NextGen IT Training

Artificial Intelligence
Artificial Intelligence

Whether it’s a chat bot that is indistinguishable from a human or a self-driving car, artificial intelligence is here. We have moved on from the days when machines would just follow algorithms, we now need them to make decisions to keep up with the pace of technology and the amount of information. In this course you’ll learn all about Artificial Intelligence.

In this course you’ll learn about types of AI, AI Techniques, Neural Networks, building AI, architectural models and design patterns.

The eLearning kit bundle provides access to a 3 Module course bundle that will be available for 1 year from the date of purchase. You can also take the on-line exam to get a Digital Badge to show your expertise in this field.

  • Module 1: Fundamental Artificial Intelligence
  • Module 2: Advanced Artificial Intelligence
  • Module 3: Artificial Intelligence Lab

Further description of the contents are included in the Details tab.


 

Intended for
Enterprise Architects, Solution Architects, Security Architects, Business Analysts and any person interested in Artificial Intelligence and its technology, uses and methods.


Pre-requisites
An understanding of IT concepts


Learning Outcomes
A comprehensive understanding of artificial intelligence, its uses and applicability to business as well as understanding of techniques and concepts. The following topics are some of the ones that are covered during the course:

  • AI Types (Narrow, General, Symbolic, Non-Symbolic, etc.)
  • Common AI Learning Approaches and Algorithms
  • Supervised Learning, Unsupervised Learning, Continuous Learning
  • Heuristic Learning, Semi-Supervised Learning, Reinforcement Learning
  • Common AI Functional Designsl
  • Computer Vision, Pattern Recognition
  • Robotics, Natural Language Processing (NLP)
  • Speech Recognition, Natural Language Understanding (NLU)
  • Frictionless Integration, Fault Tolerance Model Integration
  • Neural Networks, Neurons, Layers, Links, Weights
  • Understanding AI Models and Training Models and Neural Networks
  • Understanding how Models and Neural Networks Exist
  • Loss, Hyperparameters, Learning Rate, Bias, Epoch
  • Activation Functions (Sigmoid, Tanh, ReLU, Leaky RelU, Softmax, Softplus)
  • Neuron Cell Types 
  • Fundamental and Specialized Neural Network Architectures
  • Perceptron, Feedforward, Deep Feedforward, AutoEncoder, Recurrent, Long/Short Term Memory
  • Deep Convolutional Network, Extreme Learning Machine, Deep Residual Network
  • Support Vector Machine, Kohonen Network, Hopfield Network
  • Generative Adversarial Network, Liquid State Machine
  • How to Build an AI System (Step-by-Step)
  • Common AI System Design Principles and Common AI Project Best Practices

And more…


Note: All quoted pricing is excluding GST. For customers in Australia GST will be added during the check-out process.

Blockchain Architect
Blockchain Architect

Blockchain is more than just BitCoin or any other Crypto Currency, it’s an append-only general ledger that is consensus driven. It has been used to provide solutions in identity, security, health records, finance, logistics, insurance and many more. In this course you’ll learn the essential business drivers and the technology of blockchain as well as the mechanisms and inner workings.

The eLearning kit bundle provides access to a 3 Module course bundle that will be available for 1 year from the date of purchase. You can also take the on-line exam to get a Digital Badge to show your expertise in this field.

  • Module 1: Fundamental Blockchain
  • Module 2: Blockchain Technology and Architecture
  • Module 3: Blockchain Technology Lab

Further description of the contents are included in the Details tab.


 

Intended for
Enterprise Architects, Solution Architects, Security Architects, Business Analysts and any person interested in Blockchain and its technology, uses and methods.


Pre-requisites
An understanding of IT concepts


Learning Outcomes
A comprehensive understanding of blockchain, its uses and applicability to business as well as understanding of techniques and concepts. The following topics are some of the ones that are covered during the course:

