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MACHINE LEARNING ARCHITECT DIPLOMA

There are 4 Tracks for the Machine Learning Architect course (Deep Learning Programmer, Deep Learning Engineer, Machine Learning/Deep Learning Architect and Machine Learning/Deep Learning Architect Master). Each stage of the journey delivers 40-50 hours of courses + multimodal content and an additional 10-12 Practice Labs, Certification Pre/Assessments.

NLP for ML with Python: NLP Using Python & NLTK

NLP for ML with Python: Advanced NLP Using spaCy & Scikit-learn

Linear Algebra and Probability: Fundamentals of Linear Algebra

Linear Algebra & Probability: Advanced Linear Algebra

Linear Regression Models: Introduction to Linear Regression

Linear Regression Models: Building Simple Regression Models with Scikit Learn and Keras

Linear Regression Models: Multiple and Parsimonious Linear Regression

Linear Regression Models: An Introduction to Logistic Regression

Linear Regression Models: Simplifying Regression and Classification with Estimators

Computational Theory: Language Principle & Finite Automata Theory

Computational Theory: Using Turing, Transducers, & Complexity Classes

Model Management: Building Machine Learning Models & Pipelines

Model Management: Building & Deploying Machine Learning Models in Production

Bayesian Methods: Bayesian Concepts & Core Components

Bayesian Methods: Implementing Bayesian Model and Computation with PyMC

Bayesian Methods: Advanced Bayesian Computation Model

Reinforcement Learning: Essentials

Reinforcement Learning: Tools & Frameworks

Math for Data Science & Machine Learning

Building ML Training Sets: Introduction

Building ML Training Sets: Preprocessing Datasets for Linear Regression

Building ML Training Sets: Preprocessing Datasets for Classification

Linear Models & Gradient Descent: Managing Linear Models

Linear Models & Gradient Descent: Gradient Descent and Regularization

Final Exam: ML Programmer

ML Programming with Python

Getting Started with Neural Networks: Biological & Artificial Neural Networks

Getting Started with Neural Networks: Perceptrons & Neural Network Algorithms

Building Neural Networks: Development Principles

Building Neural Networks: Artificial Neural Networks Using Frameworks

Training Neural Networks: Implementing the Learning Process

Training Neural Networks: Advanced Learning Algorithms

Improving Neural Networks: Neural Network Performance Management

Improving Neural Networks: Loss Function & Optimization

Improving Neural Networks: Data Scaling & Regularization

ConvNets: Introduction to Convolutional Neural Networks

ConvNets: Working with Convolutional Neural Networks

Convolutional Neural Networks: Fundamentals

Convolutional Neural Networks: Implementing & Training

Convo Nets for Visual Recognition: Filters & Feature Mapping in CNN

Convo Nets for Visual Recognition: Computer Vision & CNN Architectures

Fundamentals of Sequence Model: Artificial Neural Network & Sequence Modeling

Fundamentals of Sequence Model: Language Model & Modeling Algorithms

Build & Train RNNs: Neural Network Components

Build & Train RNNs: Implementing Recurrent Neural Networks

ML Algorithms: Multivariate Calculation & Algorithms

ML Algorithms: Machine Learning Implementation Using Calculus & Probability

DL Programming with Python

Final Exam: DL Programmer

Predictive Modeling: Predictive Analytics & Exploratory Data Analysis

Predictive Modeling: Implementing Predictive Models Using Visualizations

Predictive Modelling Best Practices: Applying Predictive Analytics

