close

close

Thank you for your enquiry!

One of our training experts will be in touch shortly to go over your training requirements.

close

close

Press esc to close

close close

Back to course information

Thank you for your enquiry!

One of our training experts will be in touch shortly to go overy your training requirements.

close close

Thank you for your enquiry!

One of our training experts will be in touch shortly to go over your training requirements.

Artificial Intelligence & Machine Learning courses

Online Instructor-led (1 days)

Online Self-paced (8 hours)

Introduction to Artificial Intelligence Course Outline

  • What is Artificial Intelligence (AI)?
  • Application Areas of AI
  • Artificial Intelligence and Related Fields
  • The Foundation of AI – Machine Learning
  • Agents and Environments
  • The Concept of Rationality
  • Fuzzy Logic Systems
  • Overview of Robotics
  • Natural Language Processing
  • Neural Networks 

Show moredown

Who should attend this Artificial Intelligence Training Course?

: Anyone who wishes to gain an understanding of the basic concepts of AI can attend this course. This training course is well-suited for:

  • Management Participants
  • Students at Beginner Level
  • Technical and Non-technical Participants

Prerequisites

No prerequisites are required for this course.

Introduction to Artificial Intelligence Course Overview

Artificial Intelligence (AI) is a collection of techniques inspired by the goal of understanding and executing intelligent behaviour. AI is a field that is actively and continuously growing and changing. By attending this Artificial Intelligence (AI) course, the delegates will gain knowledge regarding every aspect of AI.

This course aims to equip you with an intensive knowledge of AI applications and related individual fields within Artificial Intelligence (AI).

Show moredown

What's included in this Artifical Intelligence Training Course?

  • The Knowledge Academy's Artificial Intelligence course Manual
  • Experienced Instructor
  • Certificate
  • Refreshments

Show moredown

Online Instructor-led (1 days)

Online Self-paced (8 hours)

Deep Learning with TensorFlow Course Outline

  • Introduction to TensorFlow
    • Tensors
    • Two Computation Phrases
    • A Computational Graph with TensorBoard
    • Variables
    • Linear Regression
    • Operations
  • Installation of TensorFlow
  • Artificial Neural Network
  • Activate Functions
  • Deep Learning Techniques
    • Convolutional Neural Networks
    • Recurrent Neural Networks
  • Deep Learning Applications
  • Computing Gradients
  • Single-layer and Multi-layer Perceptron
  • Back Propagation with TensorFlow

Show moredown

Who should attend this Deep Learning Training Course?

This training course is designed for engineers who wish to get expertise in using the TensorFlow. It is recommended for the following professionals:

  • Data Scientists
  • Software Engineers
  • Data Analysts

Prerequisites

Basic knowledge about Python programming and machine learning can help the delegate to learn this course easily. 

Deep Learning with TensorFlow Course Overview

TensorFlow is an open source software library of Google for implementing the Deep Learning – Artificial Neural Network. It works through layers of nodes to determine the correct outcome. This deep learning with tensorflow training course will provide the delegate with skills in deep learning techniques using tensorflow.

The participants will learn the use of Google’s library TensorFlow in order to solve the various real-world problems. By the completion of this course, the delegate will be able to implement algorithms, build and manage artificial neural networks.

Show moredown

What's included in this Deep Learning Training Course?

  • The Knowledge Academy’s Deep Learning with TensorFlow Training Course Manual
  • Experienced Instructor
  • Completion Certificate
  • Refreshments

Show moredown

Online Instructor-led (1 days)

Online Self-paced (8 hours)

Machine Learning Course Outline

  • Machine learning - Introduction
  • Importance of Machine Learning and its Techniques
  • Data Preprocessing
  • Machine Learning Mathematics
  • Supervised Learning
  • Classification
    • Support Vector Machines
    • Discriminant Analysis
    • Naive Bayes
    • Nearest Neighbour
  • Regression
    • Linear Regression and GLM
    • SVR and GPR
    • Decision Tree
  • Neural Networks
  • Unsupervised Learning
  • Clustering
    • K-Means, K-Medoids, Fuzzy and C-Means
    • Hierarchical
    • Gaussian Mixture
    • Hidden Markov Model
  • Deep Learning - Introduction

Show moredown

Who should attend this Machine Learning Training Course?

