Gujarat, Memnagar, Ahmedabad - Classroom T1

Memnagar Fire Station, Sarvottam Nagar Society, Memnagar, Ahmedabad, india, 380052

The classroom is located near 5-6km of Memnagar Fire Station, Sarvottam Nagar Society, Memnagar, Ahmedabad, Gujarat 380052. Some of the nearby localities are: Roop Nagar, Sushil Nagar Society and Saurabh Society.

Details about Classroom

All the centres have state of the art audio/video webinars/seminars and presentation solutions. We also provide one-on-one Training sessions upon request. We encourage our students and delegates to bring along their own laptops during the exercises, as this helps in retaining the examples and handson exercises in their systems for post-session reference. 

For Sales Enquires and Meetings

All our centres have batches running on weekdays and weekends hence, please note that, in most cases, usually we are not able to organise ad hoc sales meetings, especially on our classrooms as they are all occupied with ongoing training sessions . Please contact us by e-mail or phone at least one day earlier to make an appointment with one of our consultants at our corporate offices.

Explore Our Courses

Kubeflow

 35 Hours
This instructor-led, live training in Gujarat (online or onsite) is aimed at developers and data scientists who wish to build, deploy, and manage machine learning workflows on Kubernetes. By the end of this training, participants will be able to:
  • Install and configure Kubeflow on premise and in the cloud using AWS EKS (Elastic Kubernetes Service).
  • Build, deploy, and manage ML workflows based on Docker containers and Kubernetes.
  • Run entire machine learning pipelines on diverse architectures and cloud environments.
  • Using Kubeflow to spawn and manage Jupyter notebooks.
  • Build ML training, hyperparameter tuning, and serving workloads across multiple platforms.
Read more...

Kubeflow Fundamentals

 28 Hours
This instructor-led, live training in Gujarat (online or onsite) is aimed at developers and data scientists who wish to build, deploy, and manage machine learning workflows on Kubernetes. By the end of this training, participants will be able to:
  • Install and configure Kubeflow on premise and in the cloud.
  • Build, deploy, and manage ML workflows based on Docker containers and Kubernetes.
  • Run entire machine learning pipelines on diverse architectures and cloud environments.
  • Using Kubeflow to spawn and manage Jupyter notebooks.
  • Build ML training, hyperparameter tuning, and serving workloads across multiple platforms.
Read more...

Kubeflow on AWS

 28 Hours
This instructor-led, live training in Gujarat (online or onsite) is aimed at engineers who wish to deploy Machine Learning workloads to an AWS EC2 server. By the end of this training, participants will be able to:
  • Install and configure Kubernetes, Kubeflow and other needed software on AWS.
  • Use EKS (Elastic Kubernetes Service) to simplify the work of initializing a Kubernetes cluster on AWS.
  • Create and deploy a Kubernetes pipeline for automating and managing ML models in production.
  • Train and deploy TensorFlow ML models across multiple GPUs and machines running in parallel.
  • Leverage other AWS managed services to extend an ML application.
Read more...

Kubeflow on Azure

 28 Hours
This instructor-led, live training in Gujarat (online or onsite) is aimed at engineers who wish to deploy Machine Learning workloads to Azure cloud. By the end of this training, participants will be able to:
  • Install and configure Kubernetes, Kubeflow and other needed software on Azure.
  • Use Azure Kubernetes Service (AKS) to simplify the work of initializing a Kubernetes cluster on Azure.
  • Create and deploy a Kubernetes pipeline for automating and managing ML models in production.
  • Train and deploy TensorFlow ML models across multiple GPUs and machines running in parallel.
  • Leverage other AWS managed services to extend an ML application.
Read more...

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Testimonials (1)

I enjoyed participating in the Kubeflow training, which was held remotely. This training allowed me to consolidate my knowledge for AWS services, K8s, all the devOps tools around Kubeflow which are the necessary bases to properly tackle the subject. I wanted to thank Malawski Marcin for his patience and professionalism for training and advice on best practices. Malawski approaches the subject from different angles, different deployment tools Ansible, EKS kubectl, Terraform. Now I am definitely convinced that I am going into the right field of application.

Guillaume Gautier - OLEA MEDICAL | Improved diagnosis for life TM

Course - Kubeflow

Upcoming Courses

Kubeflow on Azure

2025-06-30 09:30
28 hours
Gujarat, Memnagar, Ahmedabad - Classroom T1
337,322 INR (Online)
363,322 INR (Classroom)

Kubeflow on AWS

2025-07-14 09:30
28 hours
Gujarat, Memnagar, Ahmedabad - Classroom T1
421,322 INR (Online)
447,322 INR (Classroom)

Kubeflow on AWS

2025-07-28 09:30
28 hours
Gujarat, Memnagar, Ahmedabad - Classroom T1
421,322 INR (Online)
447,322 INR (Classroom)

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Kubeflow Consulting
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