  • Drivers, Benefits and Challenges of Blockchain
  • Blockchain Value Propositions
  • Industrial Impacts of Blockchain on Different Industry Verticals
  • Fundamental Components of a Blockchain Architecture
  • Blocks, Nodes, Verifiers/Verification and Chaining
  • Consensus and Group Consensus
  • Public vs. Private / Permissionless vs. Permissioned Blockchains
  • Coins, Tokens, Smart Contracts
  • Basics of Cryptography Algorithms (Crypto Hashing)
  • Centralized Ledger vs Decentralized Ledger
  • Fundamental Blockchain Security Considerations
  • Blockchain and Cryptocurrency
  • DevOps for Blockchain Development
  • Blockchain Availability, Scalability and Anonymity
  • On-Chain and Off-Chain Transactions
  • Public and Private Blockchain Types
  • Smart Contract, Distributed Ledgers and Consensus
  • Proof of Work (PoW) and Proof of Stake (PoS)
  • Delegated Proof of Stake (DPoS) and Leased Proof of Stake (LPoS)
  • Proof of Importance (PoI) and Proof of Elapsed Time (PoET)
  • Decentralized Blockchain Solution Architectures
  • Smart Contracts Drill-Down and Data Sovereignty
  • Transaction Signing, Cryptography and Digital Signatures with Blockchain
  • Blockchain Integrity
  • Cloud Computing and Blockchain, Blockchain-as-a-Service
  • Blockchain Security and IoT

And more…


 

Note: All quoted pricing is excluding GST. For customers in Australia GST will be added during the check-out process.

DevOps Specialist
DevOps Specialist

A key requirement of successful DevOps enablement is a common understanding of the concepts and approach across various teams. In this vendor-neutral course you will learn the enablers of DevOPs as well as the approaches and design patterns that need to be followed for success. Recommended for anyone who is working with or interested in DevOps and automation.

In this course you’ll learn about CI/CD Pipelines, automated configuration management, Infrastructure-as-Code, Policy-as-Code and more.

The eLearning kit bundle provides access to a 3 Module course bundle that will be available for 1 year from the date of purchase. You can also take the on-line exam to get a Digital Badge to show your expertise in this field.

  • Module 1: Fundamental DevOps
  • Module 2: DevOps in Practice
  • Module 3: DevOps Lab

Further description of the contents are included in the Details tab.


 Intended for

IT Professionals, Business Analysts, Solution architects, Enterprise Architects, Infrastructure Architects, systems administrators, security professionals, release managers, change managers, Directors, Project Managers, Systems Engineers


 Pre-requisites

An understanding of IT fundamentals including infrastructure, software and testing and the software delivery lifecycle is recommended.


 Learning Outcomes

A sound understanding of the concepts, techniques and approaches to successful DevOps in any organisation. The following primary topics are covered:

  • DevOps Rapid Delivery and Scalability
  • DevOps Collaborative Practices
  • Continuous Integration (CI) and Continuous Delivery (CD)
  • Automated Configuration Management and
  • Infrastructure-as-Code (IaC) and Policy-as-Code (PaC)
  • Value Stream Mapping and Preparing for Failure
  • Kanban and the Deming Cycle
  • DevOps Platforms and Toolchains
  • Measuring DevOps (Metrics and Monitoring)
  • DevOps and Microservices
  • Agile and Integrated Pipelines with DevOps
  • DevOps and Organizational integration
  • DevOps Roles and Responsibilities and Managing People through Change
  • Creating and managing Deployment Pipelines
  • Continuous Integration (CI) Drill-Down
  • Continuous Change and Managing Change
  • Applying the DevOps Lifecycle and Stages
  • Managing Data Flow and Version Control
  • Deployment and Release Management

And more…


Note: All quoted pricing is excluding GST. For customers in Australia GST will be added during the check-out process.

Internet of Things (IoT) Architect
Internet of Things (IoT) Architect

These days everything is connected to the internet. From our watches to our fridges. Most utilities companies now offer IoT enabled services and meters. We can control the electrical devices in our homes using the assistants on our mobiles. IoT is used by all industries from logistics, manufacturing and utilities to sports associations. Have you been tasked with building an IoT capability for your organisation or just want to understand what IoT is? This three day course will teach you the why, how and what of IoT.


The eLearning kit bundle provides access to a 3 Module course bundle that will be available for 1 year from the date of purchase. You can also take the on-line exam to get a Digital Badge to show your expertise in this field.

  • Module 1: Fundamental IoT
  • Module 2: IoT Technology and Architecture
  • Module 3: IoT Technology Lab

Further description of the contents are included in the Details tab.


Intended for
IT Professionals, Business Analysts, Solution architects, Enterprise Architects, Infrastructure Architects, systems administrators, security professionals, Systems Engineers


 Pre-requisites
An understanding of IT fundamentals including infrastructure, software and networking is recommended.


