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Meta
This course offers a practical framework for basic analytics tasks including data extraction, cleaning, manipulation, and analysis, introducing the OSEMN cycle for managing analytics projects.

DeepLearning.AI
Learn to harness complex data for better business decisions through real-world datasets and practical applications in various industries.

University of Amsterdam
Learn data analytics techniques useful in Lean Six Sigma improvement projects, focusing on Minitab use and interpreting analysis outcomes.

Northeastern University
Learn computational fundamentals for analyzing real-world data, including data structures, cleaning, probability, cluster, text, and time series analysis.

Simplilearn
Master automating data workflows and analysis using generative AI tools, including building predictive models and conducting risk simulations.

University of Colorado Boulder
Experience the full analytics process by analyzing financial loans, building predictive models, and presenting investment recommendations in a practical project.

Amazon Web Services
Get introduced to data analytics concepts and AWS services to manage data processing, storage, and ETL pipelines effectively for business insights.

Tableau Learning Partner
Learn to manipulate and prepare data in Tableau, perform exploratory analysis, and use analytical features to generate accurate reports effectively.

University of Illinois Urbana-Champaign
Comprehensive exploration of dairy cow health and nutrition, focusing on physiological changes around calving and their impact on nutrient needs and health issues.

Universidad Nacional Autónoma de México
Introduction to biological evolution and its history, highlighting Charles Darwin's foundational role in shaping modern evolutionary thought.

IBM
Final assessment covering foundational skills in data analysis and visualization using Excel and Cognos Analytics.

Microsoft
Use Microsoft Copilot AI tools to transform complex data into insights, create clear visualizations, and communicate findings effectively.

Johns Hopkins University
Gain practical experience with Hadoop ecosystem tools including Hive, Pig, HBase, and Apache Spark for big data processing, management, and analysis.

Wesleyan University
Develop and test hypotheses using various statistical tests, learning strategies to select the appropriate one for your specific data and question.

The Pennsylvania State University
Gain a comprehensive understanding of dairy management, including genetics, nutrition, reproduction, animal health, farm economics, and sustainability of dairy production systems.

University of Colorado System
Second course in the specialization exploring computational thinking and beginning C programming focused on data analysis, representation, selection, and iteration.

University of Colorado Boulder
The "Data Analysis Project" course empowers students to apply their knowledge and skills gained in this specialization to conduct a real-life data analysis project of their interest.

EDUCBA
Build, format, and analyze data with pivot tables in Excel, apply grouping and filtering, and automate workflows using macros.

Wesleyan University
Apply and refine data analytic techniques on real-world projects addressing major social issues alongside academic and industry partners.

Arizona State University
Learn to read, write, manipulate, and analyze data using Python data structures and libraries like pandas and Matplotlib for effective visualization.

Microsoft
Learn to design accessible reports and dashboards in Power BI, adding visualizations to perform effective data analysis and storytelling.

Microsoft
Learn to use Microsoft 365 Copilot in Excel to analyze data efficiently, generate insights, create visualizations, and automate information summarization.

University of Colorado Boulder
Engineering and Business professionals often have access to many sources of data. The best way to way to ensure your data is both valid and reliable is to plan for it ahead of time.

University of California, Irvine
This course will take you through the various parts of analytical dashboarding: from best practices for designing a dashboard, creating a unified analytical environment, to deploying and publishing visualizations.