Planning AI Implementation

Automation Design & Robotics

ML/DL in the Enterprise: Machine Learning Modeling, Development, & Deployment

ML/DL in the Enterprise: Machine Learning Infrastructure & Metamodel

Enterprise Services: Enterprise Machine Learning with AWS

Enterprise Services: Machine Learning Implementation on Microsoft Azure

Enterprise Services: Machine Learning Implementation on Google Cloud Platform

Architecting Balance: Designing Hybrid Cloud Solutions

Enterprise Architecture: Architectural Principles & Patterns

Enterprise Architecture: Design Architecture for Machine Learning Applications

Architecting Balance: Hybrid Cloud Implementation with AWS & Azure

Refactoring ML/DL Algorithms: Techniques & Principles

Refactoring ML/DL Algorithms: Refactor Machine Learning Algorithms

Architecting ML/DL Apps with Python

Final Exam: ML Engineer

Applied Predictive Modeling

Implementing Deep Learning: Practical Deep Learning Using Frameworks & Tools

Implementing Deep Learning: Optimized Deep Learning Applications

Applied Deep Learning: Unsupervised Data

Applied Deep Learning: Generative Adversarial Networks and Q-Learning

Advanced Reinforcement Learning: Principles

Advanced Reinforcement Learning: Implementation

ML/DL Best Practices: Machine Learning Workflow Best Practices

ML/DL Best Practices: Building Pipelines with Applied Rules

Research Topics in ML and DL

Deep Learning with Keras

Architecting Advanced ML/DL Apps with Python

Final Exam: ML Architect

Course Fee: £995 / €995 Incl. VAT

You will receive immediate access to your courses upon registration and course purchase. Our on-demand cloud based training courses are accessible on a computer, laptop, tablet/smartphone for a period of 12 months. You will need to obtain 70% and above to receive your Certificate. Assessments may be retaken at no additional cost. 

Meet your Instructor:

Charles Robinson
Instructor: Technology and Development

Meet your Mentor:

Carl Mullin
Mentor: Business/Technology and Developer

  • 24/7 Access, 365 Days
  • Mobile Compatible
  • 1:1 Mentor Certification exams
  • Labs - CompTIA, Cisco, CEH, CodeX
  • 3-6 Months Payment Plan
  • Excellent Student Support
  • Award Winning Training
  • 100% Pass/Course Mastery Certificate
  • Discounted CompTIA Exam Vouchers
  • 12 Months Subscription
  • Free Official Exam Preps

Quick View Of Our Platform:

OR

GET STARTED FROM £49.00 PER MONTH - UNLIMITED ACCESS TO FULL IT LIBRARY

Choose a plan. Complete the 3 step enrolment process, start training today!

GET STARTED FROM £49.00 PER MONTH - UNLIMITED ACCESS TO FULL IT LIBRARY

Choose a plan. Complete the 3 step enrolment process, start training today!

Unlimited access to all courses£49

FULL IT SKILLS LIBRARY

ONE-ON-ONE MENTOR

PRACTICE LABS

E-BOOKS

MOBILE COMPATIBLE

CERTIFICATE

BUY NOW

Unlimited access to all courses£65

FULL IT SKILLS LIBRARY

ONE-ON-ONE MENTOR

PRACTICE LABS

E-BOOKS

MOBILE COMPATIBLE

CERTIFICATE

BUY NOW

Unlimited access to all courses£79

FULL IT SKILLS LIBRARY

ONE-ON-ONE MENTOR

PRACTICE LABS

E-BOOKS

MOBILE COMPATIBLE

CERTIFICATE

BUY NOW

REQUEST A FREE 5 DAY TRIAL, NO CREDIT CARD REQUIRED!

There are 4 Tracks for the Machine Learning Architect course (Deep Learning Programmer, Deep Learning Engineer, Machine Learning/Deep Learning Architect and Machine Learning/Deep Learning Architect Master). Each stage of the journey delivers 40-50 hours of courses + multimodal content and an additional 10-12 Practice Labs, Certification Pre/Assessments.

