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CoursesLearn AiCloud Ai
Learn Ai
Cloud Ai
With Techpratham, you can learn how to build, train, and deploy AI models on the best cloud platforms. Learn how to use cloud-based machine learning, AI services, and scalable deployment from start to finish.
5/5(4,890 Reviews)

Level

Advanced

Duration

8 weeks

What is Cloud Ai?
This Techpratham course teaches you the basics and more advanced uses of Cloud AI, so you can use Google Cloud AI, Microsoft Azure AI, and AWS AI. You will look into cloud-native AI tools for automation, computer vision, natural language processing, and machine learning. The course mixes theory with hands-on projects in real cloud environments. By the end, you'll know how to make, train, and safely deploy scalable AI models in the cloud.
Training Plan

About trainer

Working professional who is carrying more then 10 years of industry experience.

Decks

The candidate will get access to the presentation taken-up during the session.

Notes

Consolidated notes in word document.

Assignments

Assignments for every module will be covered.

MCQs

MCQs for every module covered in the session would be provided.

Video Recording

Daily Session would be recorded and shared to the candidate.

Dumps for Certification

We will provide dumps for the certification exam, which will help you to prepare for the exam.

Updated Content

We provide Generative AI Driven content By experts.

Projects

3 Live Projects will be provided for practice.

Cloud Ai Course Curriculum
.

Introduction to Cloud AI
Section 1

Understand the basics and importance of AI in the cloud.
Cloud Computing Overview
What is Cloud AI?
Key Cloud AI Providers (AWS, Azure, GCP)
Benefits of Cloud AI
Use Cases in Industry
.

Cloud AI Platforms Overview
Section 2

Explore leading Cloud AI platforms such as Google Cloud AI, Microsoft Azure AI, and AWS AI. Understand their unique features and use cases.
Google Cloud AI
Microsoft Azure AI
AWS AI Services
Platform Comparison
.

Machine Learning in the Cloud
Section 3

Understand how to build, train, and deploy machine learning models using cloud services with minimal infrastructure complexity.
ML Model Training
Cloud ML Pipelines
Deployment Services
AutoML
.

Natural Language Processing (NLP) in Cloud AI
Section 4

Learn how Cloud AI handles NLP tasks like sentiment analysis, entity recognition, and chatbots using prebuilt APIs.
Sentiment Analysis
Entity Recognition
Translation APIs
Conversational AI
.

Computer Vision in Cloud AI
Section 5

Explore image recognition, object detection, and video analysis capabilities provided by cloud-based AI services.
Image Recognition
Object Detection
OCR (Text Extraction)
Video Intelligence
.

Speech & Audio AI Services
Section 6

Leverage Cloud AI for speech-to-text, text-to-speech, and voice recognition in applications such as virtual assistants and transcription tools.
Speech-to-Text
Text-to-Speech
Voice Recognition
Real-time Transcription
.

Cloud AI for Data Analytics
Section 7

Integrate Cloud AI with big data platforms for predictive analytics, anomaly detection, and business intelligence insights.
Predictive Analytics
Anomaly Detection
Data Visualization
Business Insights
.

AI Model Deployment & MLOps
Section 8

Master cloud-based model deployment, scaling, and monitoring with MLOps frameworks for production-ready AI systems.
Model Deployment
Continuous Training
Monitoring & Logging
MLOps Pipelines
.

Cloud AI Integration with Applications
Section 9

Learn how to integrate Cloud AI services with enterprise applications, mobile apps, and IoT devices for smarter solutions.
API Integration
Mobile AI Apps
IoT + AI
Enterprise AI
.

Security, Compliance & Responsible AI
Section 10

Understand the principles of AI governance, ethical AI usage, and compliance with privacy and security standards in cloud environments.
AI Governance
Data Privacy
Compliance Standards
Responsible AI
Key Projects
Cloud Ai
AI-Powered Document Analyzer
Create a cloud-based NLP tool that can pull out, summarize, and sort information from a lot of documents. Use Google Cloud AI or Azure Cognitive Services to set it up.
Image Recognition System on Cloud
Use AWS Rekognition or Google Vision API to make a computer vision app that can find objects or flaws in pictures. Use cloud infrastructure that can grow with your needs to deploy it.
Customer Support Automation Agent
Create a cloud-based AI chatbot that uses natural language processing (NLP), sentiment analysis, and a search of a knowledge base. This project shows how to use cloud APIs and automation tools to deploy something in real time.

Cloud Ai – Associate Training Program

Category
Associate
Exam Name:
Cloud Ai – Associate
Exam Code:
N.A.
Exam Duration:
N.A.
Exam Format:
N.A.
Passing Score:
N.A.
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Frequently Asked Questions (FAQs)

Which cloud platform should I focus on for Cloud AI – AWS, Azure, or Google Cloud?

It depends on what you want to do with your career. AWS is popular with businesses, Azure works well with Microsoft services, and Google Cloud AI is great for new AI and ML ideas. This course gives you an overview of all three so you can choose one to focus on later.

What is Cloud AI?

Cloud AI refers to artificial intelligence services delivered through cloud platforms like AWS, Azure, and Google Cloud. TechPratham’s training helps learners understand Cloud AI applications and how to deploy AI solutions at scale.

How does Cloud AI work?

It uses cloud-based infrastructure to provide AI models, APIs, and tools accessible over the internet. TechPratham explains step-by-step how to build, train, and deploy AI models in the cloud.

What are the advantages of Cloud AI?

Cloud AI offers scalability, cost-effectiveness, faster deployment, and easy integration. TechPratham trains learners to maximize these benefits for enterprise and business solutions.

Which platforms provide Cloud AI services?

Major providers include AWS AI/ML, Microsoft Azure AI, and Google Cloud AI. TechPratham ensures learners get hands-on experience across multiple cloud platforms.

What skills will I gain from Cloud AI training?

You’ll gain skills in machine learning deployment, AI APIs, cloud infrastructure, and automation. TechPratham provides real-world projects to ensure learners build practical expertise.

Do I need prior AI or cloud knowledge to learn Cloud AI?

Basic understanding helps but is not mandatory. TechPratham starts from fundamentals and gradually advances to complex Cloud AI use cases.

How is Cloud AI used in industries?

It is applied in healthcare, finance, retail, manufacturing, and IT for automation and analytics. TechPratham aligns its training with industry projects to prepare learners for real-world applications.

Is Cloud AI cost-effective for businesses?

Yes, businesses can scale AI solutions without heavy infrastructure costs. TechPratham guides learners on optimizing resources and minimizing expenses while using Cloud AI.

What is the career scope after Cloud AI training?

Career opportunities include AI Engineer, Cloud Developer, Data Scientist, and ML Engineer. TechPratham supports learners with skill development and placement opportunities.

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