Microsoft Generative AI for Data Analysis Professional Certificate

Microsoft

Coursera

Microsoft Generative AI for Data Analysis Professional Certificate

Learn the basics of how generative AI works and its core applications.

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Level

Intermediate

Price

Freemuim

Duration

95

Format

Self-Paced

About

Unlock the transformative power of AI in data analysis with this Gen AI for Data Analysis Professional Certificate. Designed for both seasoned data professionals and aspiring analysts, this comprehensive program empowers you to leverage AI across the entire data lifecycle, streamlining processes and uncovering deeper insights crucial for career success. Key program features: Hands-on experience: engage in real-world projects for practical skill application Ethical AI practices: learn to implement AI responsibly and ethically Build a portfolio: Showcase your new skills with a robust portfolio You'll develop expertise in: Integrating AI tools into data analysis workflows Optimizing data processing and preparation with AI assistance Enhancing exploratory data analysis and uncover hidden insights Applying advanced analytical methods, including predictive modeling Creating dynamic visualizations and interactive dashboards Automating workflows through AI-powered code generation Upon completion, you'll be equipped to: Streamline data cleaning and preparation processes Uncover deeper insights from complex datasets Communicate findings more effectively through AI-enhanced visualizations Make data-driven decisions informed by AI-powered scenario analysis No prior experience with generative AI required, familiarity with data analysis concepts and basic programming skills is recommended. Join us to unlock the full potential of your data analysis capabilities. Applied Learning Project The Generative AI in Data Analytics certification course features 15 projects, from coding exercises to real-world challenges. You'll learn to analyze customer sentiment, clean datasets, and build forecasting models using AI tools. The course covers data exploration, sentiment classification, theme extraction, and automated data cleaning. You'll apply predictive analysis to historical data, understanding preprocessing, model selection, and evaluation. Tools used include: AI-Assisted Analysis: Leveraging large language models for analysis, code generation, and visualization Coding Environments: Using popular programming languages and libraries for data manipulation Data Profiling Tools: Employing software to identify and address data quality issues By completion, you'll have the expertise to apply Generative AI in data analytics, streamlining workflows and communicating insights effectively.

Topic

Role Specific

Role

Data Analysis

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