NLP for ML with Python: NLP Using Python & NLTK

NLP for ML with Python: Advanced NLP Using spaCy & Scikit-learn

Linear Algebra and Probability: Fundamentals of Linear Algebra

Linear Algebra & Probability: Advanced Linear Algebra

Linear Regression Models: Introduction to Linear Regression

Linear Regression Models: Building Simple Regression Models with Scikit Learn and Keras

Linear Regression Models: Multiple and Parsimonious Linear Regression

Linear Regression Models: An Introduction to Logistic Regression

Linear Regression Models: Simplifying Regression and Classification with Estimators

Computational Theory: Language Principle & Finite Automata Theory

Computational Theory: Using Turing, Transducers, & Complexity Classes

Model Management: Building Machine Learning Models & Pipelines

Model Management: Building & Deploying Machine Learning Models in Production

Bayesian Methods: Bayesian Concepts & Core Components

Bayesian Methods: Implementing Bayesian Model and Computation with PyMC

Bayesian Methods: Advanced Bayesian Computation Model

Reinforcement Learning: Essentials

Reinforcement Learning: Tools & Frameworks

Math for Data Science & Machine Learning

Building ML Training Sets: Introduction

Building ML Training Sets: Preprocessing Datasets for Linear Regression

Building ML Training Sets: Preprocessing Datasets for Classification

Linear Models & Gradient Descent: Managing Linear Models

Linear Models & Gradient Descent: Gradient Descent and Regularization

Final Exam: ML Programmer

ML Programming with Python

Getting Started with Neural Networks: Biological & Artificial Neural Networks

Getting Started with Neural Networks: Perceptrons & Neural Network Algorithms

Building Neural Networks: Development Principles

Building Neural Networks: Artificial Neural Networks Using Frameworks

Training Neural Networks: Implementing the Learning Process

Training Neural Networks: Advanced Learning Algorithms

Improving Neural Networks: Neural Network Performance Management

Improving Neural Networks: Loss Function & Optimization

Improving Neural Networks: Data Scaling & Regularization

ConvNets: Introduction to Convolutional Neural Networks

ConvNets: Working with Convolutional Neural Networks

Convolutional Neural Networks: Fundamentals

Convolutional Neural Networks: Implementing & Training

Convo Nets for Visual Recognition: Filters & Feature Mapping in CNN

Convo Nets for Visual Recognition: Computer Vision & CNN Architectures

Fundamentals of Sequence Model: Artificial Neural Network & Sequence Modeling

Fundamentals of Sequence Model: Language Model & Modeling Algorithms

Build & Train RNNs: Neural Network Components

Build & Train RNNs: Implementing Recurrent Neural Networks

ML Algorithms: Multivariate Calculation & Algorithms

ML Algorithms: Machine Learning Implementation Using Calculus & Probability

DL Programming with Python

Final Exam: DL Programmer

Predictive Modeling: Predictive Analytics & Exploratory Data Analysis

Predictive Modeling: Implementing Predictive Models Using Visualizations

Predictive Modelling Best Practices: Applying Predictive Analytics

Planning AI Implementation

Automation Design & Robotics

ML/DL in the Enterprise: Machine Learning Modeling, Development, & Deployment

ML/DL in the Enterprise: Machine Learning Infrastructure & Metamodel

Enterprise Services: Enterprise Machine Learning with AWS

Enterprise Services: Machine Learning Implementation on Microsoft Azure

Enterprise Services: Machine Learning Implementation on Google Cloud Platform

Architecting Balance: Designing Hybrid Cloud Solutions

Enterprise Architecture: Architectural Principles & Patterns

Enterprise Architecture: Design Architecture for Machine Learning Applications

Architecting Balance: Hybrid Cloud Implementation with AWS & Azure

Refactoring ML/DL Algorithms: Techniques & Principles

Refactoring ML/DL Algorithms: Refactor Machine Learning Algorithms

Architecting ML/DL Apps with Python

Final Exam: ML Engineer

Mentoring Machine Learning Architect

Applied Predictive Modeling

Implementing Deep Learning: Practical Deep Learning Using Frameworks & Tools

Implementing Deep Learning: Optimized Deep Learning Applications

Applied Deep Learning: Unsupervised Data

Applied Deep Learning: Generative Adversarial Networks and Q-Learning

Advanced Reinforcement Learning: Principles

Advanced Reinforcement Learning: Implementation

ML/DL Best Practices: Machine Learning Workflow Best Practices

ML/DL Best Practices: Building Pipelines with Applied Rules

Research Topics in ML and DL

Deep Learning with Keras

Architecting Advanced ML/DL Apps with Python

Final Exam: ML Architect

You will receive immediate access to your courses upon registration and course purchase. Our on-demand cloud based training courses are accessible on a computer, laptop, tablet/smartphone for a period of 12 months. You will need to obtain 70% and above to receive your Certificate. Assessments may be retaken at no additional cost. 

