What you'll get
- 4+ Hours
- 1 Courses
- Course Completion Certificates
- Self-paced Courses
- Technical Support
- Case Studies
Synopsis
- Achieve the Azure Data Scientist Associate (DP-100) certification on the first attempt.
- Develop practical skills to design, deploy, and manage machine learning solutions within the Azure ML ecosystem.
- Gain credentials that validate industry-ready expertise in Azure Machine Learning.
- Keep abreast of the newest developments and feature updates within the Azure Machine Learning platform.
Content
| Courses | No. of Hours | Certificates | Details |
|---|---|---|---|
| DP-100 Microsoft Azure DS Exam | 4h 34m | ✔ | View Curriculum |
Description
The Azure Machine Learning (DP-100) Certification Training provides a comprehensive learning pathway aligned with the latest DP-100 Microsoft Azure Data Scientist Associate exam. The course emphasizes hands-on experience in building, deploying, and managing machine learning solutions using Azure Machine Learning services.
Learners progress through structured modules that break down the exam objectives into clear, manageable segments, covering the end-to-end machine learning workflow in the cloud from model experimentation to production deployment. The program integrates practical exercises that enable learners to configure ML workspaces, train and optimize models, manage lifecycle operations, deploy models in production, and implement strategies for retraining models post-deployment.
Upon completion, participants are prepared to confidently attempt the DP-100 certification while mastering real-world applications of data science principles on the Azure platform.
Goals
- Equip learners with hands-on experience in Azure Machine Learning workflows.
- Prepare participants to pass the DP-100 certification exam successfully.
- Foster the ability to deploy and maintain ML models in live Azure environments.
- Ensure learners stay up to date with the evolving features of the Azure ML ecosystem.
Objectives
Upon completing the course, learners will have the ability to:
- Provision and configure Azure Machine Learning workspaces.
- Conduct experiments and train predictive models on Azure.
- Evaluate and optimize model performance using Azure ML tools.
- Deploy models to production and integrate them into automated pipelines.
- Manage model lifecycles and implement retraining strategies.
- Apply data science concepts to real-world Azure ML projects.
Highlights
- Aligned with DP-100 exam objectives for targeted certification preparation.
- Hands-on labs covering end-to-end machine learning workflows in Azure.
- Practical projects simulating real-world ML challenges.
- Step-by-step guidance on model deployment and operationalization.
- Expert instructors with deep industry and Azure ML experience.
- Up-to-date curriculum reflecting the latest Azure ML features and updates.
Requirements
- Basic familiarity with the Azure portal.
- Programming knowledge, preferably in Python or another general-purpose language.
- Access to a Microsoft Azure account (free-tier or paid subscription).
- Strong motivation to learn and apply cloud-based machine learning techniques.
Target Audience
- Individuals preparing for the Azure DP-100 certification.
- Data professionals aiming to enhance ML implementation skills.
- Azure practitioners and technical specialists seeking practical experience in ML deployment.
- Professionals looking to leverage cloud-based ML solutions for real-world applications.
FAQ
Q1: Does Microsoft officially accredit this course?
No, this course is an independent training program designed for exam preparation and skill development. It is not formally accredited or endorsed by Microsoft.
No, this course is an independent training program designed for exam preparation and skill development. It is not formally accredited or endorsed by Microsoft.
Q2: Do I need prior experience in machine learning?
Prior ML experience is helpful but not mandatory. Prior experience with programming fundamentals and a basic understanding of data analysis concepts is suggested.
Prior ML experience is helpful but not mandatory. Prior experience with programming fundamentals and a basic understanding of data analysis concepts is suggested.
Q3: Can I use a free Azure account for the labs?
Yes, the Azure free-tier account provides sufficient access for completing most course exercises.
Yes, the Azure free-tier account provides sufficient access for completing most course exercises.
Q4: Will I receive a certificate after completion?
Yes, participants receive a training completion certificate to showcase their skills and hands-on experience.
Yes, participants receive a training completion certificate to showcase their skills and hands-on experience.
Q5: How long does it take to complete the course?
The duration varies based on learning pace, but most learners complete it in 4–6 weeks with consistent practice.
The duration varies based on learning pace, but most learners complete it in 4–6 weeks with consistent practice.
Career Benefits
- Earn the Azure Data Scientist Associate credential, a recognized industry certification.
- Gain practical, hands-on expertise in cloud-based ML development.
- Enhance employability for roles like Azure Data Scientist, ML Engineer, and AI Specialist.
- Improve the ability to implement end-to-end ML solutions in enterprise environments.
- Maintain an edge in the fast-evolving domain of cloud-based data science.
