Pack

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Not sure which course to choose?

Speak to a training expert for advice if you are unsure of what course is right for you. Give us a call on 01344203999 or Enquire.

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Artificial Intelligence & Machine Learning FAQs

What is Artificial Intelligence and Machine Learning?

Artificial Intelligence and Machine Learning involve creating systems that can perform tasks typically requiring human intelligence, such as problem-solving, learning from data, and making decisions with minimal human intervention.

What are the benefits of obtaining an Artificial Intelligence and Machine Learning Certification?

Obtaining an Artificial Intelligence and Machine Learning Certification enhances career prospects, validates technical expertise, increases earning potential, and demonstrates a strong understanding of AI concepts, tools, and practical applications.

Are there any prerequisites for Attending Artificial Intelligence and Machine Learning Courses?

The prerequisites for the Artificial Intelligence and Machine Learning Courses are based on the course specifications and the target group of professionals it serves. Check the respective course page of the course that you are planning to take to know about its prerequisites.

Do you provide self-paced AI And Machine Learning Courses?

The Knowledge Academy provides flexible self-paced training for this Artificial Intelligence and Machine Learning Courses. Self-paced training is beneficial for individuals who have an independent learning style and wish to study at their own pace and convenience.

What are the levels of difficulty for these Machine Learning & AI Courses?

The course is designed to be accessible to all levels, making it suitable for both beginners and experienced professionals. It covers foundational concepts while offering in-depth insights into personal and organisational growth strategies.

What is the duration of the Artificial Intelligence and Machine Learning Course?

The duration of these Artificial Intelligence and Machine Learning Courses varies. Please visit our course pages for specific information.

Is prior coding knowledge required for this Artificial Intelligence Course Online?

Prior coding knowledge is beneficial but not always essential, as the course is designed to accommodate various skill levels, offering foundational concepts alongside practical guidance to support all delegates.

What is included in these Artificial Intelligence and Machine Learning Courses?

In these Artificial Intelligence and Machine Learning Courses, delegates will have intensive training with our experienced instructors, a digital delegate pack consisting of important notes related to this course, and a certificate after course completion.

Who should attend this Machine Learning (ML) & Artificial Intelligence (AI) course?

These Artificial Intelligence and Machine Learning Courses is ideal for data professionals, IT specialists, software developers, and anyone interested in understanding or pursuing a career in Machine Learning and Artificial Intelligence.

What kind of jobs can I expect based on a Machine Learning and Artificial Intelligence Course?

Completing a Machine Learning and Artificial Intelligence course can lead to roles such as data scientist, machine learning engineer, AI specialist, research analyst, or business intelligence developer.

Do you provide corporate training for Management Training Courses?

Yes, we provide corporate training for this course, tailored to fit your organisation’s requirements.

Do you offer 24/7 support for the Machine Learning and Artificial Intelligence Course?

Yes, The Knowledge Academy offers 24/7 support via phone & email before attending, during, and after the course. Our customer support team is available to assist and promptly resolve any issues you may encounter.

How popular is the AI and Machine learning Certification in the United Kingdom?

The popularity of these AI and Machine Learning Certification Courses in the United Kingdom has surged significantly in recent years. Between 2017 and 2022, UK university registrations in AI courses increased by 453%, reflecting a growing interest in the field. This trend aligns with the broader adoption of AI technologies across various sectors, leading to a heightened demand for skilled professionals. Consequently, obtaining certifications in AI and Machine Learning has become increasingly valuable for individuals seeking to enhance their career prospects in the UK's evolving job market.

How can I register for the AI and Machine Learning Training Courses?

To register for the Artificial Intelligence and Machine Learning Training, visit The Knowledge Academy's website, navigate to the course page, and click on the registration button. Fill in the required details, select your preferred schedule, and complete the payment process.

How long are the Machine Learning and AI Certification valid for?

Machine Learning and AI certifications are generally valid for a lifetime, allowing individuals to showcase their expertise without the need for renewal or re-certification over time.

Can I access the materials from multiple devices?

Yes, you can access the course materials from multiple devices, allowing you to study and review content on various platforms such as laptops, tablets, or smartphones, providing flexibility and convenience in managing your learning experience.

How will be the future demand for professionals certified in AI and machine learning?

The future demand for professionals certified in AI and machine learning is projected to be exceptionally strong in the United Kingdom. As industries increasingly integrate AI technologies, roles such as AI engineers, data scientists, and machine learning specialists are becoming highly sought after.

What are the best Artificial Intelligence & Machine Learning courses in the United Kingdom?

Please see our Artificial Intelligence & Machine Learning courses available in the United Kingdom

Which is the best training institute/provider of Artificial Intelligence & Machine Learning in the United Kingdom?

The Knowledge Academy is the Leading global training provider for Artificial Intelligence & Machine Learning.

What is the cost/training fees for Artificial Intelligence & Machine Learning in the United Kingdom

The training fees for Artificial Intelligence & Machine Learning in the United Kingdom starts from £1995

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