Learning Outcomes
A comprehensive understanding of IoT, its uses and applicability to business as well as understanding of techniques and concepts. The following topics are some of the ones that are covered during the course:

  • Understanding IoT Business Models and Design Processes
  • Any X-Point of View and IoT Characteristics
  • Intelligence model and Hybrid Architecture
  • Scalability and Unprecedent Events
  • Communication protocols and Localization
  • Everything-as-a-Service (XaaS)
  • IoT in Different Domains and Industries
  • IoT Enabling Technologies
  • Communication and Networking Technologies
  • IoT Software Technologies and Algorithms
  • IoT and Big Data, Machine Learning and Artificial Intelligence
  • IoT High Level Architecture Overview
  • Node, Network, Communication and Access Layers
  • IoT Security and Privacy Challenges
  • IoT Business, Functional and Technology Architectures
  • IoT Application, Protocol, Data and Analytics Architectures
  • IoT Device Specifications, Types, and Access
  • IoT Device Data Store and Transfer Capabilities
  • IoT Data Collection Mechanics
  • SQL RDBMS, NoSQL and Time Series Data
  • Human-to-Machine, Machine-to-Human, Machine-to-Machine Interactions
  • IoT Communication Channels and Protocol Technologies
  • IoT Device or Service Discovery
  • Open Hybrid, Shazam and Chrips
  • IoT Data Link Layer Protocols and OSI

And more…


 

Note: All quoted pricing is excluding GST. For customers in Australia GST will be added during the check-out process.

Machine Learning Specialist
Machine Learning Specialist

Let’s face it, with the amount of data that is being generated today, it is impossible for any human to analyse in a timely manner. The variety of data also presents the problem that by the time we understand the data and formulate a way to measure its importance, we are already behind. This is where machine learning comes in.

In this course you’ll learn what Machine Learning is, the specific learning approaches, languages and models as well as system design and Neural Networks.

The eLearning kit bundle provides access to a 3 Module course bundle that will be available for 1 year from the date of purchase. You can also take the on-line exam to get a Digital Badge to show your expertise in this field.

  • Module 1: Fundamental Machine Learning
  • Module 2: Advanced Machine Learning
  • Module 3: Machine Learning Technology Lab

Further description of the contents are included in the Details tab.


Intended for
Data Scientists, BI Specialists, Data Architects, Solution Architects and other IT Professionals that are responsible for working with and analysing data.


Pre-requisites
An understanding of Data Analytics or analytical mathematics and IT systems is recommended.


Learning Outcomes
A comprehensive understanding of Machine Learning, its concepts, uses and techniques. The following topics are some of the ones that are covered during the course:

  • Understanding Machine Learning and Deep Learning
  • Benefits and Challenges of Machine Learning
  • Machine Learning Languages
  • Machine Learning and Data Science, Artificial Intelligence
  • Machine Learning for Recommendation Systems and Match Making
  • Natural Language Processing (NLP) and Search Engines
  • Supervised, Unsupervised and Semi-Supervised Learning
  • Open Source and Proprietary Machine Learning Frameworks
  • Machine Learning Libraries and Scalability Dimensions
  • Machine Learning Architectures and Algorithms
  • Data Processing with Machine Learning
  • Decision Tree Algorithm and Classification and Regression Tree (CART)
  • Iterative Dichotomiser 3 (ID3) and C4.5/C5.0
  • Chi-squared Automatic Interaction Detection (CHAID), Decision Stump and M5
  • Conditional Decision Trees
  • Linear, Logistic, Stepwise and Ordinary Least Squares Regression (OLSR)
  • Multivariate Adaptive Regression Splines (MARS) and Locally Estimated
  • Scatterplot Smoothing (LOESS)
  • Understanding Machine Learning Algorithms
  • Machine Learning System Design
  • Classification
  • Clustering
  • Rule Systems
  • Mapping, Projection Pursuit and Multidimensional Scaling) (MDS)
  • Linear, Mixture, Quadratic and Flexible Discriminant Analyses
  • Constructing Hypotheses using Instance-based Models
  • Building Artificial Neural Network Constructs with Deep Learning
  • Constructing Machine Learning Models using Neural Networks

And more…


 

Note: All quoted pricing is excluding GST. For customers in Australia GST will be added during the check-out process.

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