This training course is beneficial for the delegates who wish to get proficient in machine learning. Professionals who are best suited for this course:

  • Graduates who wish to build a career in machine learning
  • Analytics managers
  • Information architects who wish to gain proficiency in machine learning algorithms
  • Experienced Professionals who would like to gain more insights in their fields
  • Developers intending to become a machine learning engineer or data scientist

Prerequisites

It is recommended that the delegates should possess some basic knowledge of python programming, statistics fundamentals and high school mathematics for this course.

 

Machine Learning Course Overview

Machine learning is an application of artificial intelligence (AI). It is typically concerned with the computer programs that enable computers to evolve behaviours based on empirical data. Today, Machine Learning becomes a key technique to solve various problems in multiple areas such as computational finance and biology, NLP, and energy production.

This Machine learning training course will assist the delegate to gain mastery over machine learning. This training course guides the delegates through the different concepts of machine learning such as neural networks, algorithms, clustering, supervised and unsupervised learning. By the completion of the training course, the delegate will gain expertise in creating algorithms and applications in machine learning.

Machine Learning is one of the leading career choices these days. The demand for machine learning is increasing day by day, so in the upcoming years, the companies are expected to increase their investments in this technology.

Show moredown

What's included in this Machine Learning Training Course?

  • The Knowledge Academy’s Machine Learning Training Course Manual
  • Experienced Instructor
  • Completion Certificate
  • Refreshments

Show moredown

Online Instructor-led (1 days)

Online Self-paced (8 hours)

Artificial Intelligence (AI) for DevOps Course Outline

  • Introduction to Artificial Intelligence (AI)
  • Overview of DevOps
  • Role of AI in DevOps
  • Basics of Artificial Intelligence and DevOps Automation
  • Artificial Intelligence in DevOps Quality Assurance and Control
  • Selecting Tools of AI for DevOps Automation
  • AI for Team Coordination
  • Using AI for Continuous Integration, Delivery, and Deployment
  • Impact of AI on DevOps Culture
  • Improving DevOps with Artificial Intelligence
  • Applying Artificial Intelligence to DevOps Toolchain
  • Moving DevOps Team into AI
  • Artificial Intelligence Future with DevOps

Show moredown

Prerequisites

There are no prerequisites for this course.

Who should attend?

This course is well suited for:

  • Application Developers
  • System Administrators
  • Security Engineers

Artificial Intelligence (AI) for DevOps Course Overview

Artificial Intelligence (AI) has an all-encompassing relationship with DevOps. Automating routine and repeatable actions is a fundamental facet of DevOps to help improve performance and productivity.

Artificial Intelligence reduces the operational complexities found in DevOps due to the highly distributed nature of the toolsets. AI can improve the automation quotient in DevOps by minimising the need for human involvement across processes.

This Artificial Intelligence for DevOps Training course is designed to provide knowledge of how AI is used in DevOps. During this training, delegates will become familiarised with AI and DevOps automation, including the use of AI for quality assurance and control. You will learn how AI impacts DevOps culture in general as well as its uses in delivery and deployment. Post completion of this course, you will be able to apply AI to the DevOps toolchain.

 

Show moredown

What's included?

  • The Knowledge Academy's Artificial Intelligence (AI) for DevOps Course Manual
  • Experienced Instructor
  • Certificate

Show moredown

Online Instructor-led (2 days)

Online Self-paced (16 hours)

Natural Language Processing (NLP) Fundamentals with Python Course Outline

  • Introduction to Natural Language Processing (NLP)
  • Overview of Python
  • Text Wrangling and Cleansing
    • Overview of Text Wrangling and Text Cleansing
    • Sentence Splitter
    • Tokenisation
    • Stemming
    • Lemmatisation
  • POS Tagging
    • Stanford Tagger
    • Sequential Tagger
    • Brill Tagger
    • Machine Learning Based Tagger
  • Parsing Structure in Text
  • Natural Language Processing Applications
  • Text Classification
    • Naive Bayes
    • Decision Trees
    • Stochastic Gradient Descent
    • Logistic Regression
    • Support Vector Machines
    • Text Clustering - K-means
  • Using NLTK with other Python Libraries
    • NumPy
    • SciPy
    • Pandas
    • Matplotlib
  • Text Mining at Scale

Show moredown

Who should attend this NLP course?

