// 71 courses indexed
The course directory
Every course we track across 10+ providers, in one searchable index. Want a shortlist picked for your goals? Run a free skill gap analysis.
Microsoft Copilot for Power BI: AI-Powered Report Insights
Did you know that Metro Bank improved its financial reporting efficiency by 80% using Power BI or that FedEx optimized its logistics operations through data-driven decision-making? Businesses worldwide are leveraging the power of data to drive smarter decisions and gain a competitive edge—now it's your turn! Unlock the power of data with our comprehensive Power BI course, designed to transform you into a business intelligence expert! Dive deep into the world of data analysis and visualization, where you'll master how to connect to multiple data sources, clean and model data, and craft dynami
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Healthcare Data Models
Career prospects are bright for those qualified to work in healthcare data analytics. Perhaps you work in data analytics, but are considering a move into healthcare where your work can improve people’s quality of life. If so, this course gives you a glimpse into why this work matters, what you’d be doing in this role, and what takes place on the Path to Value where data is gathered from patients at the point of care, moves into data warehouses to be prepared for analysis, then moves along the data pipeline to be transformed into valuable insights that can save lives, reduce costs, to improve h
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Gemini and Vertex AI: Building Intelligent Applications
This course introduces the essentials of Gemini AI and Vertex AI, blending architectural insights with hands-on coding, multimodal development, and intelligent agent creation. Designed to give you both theoretical foundations and practical experience, it explores how Google’s most advanced AI systems are transforming software development, data analysis, and real-world applications. Through guided lessons and demonstrations, you’ll learn to work with Gemini’s multimodal architecture, leverage APIs for text and vision, build smarter apps with AI-driven code generation, and design intelligent ag
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Statistics Foundations
This course takes a deep dive into the statistical foundation upon which data analytics is built. The first part of this course will help you to thoroughly understand your dataset and what the data actually means. Then, it will go into sampling including how to ask specific questions about your data and how to conduct analysis to answer those questions. Many of the mistakes made by data analysts today are due to a lack of understanding the concepts behind the tests they run, leading to incorrect tests or misinterpreting the results. This course is tailored to provide you with the necessary ba
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How to use Custom and Conditional Formatting in Excel
By the end of this project, you will learn how to use conditional and custom formatting in an Excel Spreadsheet by using a free version of Microsoft Office Excel. Excel is a spreadsheet that is similar in layout as accounting spreadsheets. It consists of individual cells that can be used to build functions, formulas, tables, and graphs that easily organize and analyze large amounts of information and data. Conditional formatting is a convenient tool for data analysis and visual representation of results. Knowing how to use this tool will save you a lot of time and effort. A fleet glance at
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Using Custom Fields in Looker Explores
This is a Google Cloud Self-Paced Lab. In this lab, you will learn how to utilize custom fields in Looker Explores queries. Looker provides the ability for non-developer users to create and utilize ad hoc fields for richer data analysis. This is done by creating custom measures, custom dimensions, table calculations and using custom groupings to narrow down data to match specific conditions. Using ad hoc fields gives non-developers the ability to create new fields, as opposed to regular fields, which require that you have development permissions and understand LookML allowing them to have mo
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Apply Data Analytics with Minitab for Business Decisions
By the end of this course, learners will be able to apply statistical data analytics techniques using Minitab and Excel, interpret business data through descriptive and inferential methods, evaluate relationships using correlation and ANOVA, and support data-driven business decisions through real-world case studies. This course provides a practical, industry-focused introduction to data analytics using Minitab, designed for learners who want to move beyond theory and develop job-ready analytical skills. Learners will explore core statistical concepts such as descriptive statistics, hypothesis
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Observational Methods and Qualitative Data Analysis
This is primarily aimed at first- and second-year undergraduates interested in psychology, data analysis, and qualtitative research methods along with high school students and professionals with similar interests. This course delves into the qualitative research traditions of ethnographic inquiry and case study in psychology, emphasizing the use of participant observation. Students will explore the unique practices, data gathering and analysis methods, and researcher involvement in these traditions. This course explores the interviewing methods used in qualitative research in psychology. The
