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Azure Machine Learning Course

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₹15,000.00
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Overview:

Bot Campus’s Azure Machine Learning (Azure ML) Course is an extensive program designed to equip learners with the skills needed to build, deploy, and manage machine learning models using Azure ML Studio. Our Azure certification classes are ideal for professionals looking to enhance their cloud-based machine learning expertise and advance their careers in data science and AI. The azure machine learning online course starts with an introduction to Azure ML Studio, covering its tools and navigation. Learners will discover the essentials of data science, including supervised vs. unsupervised learning, and key concepts like classification and regression. A solid foundation in data management will be established, focusing on data uploading and preprocessing.
Advanced topics such as feature engineering and hyperparameter tuning will also be included. The course covers model deployment as secure web services for real-world applications, alongside monitoring performance for optimization. A final module addresses the ethics and societal impacts of machine learning, including bias and privacy issues. By the end of this Microsoft Azure machine learning course, learners will be proficient in the complete machine learning workflow with Azure ML Studio, empowering them to create impactful solutions in data science.

What You'll Learn

Course Content

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Module 1: Getting Started with Azure ML Studio
Module 2: Building Machine Learning Models
Module 3: Deploying and Consuming Models

FAQs

1. What is Azure Machine Learning, and why should I learn it?

Azure Machine Learning is a cloud-based service for constructing, training, deploying, and managing machine learning models. Learning it equips you with skills to create scalable AI solutions and integrate them into enterprise applications.

2. Who should take this Azure Machine Learning course?

This course is designed for data scientists, AI enthusiasts, and developers who want to leverage Azure’s cloud capabilities for machine learning and AI model deployment.

3. What subjects will I explore in the Azure Machine Learning course?

You’ll learn:
How to establish and navigate through Azure Machine Learning Studio.
Data preparation, training, and deploying machine learning models.
Automated machine learning (AutoML) and hyperparameter tuning.
Integration of Azure ML with other Azure services like Databricks and Synapse Analytics.

4. How long does it take to complete the Azure Machine Learning course?

This course can be completed in 2 to 3 weeks, with a daily commitment of 1 hour. The flexible schedule makes it suitable for working professionals and students.

5. Are there prerequisites for enrolling in this course?

Learn Azure machine learning with basic knowledge of Python programming and machine learning concepts is recommended. Familiarity with cloud computing or Azure fundamentals is a plus but not mandatory.

6. Will I work on real-world projects during the course?

Yes, you’ll gain hands-on experience by working on projects such as:
Creating and deploying predictive models.
Automating workflows with AutoML.
Building an end-to-end machine learning pipeline.

7. What tools and frameworks will I use in this course?

You’ll work with:
Azure Machine Learning Studio and SDK.
Python libraries like Pandas, scikit-learn, and TensorFlow.
Azure cloud services such as Databricks, Blob Storage, and Synapse Analytics.

8. What career opportunities can I pursue after completing this course?

You can work as an AI Engineer, Machine Learning Engineer, Data Scientist, or Cloud AI Specialist. Azure ML skills are highly sought after in industries adopting cloud-based AI solutions.

9. Will I receive a certification after completing the course?

Yes, you’ll earn an Azure Machine Learning Certification, showcasing your expertise in building and deploying machine learning models on Azure.

10. How does this course differ from other machine learning courses?

This course focuses specifically on leveraging Azure’s cloud-based tools for machine learning, providing practical insights into enterprise-grade AI solutions. It combines theoretical knowledge with hands-on experience in the Azure ecosystem.

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