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AI and Machine Learning on Cloud

Learn to build, train, and deploy machine learning models on cloud platforms like Amazon Web Services, Microsoft Azure, and Google Cloud Platform with hands-on AI training.

Live Online: Total 24 Hours - 6 hours / Per Day - Total: 4 Days ( Jun 2 , 3 , 4, 5, 2026) Live Online Self Paced In Person AI & Machine Learning on Cloud Training
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Overview

The AI and Machine Learning on Cloud Certification Training is designed to help professionals build practical skills in developing and deploying intelligent solutions using cloud platforms. It combines core machine learning concepts with cloud technologies to enable scalable, efficient, and real-time AI applications.

This course covers key areas such as data preprocessing, model building, evaluation, and deployment, along with hands-on experience using cloud services from Amazon Web Services, Microsoft Azure, and Google Cloud Platform. Participants will learn how to leverage cloud infrastructure to handle large datasets, automate workflows, and deploy machine learning models at scale.

With a strong focus on real-world applications and project-based learning, this training prepares learners to apply AI and machine learning techniques to solve business problems, optimize processes, and drive innovation in cloud-driven environments.

Course Outline

  1.  Introduction to AI, Machine Learning, and Deep Learning 
  2.  Key concepts and real-world applications 
  3.  Overview of cloud platforms: Amazon Web Services, Microsoft Azure, Google Cloud Platform
  4.  Benefits of AI/ML on cloud 
  1.  Basic Python concepts for ML (overview) 
  2.  Introduction to NumPy and Pandas 
  3.  Data types and structures 
  4.  Working with datasets 
  1.  Data cleaning and transformation 
  2.  Handling missing values and outliers 
  3.  Feature engineering basics 
  4.  Preparing data for model training 
  1.  Supervised vs unsupervised learning 
  2.  Regression and classification models 
  3.  Introduction to Decision Trees and K-Means clustering 
  4.  Model evaluation techniques 
  5.  Overfitting, underfitting, and optimization 
  1.  Building ML models using Python (conceptual + demo) 
  2.  Training and testing models 
  3.  Model validation techniques 
  4.  Using notebooks for experimentation 
  1.  Overview of AI/ML services in cloud platforms 
  2.  Using pre-built AI services (Vision, NLP APIs) 
  3.  Introduction to managed ML platforms 
  4.  Deploying models on cloud (high-level demo) 
  1.  Model deployment concepts (APIs/endpoints) 
  2.  Introduction to MLOps pipelines 
  3.  Monitoring and improving model performance 
  4.  Automation basics 
  1.  Introduction to Generative AI and LLMs 
  2.  Use cases (chatbots, content generation, automation) 
  3.  Overview of AI tools and APIs 
  1.  Predictive analytics 
  2.  Recommendation systems 
  3.  NLP and chatbot applications 
  4.  Mapping business problems to AI solutions 
  1.  Build a simple ML solution 
  2.  Apply preprocessing + model + evaluation 
  3.  Simulate deployment on cloud 
  4.  Presentation and feedback 

Who Should Attend

  1. Beginners looking to start a career in AI, Machine Learning, and Cloud
  2.  Data analysts and aspiring data scientists wanting to learn ML on cloud platforms 
  3.  Software developers interested in building AI-powered applications 
  4.  Cloud engineers working with platforms like Amazon Web Services, Microsoft Azure, or Google Cloud Platform
  5.  IT professionals transitioning into AI, ML, or data-driven roles 
  6.  Business analysts and professionals interested in AI-driven decision-making 
  7.  Students and graduates exploring careers in AI, data science, and cloud computing 
  8.  Professionals looking to upskill in machine learning, MLOps, and Generative AI
  9.  Anyone interested in building and deploying AI solutions in cloud environments

Certification

The AI and Machine Learning on Cloud Certification Training validates your ability to build, train, and deploy machine learning models using modern cloud platforms such as Amazon Web Services, Microsoft Azure, and Google Cloud Platform.

Upon successful completion, participants receive a course completion certification from GraspSkill that demonstrates practical knowledge in data preprocessing, model development, cloud-based deployment, and MLOps fundamentals.

AI & Machine Learning on Cloud Training

Benefits

  1. uild strong foundational and practical skills in AI, Machine Learning, and cloud technologies
  2.  Gain hands-on experience with cloud platforms like Amazon Web Services, Microsoft Azure, and Google Cloud Platform
  3.  Learn to develop, train, and deploy machine learning models in real-world environments 
  4.  Understand how to scale AI solutions using cloud infrastructure 
  5.  Develop knowledge of MLOps and model deployment workflows 
  6.  Explore modern AI trends including Generative AI and real-world use cases 
  7.  Enhance career opportunities in roles such as ML Engineer, Data Scientist, and AI Specialist 
  8.  Increase earning potential in high-demand AI and cloud domains 
  9.  Gain a competitive edge in a rapidly evolving technology landscape 
  10.  Build a practical portfolio with hands-on projects and capstone work 
  11.  Improve problem-solving skills using data-driven and AI-based approaches 
  12.  Strengthen your ability to apply AI solutions to real business challenges 
  13.  Earn a recognized certification to validate your AI and cloud expertise

About Trainer

    Certified DevOps Engineer and automation expert with over 10 years of experience in infrastructure management, configuration automation, and cloud orchestration using Ansible, Jenkins, and Docker.

