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Data Science Practitioner

Certification & Training Course

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Data Science Practitioner
Certificate & Training Course

Why The DataTech Labs

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Hours of Training
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Students
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Industry Experts
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Top Ranked Programs

Course Curriculum

  • create an Azure Machine Learning workspace
  • configure workspace settings
  • manage a workspace by using Azure Machine Learning studio
  • select Azure storage resources
  • register and maintain datastores
  • create and manage datasets
  • determine the appropriate compute specifications for a training workload
  • create compute targets for experiments and training
  • configure Attached Compute resources including Azure Databricks
  • monitor compute utilization
  • determine access requirements and map requirements to built-in roles
  • create custom roles
  • manage role membership
  • manage credentials by using Azure Key Vault
  • create compute instances
  • share compute instances
  • access Azure Machine Learning workspaces from other development environments
  • create a training pipeline by using Azure Machine Learning designer
  • ingest data in a designer pipeline
  • use designer modules to define a pipeline data flow
  • use custom code modules in designer
  • create and run an experiment by using the Azure Machine Learning SDK
  • configure run settings for a script
  • consume data from a dataset in an experiment by using the Azure Machine Learning
    SDK
  • run a training script on Azure Databricks compute
  • run code to train a model in an Azure Databricks notebook
  • log metrics from an experiment run
  • retrieve and view experiment outputs
  • use logs to troubleshoot experiment run errors
  • use MLflow to track experiments
  • track experiments running in Azure Databricks
  • use the Automated ML interface in Azure Machine Learning studio
  • use Automated ML from the Azure Machine Learning SDK
  • select pre-processing options
  • select the algorithms to be searched
  • define a primary metric
  • get data for an Automated ML run
  • retrieve the best model
  • select a sampling method
  • define the search space
  • define the primary metric
  • define early termination options
  • find the model that has optimal hyperparameter values
  • consider security for deployed services
  • evaluate compute options for deployment
  • configure deployment settings
  • deploy a registered model
  • deploy a model trained in Azure Databricks to an Azure Machine Learning endpoint
  • consume a deployed service
  • troubleshoot deployment container issues
  • register a trained model
  • monitor model usage
  • monitor data drift
  • configure a ParallelRunStep
  • configure compute for a batch inferencing pipeline
  • publish a batch inferencing pipeline
  • run a batch inferencing pipeline and obtain outputs
  • obtain outputs from a ParallelRunStep
  • create a target compute resource
  • configure an inference pipeline
  • consume a deployed endpoint
  • create a pipeline
  • pass data between steps in a pipeline
  • run a pipeline
  • monitor pipeline runs
  • trigger an Azure Machine Learning pipeline from Azure DevOps
  • automate model retraining based on new data additions or data changes
  • refactor notebooks into scripts
  • implement source control for scripts
  • select a model interpreter
  • generate feature importance data
  • evaluate model fairness based on prediction disparity
  • mitigate model unfairness
  • describe principles of differential privacy
  • specify acceptable levels of noise in data and the effects on privacy

Industry Trends

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Cloud Computing

Industry Growth

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17.5% CAGR

between 2016 and 2026

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$331 billion

market growth by 2022

Cloud Professional

Annual Salary

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Cloud Professional

Hiring Companies

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Data Science Practitioner Amazon
Data Science Practitioner Cisco Systems
Data Science Practitioner HP
Data Science Practitioner American Express
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OUR PARTNERS

Useful Links

Contact Us

India

Dnyanasha Technology Solutions India Pvt. Ltd. The Kode, AWFIS, Baner Pashan Link Road, Pune

+91 8237377106

UAE

Dnyanasha Technology Solutions 17th floor, Prime Tower, 6C Marasi Dr – Business Bay – Dubai

+971 0524 807 514

UK

The DataTech Labs 2, Frederick Street Kings Cross, London. WC1X 0ND, UK

8000485080

USA

The DataTech Labs Inc. 188, Grand Street, Office 255, NY 10013, USA

855 5616 600