Anyone who wishes to gain knowledge regarding Natural Language Processing can attend this course. This course is ideal for:

  • Data Scientists
  • Developers who wish to become a Data Scientist
  • Python Professionals
  • Programmers and Data Analysts
  • Analytics Managers who are leading a team of Analysts

Prerequisites

Basic knowledge of Python is recommended.

Natural Language Processing (NLP) Fundamentals with Python Course Overview

Natural Language Processing (NLP) is a powerful skill that helps you extract important information from text data. The NLP Fundamentals with Python Training course guides delegates how to auto-summarise the text by using machine learning. Delegates will also acquire knowledge about how to build the text classifier using the Naive Bayes algorithm.

During this course, delegated will learn how to use the Natural Language Toolkit (NLTK) to pre-process raw text. You will master how to use NLTK with other Python Libraries such as SciPy, matplotlib, NumPy, and pandas.

Show moredown

What's included in this NLP training course?

  • Delegate pack consisting of course notes and exercises
  • Manual
  • Experienced Instructor
  • Refreshments

Show moredown

Online Instructor-led (1 days)

Online Self-paced (8 hours)

Introduction to Artificial Intelligence (AI)

  • Aim and Purpose
  • Scope of Research
  • AI within the Corporate Context

Theoretical Framework

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

Methodology

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

Results – Surveys

  • Artificial Intelligence
  • Project Management
  • Organisational Business

Results – Interviews

  • Project Management
  • Artificial Intelligence

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

Show moredown

Prerequisites

There are no prerequisites for this course, anyone with an interest in AI or the way that AI can support project management should attend.

Audience

This course is designed for Project Managers with an interest in developing their awareness of AI and how AI can support their projects, operations, and efficient management

Artificial Intelligence (AI) is a collection of techniques inspired by the goal of understanding and executing intelligent behaviour. By attending this Artificial Intelligence (AI) for Project Managers course, delegates will gain an insight into project management fundamentals, SWOT analysis, methodologies, etc.

By attending this course, delegates will gain extensive knowledge of how Artificial Intelligence (AI) can be used within the corporate context. This training course will help project managers to add values in different phases of the project lifecycle. On completion of this course, delegates will learn to build AI Systems and will also learn how to implement AI in their organisation.

 

Show moredown

  • Delegate pack consisting of course notes and exercises
  • Manual
  • Experienced Instructor

Show moredown

Online Instructor-led (1 days)

Online Self-paced (8 hours)

Artificial Intelligence (AI) for Business Analysts Course Outline

Introduction to Artificial Intelligence (AI)

Use of Artificial Intelligence (AI)

  • In Banking
  • In Finance
  • In Investment

Artificial Intelligence (AI) and its Relevance to Banking

Artificial Intelligence (AI) Applications in the Banking Industry

  • AML Pattern Detection
  • Chatbots
  • Algorithmic Trading
  • Fraud Detection

Impact of Artificial Intelligence on Investing

AI and its Impact on Finance Industry

Future Evolution of Business Analyst

  • How Will Business Analysis Evolve with Artificial Intelligence?

Hybrid Roles for Future Business Analyst

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

How Artificial Intelligence (AI) Change the Face of Business?

Co-Existence of Artificial Intelligence and Business Analysis

Show moredown

Prerequisites

There are no prerequisites for this course.

Who should attend?

This course is designed for Business Analysts.

Artificial Intelligence (AI) for Business Analysts Course Overview

Artificial Intelligence (AI) is an area of computer science that focuses on the creation of intelligent machines that work and react like humans.

This Artificial Intelligence (AI) for Business Analysts training is designed to provide knowledge of how AI can help and enhance the skills of business analysts in making significant decisions for business. Delegates will learn the use of Artificial Intelligence (AI) in different fields like banking, finance, and investment and its impact on these.

During this course, delegates will be familiarised with different AI applications including AML pattern detection, Chatbots, Algorithmic Trading, and fraud detection. They will also acquire knowledge of various hybrid roles for future business analysts. On completion of this course, delegates will know how Artificial Intelligence (AI) can improve business processes.

Show moredown

What's included?

