Azure Data Scientist Associate

5 Courses | 100 Lessons
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📖 C1 Create Machine Learning Models in Azure 4 Modules | 20 Lessons
▶ M1 Machine Learning Fundamentals 5
1L1 Machine Learning Kya Hai→ 2L2 ML Workflow→ 3L3 Features aur Labels→ 4L4 ML Algorithms Overview→ 5L5 Module Review→
▶ M2 Regression Models in Azure 5
1L1 Regression kya hai→ 2L2 Advanced Regression Techniques→ 3L3 Azure ML Designer me Regression→ 4L4 Regression Evaluation Metrics→ 5L5 Module Review→
▶ M3 Classification Models 5
1L1 Classification kya hai→ 2L2 Classification Algorithms→ 3L3 Classification Me Azure ML→ 4L4 Classification Evaluation Metrics→ 5L5 Module Review→
▶ M4 Clustering and Unsupervised Learning 5
1L1 Unsupervised Learning Overview→ 2L2 KMeans Clustering→ 3L3 Beyond KMeans→ 4L4 Practical Clustering Projects→ 5L5 Module Review→
📖 C2 Azure Machine Learning for Data Scientists 4 Modules | 20 Lessons
▶ M1 Azure Machine Learning Workspace 5
1L1 Azure ML Workspace Overview→ 2L2 Compute Resources→ 3L3 Datastores aur Datasets→ 4L4 Environment aur Configuration→ 5L5 Module Review→
▶ M2 Experiments and Runs 5
1L1 Experiments kya hain→ 2L2 Python SDK se Training→ 3L3 Distributed Training→ 4L4 Experiment Best Practices→ 5L5 Module Review→
▶ M3 Automated Machine Learning 5
1L1 AutoML kya hai→ 2L2 AutoML Configuration→ 3L3 AutoML Results Analysis→ 4L4 Advanced AutoML Features→ 5L5 Module Review→
▶ M4 ML Pipelines and Workflows 5
1L1 ML Pipelines Overview→ 2L2 Pipeline Components→ 3L3 Pipeline Scheduling aur Triggers→ 4L4 Pipeline Best Practices→ 5L5 Module Review→
📖 C3 Build and Operate ML Solutions with Azure 4 Modules | 20 Lessons
▶ M1 Model Registration and Deployment 5
1L1 Model Registry→ 2L2 Deployment Options→ 3L3 Scoring Script aur Environment→ 4L4 Endpoint Management→ 5L5 Module Review→
▶ M2 RealTime and Batch Inference 5
1L1 RealTime Inference→ 2L2 Batch Inference→ 3L3 Inference Optimization→ 4L4 Edge Deployment→ 5L5 Module Review→
▶ M3 MLOps and Model Monitoring 5
1L1 MLOps Fundamentals→ 2L2 Azure DevOps aur GitHub Actions→ 3L3 Model Monitoring→ 4L4 Retraining Strategies→ 5L5 Module Review→
▶ M4 Responsible AI in Azure 5
1L1 Responsible AI Principles→ 2L2 Azure Responsible AI Dashboard→ 3L3 Model Explainability→ 4L4 Fairness aur Bias Mitigation→ 5L5 Module Review→
📖 C4 Perform Data Science with Azure Databricks 4 Modules | 20 Lessons
▶ M1 Introduction to Azure Databricks 5
1L1 Azure Databricks Overview→ 2L2 Databricks Workspace Setup→ 3L3 Databricks Architecture→ 4L4 Integration with Azure Services→ 5L5 Module Review→
▶ M2 Apache Spark Fundamentals 5
1L1 Apache Spark kya hai→ 2L2 PySpark Basics→ 3L3 Data Transformations→ 4L4 Spark Performance Optimization→ 5L5 Module Review→
▶ M3 Data Science with Databricks Notebooks 5
1L1 Databricks Notebooks→ 2L2 ML with Spark MLlib→ 3L3 MLflow on Databricks→ 4L4 Advanced Notebook Features→ 5L5 Module Review→
▶ M4 Collaborative Data Science Workflows 5
1L1 Team Collaboration→ 2L2 Databricks Workflows→ 3L3 Delta Lake for Data Science→ 4L4 EndtoEnd Project Workflow→ 5L5 Module Review→
📖 C5 DP100 Exam Preparation and Practice 4 Modules | 20 Lessons
▶ M1 DP100 Exam Overview and Domains 5
1L1 DP100 Exam Structure→ 2L2 Domain 1 Design aur Prepare ML Solution→ 3L3 Domain 2 Explore Data aur Train Models→ 4L4 Domain 3 Prepare aur Deploy Models→ 5L5 Module Review→
▶ M2 Practice Questions ML and Azure ML 5
1L1 ML Concepts Questions→ 2L2 Azure ML Workspace Questions→ 3L3 AutoML aur Pipeline Questions→ 4L4 ScenarioBased Questions→ 5L5 Module Review→
▶ M3 Practice Questions Deployment and MLOps 5
1L1 Model Deployment Questions→ 2L2 MLOps Questions→ 3L3 Responsible AI Questions→ 4L4 Monitoring aur Optimization Questions→ 5L5 Module Review→
▶ M4 Final Review and Exam Strategies 5
1L1 DomainWise Review→ 2L2 HighFrequency Topics→ 3L3 Exam Taking Strategies→ 4L4 PostExam aur Career Growth→ 5L5 Module Review→