Learning Outcomes

  1. Understand core concepts of Artificial Intelligence, Machine Learning, and Deep Learning
  2.  Gain practical knowledge of working with data, including preprocessing and feature engineering 
  3.  Build and evaluate machine learning models for regression, classification, and clustering 
  4.  Use basic Python tools (NumPy, Pandas) for data handling and analysis 
  5.  Apply model training, validation, and optimization techniques 
  6.  Understand how to deploy machine learning models on cloud platforms like Amazon Web Services, Microsoft Azure, and Google Cloud Platform
  7.  Explore cloud-based AI services such as vision, NLP, and APIs 
  8.  Learn the fundamentals of MLOps, including model deployment and monitoring 
  9.  Understand Generative AI concepts and modern AI tools 
  10.  Apply AI and ML techniques to real-world business use cases 
  11.  Build a simple end-to-end machine learning solution as part of a capstone project 
  12.  Develop the confidence to work on AI projects and transition into AI/ML roles

Student Reviews

"“The real-world use cases and cloud integration made this course stand out. It’s perfect for anyone starting in AI and ML.”"

D
Daniel Schmidt
IT Consultant, SAP | Germany

" “A well-structured course with practical examples. It helped me gain confidence in AI and cloud technologies.”"

M
Mei Lin Tan
Junior Data Analyst , Shopee | Singapore

"“This course provided a strong foundation in machine learning and cloud integration. The capstone project was a great learning experience.”"

L
Lucas Pereira
Data Scientist , Deloitte | Brazil

"“The modules on MLOps and deployment were very insightful. I now feel confident working on AI projects in cloud environments.”"

E
Emily Chen
Software Engineer, Tencent | China

Frequently Asked Questions

This course provides hands‑on instruction in Ansible, the leading automation tool for IT configuration, orchestration and deployment, helping you automate complex processes across infrastructure and application environments.

It’s ideal for DevOps engineers, system administrators, cloud engineers, IT automation specialists and software developers who want to streamline operations, reduce manual tasks and improve efficiency using automation.

You’ll learn Ansible fundamentals, playbooks, inventory management, roles and modules, configuration automation, orchestration best practices and how to integrate Ansible with CI/CD pipelines for DevOps workflows.

Basic familiarity with Linux/Unix commands and scripting helps, but the course is designed to support learners with varying skill levels, from beginners to intermediate practitioners.

Yes, this course includes practical labs and real‑world exercises so you can apply Ansible automation in realistic scenarios and build working automation projects.

Yes, upon successful completion, you will receive a certificate of completion that validates your Ansible automation skills and boosts your professional credibility.

The course is delivered through interactive sessions with expert instructors, live demonstrations, guided exercises and real‑world use cases to reinforce learning.

This training enhances your ability to automate IT processes, improves operational productivity and increases your eligibility for DevOps, automation and infrastructure engineering roles.

Recordings of live sessions are often provided, allowing you to review content later and stay aligned with the training schedule.

Yes, the Ansible course can be delivered as in‑house training for teams and organizations looking to upskill staff in automation technologies.

Yes. The online training is accessible worldwide.

Yes, there will be an assessment of 20 questions based on the training topics at the end of the course, you will have to score 75% to pass.

You will get 2 attempts to pass the test.

Group discounts are available to groups of more than three candidates. You can get up to 20% discount depending on the number of participants.

Yes, if you notify at least 24 hours in advance before the 1st class of the training and there is an availability in a different batch then you will be able to switch your start date.

Our courses are designed to provide high quality learning and outcomes that exceed expectations. If for some reason your expectations are not met. You will be given a refund in accordance with our 100% satisfaction policy.

You will receive meeting login for Zoom live classes and training materials.

All the participants will be added to WhatsApp/SMS group and email thread. You can clarify doubts at any time via WhatsApp, SMS or email.

Yes, we provide mentorship, doubt resolution and guidance for assessment preparation.

The digital certificate is issued immediately upon passing the assessment.

Live Class Schedules

Self Paced Learning

Access: Online, anytime
Certificate on completion
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Minimum 5 participants required — email us at info@graspskill.com

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Upcoming Schedules

Date Time Duration Mode Price Action
12:00 - 18:00 Kolkata (UTC+5:30) Total 24 Hours - 6 hours / Per Day - Total: 4 Days ( Jun 2 , 3 , 4, 5, 2026) Live Online $499.00 $399.00

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