DP-100: Designing and Implementing Data Science Solution on Microsoft Azure

Course Description

The DP-100: Designing and Implementing a Data Science Solution on Microsoft Azure course is tailored for professionals aiming to apply data science and machine learning techniques using Azure services. Participants will gain hands-on experience in managing data ingestion, preparation, model training, deployment, and monitoring within the Azure ecosystem. The course emphasizes practical applications of Azure Machine Learning, enabling learners to build and operationalize end-to-end machine learning solutions at scale. Upon completion, participants will be prepared to take the DP-100 certification exam, validating their expertise as Azure Data Scientists.

Key Learning Objectives

By completing this course, participants will be able to:

1. Design and Prepare a Machine Learning Solution
2. Run Experiments and Train Models
3. Deploy and Operationalize Machine Learning Solutions
4. Implement Responsible Machine Learning

Prerequisites

To ensure a successful learning experience, participants should have:

• Proficiency in Python programming and familiarity with machine learning frameworks such as Scikit-Learn, PyTorch, or TensorFlow.
• Understanding of data science concepts, including data exploration, preparation, and model training.
• Basic knowledge of cloud computing and Azure services.

Audience Profile

This course is ideal for:

• Data Scientists seeking to leverage Azure for scalable machine learning solutions.
• Machine Learning Engineers aiming to deploy and manage models in a cloud environment.
• Data Engineers interested in expanding their skill set to include machine learning operations on Azure.
• AI Professionals looking to integrate Azure’s AI services into their workflows.
• IT Professionals aspiring to transition into data science roles with a focus on Azure technologies.

If you’re involved in designing, implementing, or managing machine learning models and data science solutions, this course will enhance your proficiency with Azure’s data science tools.

Career Growth & Industry Demand

The integration of data science and cloud computing is driving demand for professionals skilled in Azure’s machine learning services. Organizations are seeking experts who can develop, deploy, and manage scalable AI solutions. Job Roles After Completing This Course

• Azure Data Scientist
• Machine Learning Engineer
• AI Solutions Architect
• Data Science Consultant
• Cloud AI Engineer

Industries That Hire Azure Data Scientists

• Technology & IT Services (Developing AI-driven applications and services)
• Healthcare & Pharmaceuticals (Implementing predictive analytics for patient care and drug development)
• Finance & Banking (Enhancing fraud detection and risk assessment models)
• Retail & E-Commerce (Personalizing customer experiences through data-driven insights)
• Manufacturing & Supply Chain (Optimizing operations with predictive maintenance and demand forecasting)

Why Enroll in This Course?

• Comprehensive Curriculum: Gain in-depth knowledge of designing and implementing data science solutions on Azure.
• Certification Preparation: Be fully prepared to pass the DP-100 certification exam and earn the Azure Data Scientist Associate credential.
• Hands-On Experience: Engage in practical exercises and labs that simulate real-world scenarios.
• Career Advancement: Enhance your professional profile and open new opportunities in various industries.
• Expert Instruction: Learn from experienced instructors with deep expertise in Azure and data science.

Enrolling in this course will equip you with the skills and credentials needed to excel in the rapidly evolving field of data science and machine learning on Microsoft Azure.