  • The Knowledge Academy's Artificial Intelligence (AI) for Business Analysts Course Manual
  • Experienced Instructor
  • Certificate

Show moredown

Online Instructor-led (1 days)

Online Self-paced (8 hours)

Artificial Intelligence (AI) for IT Professionals Course Outline

Introduction to Artificial Intelligence (AI)

Building Blocks of AI

  • Machine Learning
  • Deep Learning

AI vs. Machine Learning vs. Deep Learning

How to train AI?

Implementing AI in an Organisation

  • Identify AI Opportunities
  • Develop an AI Roadmap
  • Identify AI Solutions
  • Identify Data Requirements

AI Use Cases in Information Management

Case Studies

(Human) Supervision of AI

Implementation Areas of AI

  • Voice Recognition
  • Natural Language Generation (NLG)
  • Virtual Assistants
  • Cognitive Computing
  • Computer Vision
  • Recommendation Systems
  • Natural Language Processing
  • Neural Networks
  • Robotic Process Automation
  • Machine Learning Platform
  • Predictive Analysis
  • Biometric Recognition
  • Image Analysis
  • Deep Learning Platforms
  • Quantum Computing
  • Decision Making and Management
  • Hardware Optimisation

Show moredown

Prerequisites 

There are no prerequisites for attending this course. However, basic knowledge of statistics and programming will be beneficial.

Who should attend?

This course is designed for IT Professionals.

Artificial Intelligence (AI) for IT Professionals Course Overview

Artificial Intelligence (AI) is the science of creating machines that work intelligently. It is accomplished by analysing how the human brain functions during problem-solving and uses the results as the base of developing intelligent software and systems.

This Artificial Intelligence course for IT Professionals will provide delegates with an in-depth understanding of AI and its applications. Delegates will learn about the building blocks of AI and the differences between AI, machine learning, and deep learning.

In addition, this 1-day course will also provide delegates with knowledge on how to train AI. Delegates will become familiarised with AI use cases in information management and human supervision of AI. They will also learn how to implement AI in an organisation. By the end of this course, you will have learned about various implementation areas for AI including voice recognition, computer vision, neural networks, robotic process automation, and more.

Show moredown

What's included

  • The Knowledge Academy's Artificial Intelligence (AI) for IT Professionals Training Course Manual
  • Experienced Instructor
  • Certificate

Show moredown

Online Instructor-led (1 days)

Online Self-paced (8 hours)

Deep Learning Course Outline

Machine Learning Basics

Introduction to Deep Learning

  • Importance of Deep Learning
  • How Deep Learning Works
  • Difference between Deep Learning and Machine Learning

Artificial Neural Networks

Deep Neural Networks

  • Feedforward Networks
  • Convolutional Networks
  • Recurrent and Recursive Networks

Linear Algebra

Probability

  • Random Variables
  • Probability Distributions
  • Marginal Probability
  • Conditional Probability
  • Chain Rule of Conditional Probabilities
  • Bayes’ Rule

Autoencoders

Computational Graphs

Monte Carlo Methods

Deep Generative Model

  • Boltzmann Machines

Applications

Libraries and Frameworks

Show moredown

Prerequisites

It is recommended that delegates possess some basic knowledge of Python, linear algebra and probability.

Who should attend this Deep Learning Training?

This course is intended for individuals who wish to learn how deep learning works and who may wish to develop their own applications using deep learning techniques. 

Deep Learning Course Overview

Deep Learning is used for building and training neural networks – layers of decision-making nodes inspired by the human brain.

It is a subset of machine learning (ML) where artificial neural networks learn from large amounts of data. It allows machines to solve complicated problems even when using diverse, unstructured, and interconnected data sets.

This Deep Learning Training course will provide you with a basic understanding of the linear algebra, probabilities, and algorithms used in deep neural networks. After learning the difference between deep learning and machine learning, delegates will gain in-depth knowledge of the different types of neural networks such as feedforward, convolutional, and recursive. At the end of this course, delegates will be able to build complex models that help machines to solve real-world problems.

Show moredown

What's included in this Deep Learning Course?