  • 24/7 Access, 365 Days
  • Mobile Compatible
  • 1:1 Mentor Certification exams
  • Labs - CompTIA, Cisco, CEH, CodeX
  • 3-6 Months Payment Plan
  • Excellent Student Support
  • Award Winning Training
  • 100% Pass/Course Mastery Certificate
  • Discounted CompTIA Exam Vouchers
  • 12 Months Subscription
  • Free Official Exam Preps

Quick View Of Our Platform:

Course Fee: £995 / €995 Incl. VAT

OR

GET STARTED FROM £49.00 PER MONTH - UNLIMITED ACCESS TO FULL IT LIBRARY

Choose a plan. Complete the 3 step enrolment process, start training today!

GET STARTED FROM £49.00 PER MONTH - UNLIMITED ACCESS TO FULL IT LIBRARY

Choose a plan. Complete the 3 step enrolment process, start training today!

Unlimited access to all courses£49

FULL IT SKILLS LIBRARY

ONE-ON-ONE MENTOR

PRACTICE LABS

E-BOOKS

MOBILE COMPATIBLE

CERTIFICATE

BUY NOW

Unlimited access to all courses£65

FULL IT SKILLS LIBRARY

ONE-ON-ONE MENTOR

PRACTICE LABS

E-BOOKS

MOBILE COMPATIBLE

CERTIFICATE

BUY NOW

Unlimited access to all courses£79

FULL IT SKILLS LIBRARY

ONE-ON-ONE MENTOR

PRACTICE LABS

E-BOOKS

MOBILE COMPATIBLE

CERTIFICATE

BUY NOW

REQUEST A FREE 5 DAY TRIAL, NO CREDIT CARD REQUIRED!

Your Quick Course Guide

Certification: Machine Learning Architect

Study Time: 12 Months to complete 370 hours eg study 1 hour per day to complete your course in 12 months |study Full Time or Part Time

Vendor: IT Academy

Provider: IT Academy

Student support: One-on-One Mentoring

Pre-requisite: Data Analytics to Data Scientist

Assessment: Multimodal/Assessments

Resources: Laptop, Tablet or Smartphone & Internet Connection

Expertise Level: Intermediate

Salary Indicator

SALARY PROJECTION

Average
salary after
completing

Junior
£32k
Average Salary
You can earn
£50k
Senior
£79k

High

Source: Payscale

£50k

You can earn an average
of £50,000 a year

What’s Included

Replace-trainer-img
  • 24/7 Access, 365 Days
  • Mobile Compatible
  • 1:1 Mentor Certification exams
  • Labs - CompTIA, Cisco, CEH, CodeX
  • 3-6 Months Payment Plan
  • Excellent Student Support
  • Award Winning Training
  • 100% Pass/Course Mastery Certificate
  • Discounted CompTIA Exam Vouchers
  • 12 Months Subscription
  • Free Official Exam Preps

Reviews:

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WHAT SETS US APART:

  • Official Partnerships

Partners with IT certification vendors CompTIA, Microsoft & Skillsoft who are the global leaders in online learning

  • We are IT Experts

With over 13 years experience, we have 13 000+ students graduate through IT Academy

  • Award Winning

Latest-in-Market Online Cloud Based Courses delivered via Video, Quizzes, Virtual labs & Mentoring

  • Virtual Practice Labs

Learn, Practice writing Code with instant feedback in a Live Environment

  • Live Mentoring

Free One-on-One Live Mentoring with Certified Industry Experts

  • Practice Tests

Take Practice Tests designed to mimic the actual exam

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