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Best ML on Cloud & Auto ML Course Training in Saudi Arabia

Build, train and deploy Machine Learning models using Cloud. Advance your career in this in-demand and powerful field with certification in Machine Learning on Cloud.
  • Get Trained by Trainers from ISB, IIT & IIM
  • 24 Hours of Intensive Classroom & Online Sessions
  • 60+ Hours of Practical Assignments
  • 2 Capstone Live Projects
  • AWS Certified Speciality Machine Learning Certification
machine learning on Cloud course reviews in Saudi Arabia- 360digitmg
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machine learning on Cloud course reviews in Saudi Arabia- 360digitmg
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Academic Partners & International Accreditations
  • MLOps course with Microsoft
  • MLOps course with Nasscomm
  • MLOps course with Innodatatics
  • MLOps Certification Course with SUNY
  • MLOps Course with NEF

The Machine Learning on Cloud course is designed to equip you with the necessary skills needed in this field. Even as we speak, technology is advancing making its way into the domain of Machine Learning which is a part of Artificial Intelligence. Recently machine learning in the cloud has been a boon for businesses and provides many benefits like the pay-per-use model where you pay only for space used resulting in no wasted resources and helping companies cut down on costs. With Google Cloud Platform, Microsoft Azure, and AWS companies now don’t have to worry about having a data science proficient team because now the artificial intelligence features can be functional without requiring any deep or hardcore knowledge. As businesses adopt both machine learning and cloud together, they will need individuals who know both the worlds and can provide value to the organization. The Machine Learning on Cloud Certification course will be a step towards your career growth.

ML on Cloud

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Total Duration

1 Month

machine learning on aws course pre-requisites in Saudi Arabia- 360digitmg


  • Traditional ML Algorithms & DL Algorithms
  • Programming Knowledge
  • No cloud knowledge is needed

Machine Learning on Cloud Training Overview

Learn to install Machine Learning models on the cloud in the most comprehensive program. Learn the various ML algorithms to handle large data and to derive patterns and predict results. Explore how Machine Learning models are designed, deployed, configured, and managed on the various cloud platforms. You will also learn about the various benefits of Machine learning on the cloud and also draw a comparison of machine learning services on various cloud platforms like AWS, Azure, and Google Cloud.

The course commences with an introduction to AWS and Amazon SageMaker. Learn the various benefits of Amazon SageMaker and explore all ML Algorithms in-built in SageMaker. In this course, you will also learn about Machine Learning in Azure and how its UI-based interface and predefined algorithms help in building training models. Learn ML model handling using AutoML or advanced model optimization and infuse cutting-edge AI technologies into your applications via tools like TensorFlow and TPUs while learning Google Cloud Platform. Also, explore the features of IBM Watson's cognitive computing technology. This course is designed for Data Science Enthusiasts, Statisticians, Cloud engineers, Software and IT engineers, Software Architects, etc.

Machine Learning on Cloud Learning Outcomes

Machine learning focuses on developing applications that learn from data and improves its efficiency. This course will equip students to give end-to-end packaged ML solutions for any organization. Students will learn to apply a machine-learning algorithm to categorize data and make appropriate predictions. This course prepares you to work in large organizations to meet the ML needs of the organizations. Students will also learn about machine learning and cloud computing capabilities that help resolve IT problems and how it can analyze large amounts of data with speed and agility in performance. Students will learn about AWS & Amazon SageMaker and how to handle Machine Learning Models along with working on ML frameworks available in SageMaker. In this course, you will also learn about the machine learning services provided by Microsoft Azure and how to manage data in the cloud, and how to automate the end-to-end machine learning process in the cloud. Students will also explore Google Cloud and Machine Learning wherein they will learn about the various Algorithms and Services available in GCP and how one can compute, store, and process data on Google Cloud Platform (GCP). So, if you want to soar in your career as an ML Cloud engineer join the course on Machine Learning on Cloud.

Examine the various Machine learning offering provided by various cloud services
Learn about the application and benefits of AWS, GCP, IBM Watson and Azure cloud platforms
Understand how to develop, train and deploy ML models on Cloud
Apply the various Machine Learning Algorithms to segregate data and make predictions
Explore hoe to compute, store and process data on various cloud Platforms

Block Your Time

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24 hours

Classroom Sessions

machine learning on Cloud course in Vietnam- 360digitmg

60 hours


machine learning on Cloud course in Vietnam- 360digitmg

60 hours

Live Projects

Who Should Sign Up?

  • IT Engineers
  • Data and Analytics Manager
  • Business Analysts
  • Data scientists, technology heads, decision-makers
  • Professionals with analytics knowledge
  • Professionals with industry domain experience in various areas (banking, finance, insurance, mechanical, IoT etc.)

