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.
Level
Advanced
Duration
8 weeks



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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.
Working professional who is carrying more then 10 years of industry experience.
Access to updated presentation decks shared during live training sessions.
E-book provided by TechPratham. All rights reserved.
Module-wise assignments and MCQs provided for practice.
Daily Session would be recorded and shared to the candidate.
Live projects will be provided for hands-on practice.
Expert-guided resume building with industry-focused content support.
Comprehensive interview preparation with real-time scenario practice.
Cloud Ai
Course CurriculumIntroduction to Cloud AI
Understand the basics and importance of AI in the cloud.
Cloud AI Platforms Overview
Explore leading Cloud AI platforms such as Google Cloud AI, Microsoft Azure AI, and AWS AI. Understand their unique features and use cases.
Machine Learning in the Cloud
Understand how to build, train, and deploy machine learning models using cloud services with minimal infrastructure complexity.
Natural Language Processing (NLP) in Cloud AI
Learn how Cloud AI handles NLP tasks like sentiment analysis, entity recognition, and chatbots using prebuilt APIs.
Computer Vision in Cloud AI
Explore image recognition, object detection, and video analysis capabilities provided by cloud-based AI services.
Speech & Audio AI Services
Leverage Cloud AI for speech-to-text, text-to-speech, and voice recognition in applications such as virtual assistants and transcription tools.
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Cloud Ai
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IT Professionals
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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.

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