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Design and Implementing a Data Science Solutions on Azure

Learn how to operate machine learning solutions at cloud scale using Azure Machine Learning. This course teaches you to leverage your existing knowledge of Python and machine learning to manage data ingestion and preparation, model training and deployment, and machine learning solution monitoring in Microsoft Azure.

Course Info

Learn how to operate machine learning solutions at cloud scale using Azure Machine Learning. This course teaches you to leverage your existing knowledge of Python and machine learning to manage data ingestion and preparation, model training and deployment, and machine learning solution monitoring in Microsoft Azure.

Who Should Attend?

This course is aimed at data scientists and those with significant responsibilities in training and deploying machine learning models. This course is for those who want to build and operate machine learning solutions in the cloud 

Course Outline 

Azure Notebook

Jupyter Notebooks

Zeppelin Notebooks

Azure Machine Learning Workspace

Manage Experiment Compute Contexts

Design the Data Preparation Flow

Pipelines in Azure Machine Learning

Datasets and Dataset Management

Eligibility Criteria:

1. Pakistani Nationals with Valid CNIC

2. First Come First Serve Basis

3. ICT Graduates, Public Sector Individuals & Industry Potentials

4. CV of every participant

5. Recommendation letter of participants from public/private sector

6. Undertaking from all the participants 

Duration:

1 Month Flexible Class Options

Weekend Classes for Professionals SAT | SUN

? Online Classes – Live Virtual Class (L.V.C), Online Training

1. ICT Graduates : 

a) Training Fee:

     Free

b) Deadline 22nd Aug 2020

2. ICT Public Sector Individuals

a) Training Fee:

   Free ( Funded by PSEB ( Ministry of Information & Technology) )

 b) Deadline For 20th July 2020

3. ICT Private Sector Individuals

 a) Training Fee: 10 % to be paid by applicants 90 % to be paid by PSEB ( Ministry of Information & Technology

 b) Deadline 20 th July 2020