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Precalculus: Relations and Functions
This course helps to build the foundational material to use mathematics as a tool to model, understand, and interpret the world around us. This is done through studying functions, their properties, and applications to data analysis. Concepts of precalculus provide the set of tools for the beginning student to begin their scientific career, preparing them for future science and calculus courses. This course is designed for all students, not just those interested in further mathematics courses. Students interested in the natural sciences, computer sciences, psychology, sociology, or similar w
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PySpark Foundations: Process, analyze, and summarize data
Did you know that a billion records are processed daily in PySpark by companies worldwide? As big data is on the rise, you’ll need tools like PySpark to process massive amounts of data. This guided project was designed to introduce data analysts and data science beginners to data analysis in PySpark. By the end of this 2-hour-long guided project, you’ll create a Jupyter Notebook that processes, analyzes, and summarizes data using PySpark. Specifically, you will set up a PySpark environment, explore and clean large data, aggregate and summarize data, and visualize data using real-life examples
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Launch & Optimize Email Series
Ready to transform scattered email sends into powerful, strategic sequences that build relationships and drive results? This Short Course was created to help Marketing professionals accomplish building and optimizing high-performing email series that outperform single-email campaigns. By completing this course, you'll be able to create cohesive multi-email campaigns with personalized content, implement A/B testing strategies, and use data analytics to continuously improve your email series performance. By the end of this course, you will be able to: Build and launch a 3-part email series us
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Introduction to Data Analytics
Ready to start a career in Data Analysis but don’t know where to begin? This course presents you with a gentle introduction to Data Analysis, the role of a Data Analyst, and the tools used in this job. You will learn about the skills and responsibilities of a data analyst and hear from several data experts sharing their tips & advice to start a career. This course will help you to differentiate between the roles of Data Analysts, Data Scientists, and Data Engineers. You will familiarize yourself with the data ecosystem, alongside Databases, Data Warehouses, Data Marts, Data Lakes and Data Pi
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R Programming
In this course you will learn how to program in R and how to use R for effective data analysis. You will learn how to install and configure software necessary for a statistical programming environment and describe generic programming language concepts as they are implemented in a high-level statistical language. The course covers practical issues in statistical computing which includes programming in R, reading data into R, accessing R packages, writing R functions, debugging, profiling R code, and organizing and commenting R code. Topics in statistical data analysis will provide working examp
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Developing AI Applications on Azure
This course introduces the concepts of Artificial Intelligence and Machine learning. We'll discuss machine learning types and tasks, and machine learning algorithms. You'll explore Python as a popular programming language for machine learning solutions, including using some scientific ecosystem packages which will help you implement machine learning. Next, this course introduces the machine learning tools available in Microsoft Azure. We'll review standardized approaches to data analytics and you'll receive specific guidance on Microsoft's Team Data Science Approach. As you go through the c
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Introduction to Data Analytics
This course provides a practical understanding and framework for basic analytics tasks, including data extraction, cleaning, manipulation, and analysis. It introduces the OSEMN cycle for managing analytics projects and you'll examine real-world examples of how companies use data insights to improve decision-making. By the end of this course you will be able to: • Formulate business goals, KPIs and associated metrics • Apply a data analysis process using the OSEMN framework • Identify and define the relevant data to be collected for marketing • Compare and contrast various data formats and the
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Introduction to SIEM (Splunk)
This course provides a comprehensive understanding of Security Information and Event Management (SIEM) concepts and practical skills using Splunk as an SIEM solution. You will discover SIEM fundamentals, Splunk architecture, data collection and management, data analysis, and advanced topics such as correlation and incident response. By the end of the course, you will effectively apply Splunk for log analysis, threat detection, and security monitoring. Learning Objectives: Module 1: Introduction to SIEM and Log Management • Recognize SIEM fundamentals and its role in cybersecurity. • Compreh