Machine Learning on Cloud Modules

Machine Learning on Cloud is a unique program that helps you learn about machine learning capabilities in the cloud. With the adoption of cloud computing, many companies have realized that the ‘One cloud fit all’ approach doesn’t work anymore. Therefore, this course includes concepts of Machine Learning across various platforms. The course commences with the module on the introduction of AWS cloud and benefits of Amazon SageMaker and how it facilitates the building, training, and deploying of machine learning models at any scale. Then the students will learn about the Microsoft Azure Machine Learning Services and then further students will be introduced to Google Cloud Platform followed by features of cognitive computing and IBM Watson. Join this certification program if you aspire to learn the fundamentals of Machine Learning on the Cloud.

  • Introduction to Cloud Computing
  • The ML development Life Cycle
  • Automated ML
  • How automated ML works
  • Democratization of Data Science
  • Debunking automated ML myths
  • Automated ML Ecosystem
  • Automated Feature Engineering
  • Automated Model Selection and Hyperparameter Tuning
  • Automated Neural Network Architecture Selection
  • Automated Model choosing and Hyperparameter Optimization
  • Automated ML Challenges and Limitations
  • AutoML and AutoAI
  • Four levels of Automation
    • Basic Automation
    • Process Automation
    • Integration Automation
    • AI Automation
  • AutoML with Open Sources
  • TPOT – Tree-based Pipeline Optimization Tool
  • AutoML - AutoKeras
  • AutoML with Cloud Platforms
  • Amazon SageMaker
  • Notebook instances
  • Amazon SageMaker Studio
  • Amazon SageMaker - Training
  • Amazon SageMaker - Deploying
  • Amazon SageMaker - Autopilot
  • AWS ML Services
  • Rekognition
  • Polly
  • Transcribe
  • Comprehend
  • Translate
  • Textract
  • Amazon Lex
  • Introduction to Microsoft Azure ML Services
  • Pipeline Building for ML Solutions
  • Varied Machine Learning Microsoft Azure Services
  • Azure GUIs and Workspace
  • AML Studio
  • Creating your first AMLS workspace
  • Building compute to run your AutoML jobs
  • Working with data in AMLS
  • Understanding how AutoML works on Azure
  • Feature Engineering on Azure
  • Feature Extraction after Data Pre-processing
  • Building ML Pipeline Workflows using Designer
  • Building ML Models on Automated ML
  • Hyperparameter Tuning in Azure
  • Model Deployment on Azure
  • Real-Time vs Batch Scoring Services
  • Constant Real-Time Monitoring of Model Deployments
  • Introduction to GCP
  • Primer to Machine Learning in GCP
  • Services Available in GCP
  • Compute, Storage and Processing in GCP
  • Building ML Pipeline in GCP
  • Building XGBoost in GCP
  • Using Pretrained Models in GCP
  • NLP for Document Classification using AutoML NLP
  • AutoML Vision APIs for Handling Image AI Problems
  • Building a Big Data Cloud ML Engine
  • Batch Processing and Real-Time Prediction using Cloud ML Engine
  • Compute & Monitoring Options for Training the Model Jobs
  • Model Versioning of Saved Models
  • Model Deployment on GCP
  • Prediction with Service Endpoints
  • Usage of Google Cloud DialogFlow & Google Cloud Dataproc
  • IBM Watson Studio
  • IBM Watson Machine Learning architecture and services
  • Data Preparation
  • Analyzing data and building models
  • Evaluate models
  • Deploying and managing models with Watson Machine Learning
  • Defining XAI
  • The key features of XAI
  • Executive function XAI
  • Different forms and methods of XAI - Pre, During, Post
  • XAI timeline from conception to production
  • AI accountability
How we prepare you
  • Machine Learning on Cloud course with placements in Saudi Arabia
    Additional Assignments of over 60+ hours
  • Machine Learning on Cloud course with placements training in Saudi Arabia
    Live Free Webinars
  • Machine Learning on Cloud training institute with placements in Saudi Arabia
    Resume and LinkedIn Review Sessions
  • Machine Learning on Cloud course with certification in Saudi Arabia
    Lifetime LMS Access
  • Machine Learning on Cloud course with USP in Saudi Arabia
    24/7 Support
  • Machine Learning on Cloud certification with USP in Saudi Arabia
    Job Placements in Data Science fields
  • best Machine Learning on Cloud course with USP in Saudi Arabia
    Complimentary Courses
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    Unlimited Mock Interview and Quiz Session
  • best Machine Learning on Cloud training with placements in Saudi Arabia
    Hands-on Experience in Live Projects
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