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Cloud & AI Integration(ML Ops, Serverless, AI, Data Engineering in Cloud)

Course Overview

The Cloud & AI Integration course by TrainingLabs is designed for professionals who want to bridge the gap between Artificial Intelligence and modern cloud platforms. This program covers MLOps, Serverless Architecture, AI model deployment, and Cloud Data Engineering, enabling you to design, implement, and scale intelligent cloud-native applications. Through real-world projects and practical exercises, you’ll gain skills in automating ML pipelines, managing AI workflows, leveraging serverless computing for efficiency, and building robust data pipelines in the cloud. Whether you are a developer, data engineer, or aspiring AI professional, this course equips you with the expertise to thrive in today’s cloud-driven AI ecosystem.

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FAQ

Course curriculum

Requirment

  • Basic understanding of cloud computing concepts and platforms (AWS, GCP, or Azure).

  • Familiarity with programming languages, especially Python, and data handling (SQL/NoSQL).

  • Knowledge of AI/ML fundamentals (algorithms, model training, evaluation) is helpful.

  • Access to cloud environments for hands-on practice.

  • Understanding of data pipelines, ETL processes, and storage solutions.

  • Willingness to work on projects combining cloud infrastructure and AI workflows.

Outcomes

  • Design and deploy serverless applications and APIs in cloud environments.

  • Implement ML Ops pipelines to train, deploy, and monitor machine learning models efficiently.

  • Build data engineering pipelines for ingestion, processing, and analytics on cloud platforms.

  • Apply AI services like natural language processing, computer vision, and prediction APIs in production workloads.

  • Automate cloud workflows integrating data, AI models, and serverless components.

...

₹3000

₹4000
... Buy Now
  • ...

    language

     English
  • ...

    Duration

     00h 10m

  • Level

     advanced
  • ...

    Expiry period

     Lifetime
  • ...

    Certificate

     Yes
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