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Population Health: Responsible Data Analysis
In most areas of health, data is being used to make important decisions. As a health population manager, you will have the opportunity to use data to answer interesting questions. In this course, we will discuss data analysis from a responsible perspective, which will help you to extract useful information from data and enlarge your knowledge about specific aspects of interest of the population. First, you will learn how to obtain, safely gather, clean and explore data. Then, we will discuss that because data are usually obtained from a sample of a limited number of individuals, statistical
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Data Visualization and Communication with Tableau
One of the skills that characterizes great business data analysts is the ability to communicate practical implications of quantitative analyses to any kind of audience member. Even the most sophisticated statistical analyses are not useful to a business if they do not lead to actionable advice, or if the answers to those business questions are not conveyed in a way that non-technical people can understand. In this course you will learn how to become a master at communicating business-relevant implications of data analyses. By the end, you will know how to structure your data analysis proj
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Explain Black-Box Models
Ready to unlock the mystery behind your most powerful models? This Short Course was created to help data analysis professionals accomplish transparent and trustworthy AI implementation. By completing this course, you'll master SHAP values for executive communication, systematically compare explainability methods, and align explanation strategies with stakeholder needs. By the end of this course, you will be able to: Apply SHAP values to a black-box model and produce feature-importance visuals interpretable by non-technical executives Evaluate two XAI methods (LIME vs. SHAP) for fidelity and s
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ChatGPT and Prompt Engineering With Advanced Data Analysis
This course features Coursera Coach! A smarter way to learn with interactive, real-time conversations that help you test your knowledge, challenge assumptions, and deepen your understanding as you progress through the course. This course offers an in-depth journey into the world of ChatGPT, prompt engineering, and advanced data analysis techniques. You will explore how to leverage AI tools like ChatGPT in business, programming, social media, and machine learning, while gaining hands-on experience in crafting effective prompts, using AI for data analysis, and generating creative outputs. By t
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Analyze E-Commerce Data Using PostgreSQL
Learners will apply SQL concepts, analyze real-world e-commerce datasets, and produce business-ready reports using PostgreSQL. By the end of this course, learners will be able to design relational database structures, write optimized SQL queries, perform advanced aggregations, and generate actionable insights from transactional data. This course provides a hands-on, project-driven approach to mastering PostgreSQL for data analysis. Learners begin by setting up the PostgreSQL environment and building a strong foundation in database management, table design, data types, and constraints. They th
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Fast-Track Data Analysis and Presentations
Need to crunch data or pull together a presentation? In this course, you’ll design prompts that help you extract insights, understand spreadsheet formulas, and build graphs to visualize data. You'll also explore how to use AI tools to help with speaker notes and practice before your big day, once you’re ready to present your findings. By the end of this course, you will be able to: - Develop a responsible prompting practice when entering data into generative AI tools - Apply the prompting framework to extract insights from data, identify and fix spreadsheet formulas, and explore data visualiz
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Data Management for Analytics Part 1
This course will offer you an opportunity to learn the fundamental concepts and emerging technologies in database design and modeling and database systems. It presents a balanced theory-practice focus and covers entity relationship model and UML model, relational model, and relational databases. By the end of this part 1 course on data analytics, you will have a foundational understanding of the theory and applications of database management to support data analytics, data mining, machine learning, and artificial intelligence.
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Data Analysis with Pivot Tables: Build & Automate
Master Data Analysis with Pivot Tables: Build, Analyze & Automate teaches you how to transform raw Excel data into meaningful insights using pivot tables, pivot charts, advanced calculations, and automation. Through a structured, step-by-step learning experience, you'll progress from understanding the fundamentals of pivot tables to applying advanced analytical features that improve reporting and decision-making. You will learn how to build and format pivot tables, sort and filter data, group numeric and date fields, and use advanced features such as Show Details, grand total settings, and Sh
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