  • The Knowledge Academy’s Deep Learning Training Manual
  • Experienced Instructor
  • Completion Certificate

Show moredown

Online Instructor-led (1 days)

Online Self-paced (8 hours)

Neural Networks with Deep Learning Training Course Outline

Introduction to Deep Learning

  • Introduction to Neural Networks
  • Supervised Learning with Neural Networks

Neural Networks Fundamentals

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

Shallow Neural Networks

  • Representation of a Neural Network
  • Computing the Output of a Neural Network
  • Vectorised Implementation
  • Activation Functions
  • Derivatives of Activation Functions
  • Gradient Descent for Neural Networks
  • Backpropagation Intuition

Deep Neural Networks

  • Deep L-layer Neural Network
  • Forward Propagation
  • Deep Representations
  • Building Blocks
  • Backward Propagation
  • Difference Between Parameters and Hyperparameters

Show moredown

Prerequisites

There are no prerequisites for this course. However, some experience with the Python programming language would be beneficial.

Audience

Anyone who wants to learn about neural networks and deep learning can attend this course.

Neural Networks with Deep Learning Training Course Overview

Neural Networks are a set of algorithms designed to identify patterns. These are developed to imitate the human brain. Neural networks translate sensory data through labelling or clustering raw input and machine perception. These networks identify numerical patterns that are stored in vectors. All the real-world data, including text, images, or sound, must be translated into these numerical patterns. Neural networks can be thought of as a clustering and classification layer on top of the data stored and managed.

The Knowledge Academy’s Neural Networks with Deep Learning Training course will provide delegates with an understanding of deep learning and neural networks. Delegates will be familiarised with basic concepts of neural networks such as binary classification, logistic regression, derivatives, and vectorisation.

During this 1-day training course, delegates will be introduced to Python and Jupyter/IPython notebooks. Delegates will learn about shallow neural networks, including vectorised implementation, activation functions, and backpropagation intuition. In addition, delegates will also gain knowledge on the concepts of deep neural networks involving deep L-layer neural network, deep representations, and forward and backward propagation.

Show moredown

  • Delegate pack consisting of course notes and exercises
  • Manual
  • Experienced Instructor
  • Refreshments

Show moredown

Online Instructor-led (1 days)

Online Self-paced (8 hours)

Cognitive Computing Training​ Course Outline

Introduction to Cognitive Computing

  • Working of Human Brain
  • Artificial Neural Networks
  • Symbolic Representation of Facts and Rules
  • Symbolic Models for Natural Language Processing (NLP)

Basics of Linguistics

  • Phonology
  • Morphology
  • Syntax
  • Semantics
  • Pragmatics

Cognitive Computing – Practical Applications

Introduction to Machine Learning

  • Supervised and Unsupervised Learning
  • Linear Regression
  • Backpropagation Neural Networks
  • Feature Engineering

TensorFlow for Implementing Deep Neural Networks

  • Installing TensorFlow
  • Convolutional Deep Learning Networks for Text Classification

Tools and Techniques – Natural Language Processing

  • Overview of spaCy NLP Library
  • spaCy for Assigning Part of Speech Tags
  • spaCY for Entity Recognition
  • Overview of OpenNLP Library and Installation Notes

Show moredown

Prerequisites

There are no prerequisites for attending this course.

Audience

Anyone interested in learning how cognitive computing works with machine learning, deep neural networks, and NLP can attend this course.

 

Cognitive Computing Training​ Course Overview

Cognitive Computing simulates the thought processes of humans. It uses deep-learning or self-learning algorithms backed by natural language processing, big data, and artificial intelligence. Cognitive Computing solves complicated problems characterised by uncertainty and ambiguity. It synthesises data from different information sources, while weighing context and conflicting evidence to advise the best possible answers.

This Cognitive Computing Training is designed to equip delegates with in-depth knowledge on how Cognitive Computing works. Delegates will learn about artificial neural network and symbolic representation of facts and rules. During this 1-day training course, delegates will become familiarised with the basics of linguistics. In addition, delegates will gain knowledge of supervised learning, unsupervised learning, and linear regression. Post completion of this training, delegates will be able to use spaCy for assigning part of speech tags and entity recognition.

