Module 1: Introduction to Data Science

Module 2: Azure Machine Learning Overview

Module 3: Data Preparation and Feature Engineering

Module 4: Machine Learning Modeling

Module 5: Model Deployment and Management

Module 6: Advanced Topics in Azure Machine Learning

Module 7: Big Data and Machine Learning

Module 8: Ethical AI and Responsible ML

Prerequisites

1. Basic understanding of data science and machine learning concepts.

2. Experience with Python programming.

3. Familiarity with cloud computing basics (beneficial but not mandatory).

Certification: Microsoft Certified: Azure Data Scientist Associate (Exam DP-100)

Exam Format: Multiple-choice questions, scenario-based tasks

Duration: Approximately 180 minutes

Passing Criteria: Typically 700 or higher on a scale of 1000

Topics Covered: All course modules, with emphasis on practical application of Azure machine learning tools and techniques.

Who Should Attend:

1. Data Scientists

2. Data Analysts

3. Machine Learning Engineers

4. IT Professionals interested in data science

What You'll Learn:

1. Building and managing machine learning models with Azure Machine Learning

2. Conducting exploratory data analysis and feature engineering

3. Evaluating and validating machine learning models

4. Deploying and monitoring models in Azure

5. Implementing advanced machine learning and deep learning techniques

6. Best practices for end-to-end data science projects on Azure

Target Audience

1. Data Scientists transitioning to Azure cloud platform.

2. Data Analysts interested in advancing their skills in machine learning and AI.

3. IT Professionals exploring careers in data science and AI development using Azure