DP-100
| Formats: | Asynchronous |
| Blended | |
| Online | |
| Onsite | |
| Part-time | |
| Level: | Beginner |
| Prerequisites: | |
| Recommended Knowledge | |
| Understanding of statistics, machine learning, and data wrangling. | |
| Proficiency in Python or R for data analysis. | |
| Familiarity with Azure services. | |
Formats: We offer our training content in a flexible format to suit your needs. Contact Us if you wish to know if we can accommodate your unique requirements.
Level: We are happy to customize course content to suit your skill level and learning goals. Contact us for a customized learning path.
Microsoft Certified: Azure Data Scientist Associate (DP-100)
Microsoft Certified: Azure Data Scientist Associate (DP-100)
Mastering Data Science with Microsoft Azure in South Africa
In today’s data-driven landscape, the ability to leverage advanced analytics and machine learning is crucial for driving business innovation. The Microsoft Certified: Azure Data Scientist Associate (DP-100) course equips you with the skills to design and implement machine learning solutions using Microsoft Azure, a leading cloud platform adopted by enterprises globally.
At Big Data Labs in Randburg, Gauteng, we provide hands-on training to empower South African professionals to excel in data science. This course prepares you for the DP-100 exam, earning you a globally recognized certification that validates your expertise in Azure-based data science solutions.
Target Audience
This course is designed for professionals aiming to advance their data science careers, including:
Data Scientists
Professionals seeking to implement machine learning on Azure.
Data Engineers
Engineers transitioning to data science roles with Azure tools.
AI Developers
Developers building predictive models on Azure platforms.
Career Changers
Individuals entering data science with Azure expertise.
Prerequisite Skills
This course is tailored for professionals with foundational data science knowledge, with the following recommended skills:
- Data Science Fundamentals: Understanding of statistics, machine learning, and data wrangling.
- Programming Skills: Proficiency in Python or R for data analysis.
- Azure Basics: Familiarity with Azure services (e.g., Azure Fundamentals AZ-900 or Data Fundamentals DP-900) is helpful but not mandatory.
What One Will Learn (Learning Outcomes)
Upon completion of this course, you will be able to:
- Design ML Solutions: Plan and implement machine learning workflows on Azure.
- Prepare Data: Clean and transform data using Azure Databricks and Azure Data Factory.
- Train Models: Build and train machine learning models with Azure Machine Learning.
- Deploy Models: Deploy and manage models using Azure endpoints and pipelines.
- Optimize Solutions: Apply hyperparameter tuning and AutoML for model performance.
- Ensure Responsible AI: Implement ethical AI practices and compliance.
Target Market
This course is essential for organizations in South Africa aiming to leverage advanced data science solutions:
Enterprises
Developing predictive analytics for business growth.
Consulting Firms
Delivering AI-driven insights for clients.
Financial Services
Enhancing fraud detection and risk modeling.
Retail & E-commerce
Optimizing customer personalization and demand forecasting.
Healthcare
Improving patient outcomes with predictive analytics.
Course Outline: Azure Data Scientist Associate
This course provides comprehensive training on designing and implementing machine learning solutions with Azure, covering the full data science lifecycle.
Module 1: Set Up an Azure Machine Learning Workspace (10–15%)
- Create and configure Azure Machine Learning workspaces.
- Manage compute resources and environments.
- Implement security and access controls.
- Lab: Set up an Azure ML workspace.
Module 2: Run Experiments and Train Models (30–35%)
- Design experiments using Azure ML Designer and SDK.
- Train models with Python, Scikit-learn, or TensorFlow.
- Apply AutoML and hyperparameter tuning.
- Lab: Train a model with Azure ML.
Module 3: Optimize and Manage Models (20–25%)
- Evaluate model performance with metrics and diagnostics.
- Implement model monitoring and retraining.
- Use MLflow for model tracking.
- Lab: Optimize a model with hyperparameter tuning.
Module 4: Deploy and Consume Models (25–30%)
- Deploy models to Azure endpoints (real-time and batch).
- Build and manage ML pipelines with Azure Data Factory.
- Ensure responsible AI with fairness and interpretability tools.
- Lab: Deploy a model to an Azure endpoint.
Course Features
- Duration: 4–6 days instructor-led or 6–8 weeks self-paced.
- Format: Lectures, hands-on labs, and practice exams.
- Certification Exam: DP-100 (120 minutes, 40–60 questions, USD 165).
- Certification Validity: 1 year, renewable via free assessment.
- Delivery: Classroom, online, or hybrid formats.
Why Choose DP-100?
The DP-100 certification validates your ability to design and deploy machine learning solutions on Azure, positioning you as a leader in South Africa’s data science industry. With hands-on skills in Azure Machine Learning, you’ll drive innovation and business value across diverse sectors.