Show moredown

  • Delegate pack consisting of course notes and exercises
  • Manual
  • Experienced Instructor
  • Refreshments

Show moredown

Online Instructor-led (1 days)

Online Self-paced (8 hours)

Recommendation System Training Course Outline

Introduction to Recommender Systems

  • What is Recommender System?
  • Goals of Recommender System
  • Basic Models of Recommender System
  • Domain-Specific Challenges

Collaborative Recommendation

  • User and Item Based Neighbor Recommendation
  • Model-Based and Preprocessing-Based Approaches
  • Practical Approaches and Systems

Knowledge-Based Recommendation

  • Knowledge Representation and Reasoning
  • Interacting with Constraint-Based Recommenders
  • Interacting with Case-Based Recommenders

Hybrid Recommendation Approaches

  • Opportunities for Hybridisation
  • Monolithic Hybridisation Design
  • Parallelised Hybridisation Design
  • Pipelined Hybridisation Design

Recommender Systems Explanations

  • Constraint-Based Recommenders
  • Case-Based Recommenders
  • Collaborative Filtering Recommenders

Evaluating Recommender Systems

  • Properties of Evaluation Research
  • Popular Evaluation Designs
  • Evaluation of Historical Datasets
  • Alternate Evaluation Designs

Show moredown

Prerequisites

There are no prerequisites to attend this course.

Audience

Anyone wishes to have a comprehensive knowledge of Recommendation system can attend this course. This course is well-suited for:

  • Machine Learning Engineers
  • Data engineers and Scientists
  • Data Analysts

Recommendation System Training​ Course Overview

A Recommendation system is an extensive class of web applications comprising predicting the user responses to the options. It is a data filtering tool that analyses historical data for predicting what users will be interested in and create accurate recommendations. This system is mostly used in social media, e-commerce platforms, and content-based services. This Recommendation System Training is designed to equip delegates with a knowledge of all the fundamental techniques in the recommender system.

In this Recommendation System Training, delegates will learn about basic concepts of recommendation systems. Delegates will get an understanding of model-based and preprocessing-based approaches. In addition, delegates will learn how to interact with constraint and case-based recommenders.

During this 1-day training, delegates will gain extensive knowledge of hybrid recommendation approaches. This course will introduce delegates to explanations in constraint, case, and collaborative based recommenders. Post completion of this course, delegates will be able to evaluate recommender systems.

Show moredown

  • Delegate pack consisting of course notes and exercises
  • Manual
  • Experienced Instructor

Show moredown

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 +44 1344 203999 or Enquire.

Package deals

Our training experts have compiled a range of course packages to compliment a variety of categories in order to help fast track your career. The packages consist of the best possible qualifications in each industry and allows you to purchase multiple courses at a discounted rate.

Swipe for more. Don’t miss out!

What our customers are saying

Frequently asked questions

FAQ's

This depends on the training course you choose. The introduction to Artificial Intelligence and Deep Learning Training with TensorFlow takes 1 day, and the Machine Learning Training Course and NLP fundamentals with Python Essential Training lasts 2 days.
We offer Artificial Intelligence and Machine Learning training courses in locations all over the UK, as well as abroad. We make it easy to find a training venue near you!
The Knowledge Academy’s Artificial Intelligence and Machine Learning training courses include the courseware, a certificate, an experienced instructor and, refreshments.
Prerequisites vary according to the course. Please see each course for details.
The Knowledge Academy is the Leading global training provider in the world for Artificial Intelligence & Machine Learning.
The price for Artificial Intelligence & Machine Learning certification in Philippines starts from $1169.

Why we're the go to training provider for you

icon

Best price in the industry

You won't find better value in the marketplace. If you do find a lower price, we will beat it.

icon

Trusted & Approved

We are accredited by PeopleCert on behalf of AXELOS

icon

Many delivery methods

Flexible delivery methods are available depending on your learning style.

icon

High quality resources

Resources are included for a comprehensive learning experience.

barclays Logo
deloitte Logo
Thames Water Logo

"Really good course and well organised. Trainer was great with a sense of humour - his experience allowed a free flowing course, structured to help you gain as much information & relevant experience whilst helping prepare you for the exam"

Joshua Davies, Thames Water

santander logo
bmw Logo
Google Logo
Shell Logo

"...the trainer for this course was excellent. I would definitely recommend (and already have) this course to others."

Diane Gray, Shell

Looking for more information on Artificial Intelligence & Machine Learning