Overview
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Microsoft Advanced Analytics Techniques with Generative AI helps you build modern analytics skills by combining proven data methods with emerging AI tools. You’ll strengthen your ability to analyze structured and unstructured data, automate workflows, create forecasts, and support strategic decisions using practical techniques employers value.
Across five courses, you’ll work with R, GitHub Copilot, Power BI, Excel, Azure Blob Storage, APIs, and reporting tools to solve realistic business problems. You’ll move from statistical testing and regression analysis to time-series forecasting, scenario planning, anomaly detection, and automated coding workflows.
You’ll learn how to improve efficiency with generative AI while maintaining analytical judgment. The program emphasizes using AI responsibly to generate code, streamline documentation, accelerate data cleaning, and uncover insights faster.
By the end of the specialization, you’ll be able to build predictive models, automate repetitive tasks, create dynamic reports, evaluate risks, and communicate findings clearly to stakeholders.
This specialization is designed for analysts, technical professionals, and experienced learners who want to modernize their skills with AI-enhanced analytics. Prior experience with data analysis, spreadsheets, or basic programming is recommended.
Syllabus
- Course 1: Statistical Analysis and Advanced Techniques
- Course 2: Advanced Data Applications and Integration
- Course 3: Advanced Data Analysis with Generative AI
- Course 4: Scenario and Root Cause Analysis with Generative AI
- Course 5: Coding and Automation for Data Analysis with Generative AI
Courses
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This course delves into sophisticated analytical methods, including predictive modeling, time-series forecasting, and anomaly detection. You'll learn to harness the power of AI to uncover hidden patterns and trends in complex datasets. The course covers text data analysis, enabling you to extract valuable insights from unstructured data sources. Upon completion of this course, you'll be able to: - Perform predictive analysis using generative AI tools - Conduct time-series analysis and forecasting with AI assistance - Extract insights from text data using generative AI technologies - Identify and analyze anomalies and outliers in datasets using AI
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This course teaches you to harness AI-powered tools for code generation, focusing on SQL, Python, and R for data analysis tasks. The target learner for this course is a seasoned data professional or an aspiring analyst. This comprehensive program empowers. The course covers the design and implementation of automated data processing pipelines, enabling you to streamline your entire data analysis workflow. Upon completion of this course, you'll be able to: - Generate code snippets for data analysis tasks using AI - Create and optimize formulas for data manipulation and analysis - Design automated data processing pipelines with generative AI - Integrate AI capabilities into existing coding environments and workflows
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In this final course, you'll apply generative AI to scenario planning and root cause analysis. The target learner for this course is a seasoned data professional or an aspiring analyst. This comprehensive program empowers. Upon completion of this course, you'll be able to: - Conduct scenario analysis using generative AI models - Perform root cause analysis with AI assistance - Identify and assess potential risks using AI-powered techniques - Develop data-driven strategies based on AI-generated scenario insights
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Take your R programming skills to the next level with this final, practical course that bridges theory and real-world applications. Learn to collect data from web sources, create interactive visualizations, handle large datasets efficiently, and integrate with cloud services. While covering advanced topics, the course maintains a beginner-friendly approach with step-by-step guidance and AI assistance.
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Begin your journey into practical statistics with this beginner-friendly course that makes complex concepts accessible. Learn to perform basic statistical analyses using R and Microsoft's tools, while using AI assistance to help understand and implement statistical concepts. Through hands-on practice with real datasets, you'll build confidence in conducting and interpreting statistical tests. By the end of this course, you will be able to: • Apply core statistical methods — including descriptive statistics, hypothesis testing, and regression analysis — to real-world datasets with confidence. • Use R and Microsoft tools to perform, visualize, and communicate statistical analyses effectively. • Interpret the results of statistical tests and translate findings into clear, actionable insights for non-technical audiences. • Design and execute a basic end-to-end statistical analysis workflow, from data preparation through to results and conclusions.
Taught by
Microsoft