Coursera

Power BI Data Analyst Associate Prep (Coursera)

Offered by SkillUp EdTech,
Power BI Data Analyst Associate Prep (Coursera)

This short course will guide you on preparing for the PL-300: Microsoft Power BI Data Analyst exam. This exam is the requirement for Microsoft Certified: Power BI Data Analyst Associate certification. The course provides you with a detailed understanding of the Power BI concepts, its features, and capabilities.

Class Deals by MOOC List - Click here and see Coursera's Active Discounts, Deals, and Promo Codes.

By the end of this course, you will be able to:

  • Describe how to prepare data for analysis by transforming, configuring, cleaning, and shaping it using Power BI.
  • Discuss the creation of data models in Power BI using a data model framework and Data Analysis Expressions (DAX) functions.
  • Explain how to design visually appealing reports using data visualization strategies in Power BI and perform data analytics using Analyze feature.
  • Examine how to create workspace, design interactive dashboards, and safeguard the data by configuring row-level security for datasets in Power BI.

The PL-300 exam is intended for data professionals who want to collaborate closely with business stakeholders, enterprise data analysts, and data engineers to identify and acquire data, transform the data, create data models, visualize data, and share assets using Power BI.
Having experience with data analysis, reporting, Power BI, proficiency in writing expressions by using Data Analysis Expressions (DAX), and understanding how to assess data quality is a must.

What you'll learn

  • Describe how to prepare data for analysis by transforming, configuring, cleaning, and shaping it using Power BI.
  • Discuss the creation of data models in Power BI using a data model framework and Data Analysis Expressions (DAX) functions.
  • Explain how to design visually appealing reports using data visualization strategies in Power BI and perform data analytics using Analyze feature.
  • Examine how to create workspace, design interactive dashboards, and safeguard the data by configuring row-level security for datasets in Power BI.

Syllabus

Data preparation and modeling in Power BI
The module begins with an overview of the features and components of Power BI that make it a great tool for data analysis. You’ll be able to explain how to retrieve data from different data sources and import it into Power BI by using Power Query. You’ll also learn how to clean and shape data for analysis purposes and load it into Power BI before getting into data modeling. Additionally, you will gain insight into Power BI data model frameworks, their benefits, limitations, and features that help optimize the selection of a Power BI data model. You will also learn to simplify the process of designing data models with an emphasis on the use of tables and dimensions and the significance of correct data granularity. Finally, you will gain insight into advanced data modeling features and how to perform advanced model calculations by using Data Analysis Expression (DAX) functions. You’ll also learn to add measures to Power BI Desktop models for enhancing the visualization of model data.

Data visualization and analysis in Power BI
In this module, you’ll explore various visualization strategies that enable you to implement effective data visualization. You will learn how to use core desktop visualization types to design visually appealing reports. Additionally, you will gain insight into formatting and configuring visualizations and discover techniques to perform data analytics by using the Analyze feature in Power BI. Finally, you’ll dive into how to use the Analytics feature for performing data analytics within Power BI, which helps you perform tasks such as identifying outliers, grouping data, and applying time series analysis.

Assets deployment and maintenance
In this module, you’ll explore asset deployment by creating a Power BI service workspace and dynamic dashboards. Additionally, you will learn how to manage and promote datasets and implement essential measures to ensure row-level security (RLS) in Power BI.

Go to Class
MOOC List is learner-supported. When you buy through links on our site, we may earn an affiliate commission.

Related Courses

Data Manipulation at Scale: Systems and Algorithms (Coursera) Coursera
University of Washington

Data Manipulation at Scale: Systems and Algorithms (Coursera)

Statistics & Data Analysis Data Science

Data analysis has replaced data acquisition as the bottleneck to evidence-based decision making --- we are drowning in it. Extracting knowledge from large, heterogeneous, and noisy datasets requires not only powerful computing resources, but the programming abstractions to use them effectively. The abstractions that emerged in the last decade blend ideas from parallel databases, distributed systems, and programming languages to create a new class of scalable data analytics platforms that form the foundation for data science at realistic scales.

Jun 22nd 2026
4 Weeks
Algebra Algorithms Databases
Details
Fundamentals of GIS (Coursera) Coursera
University of California, Davis

Fundamentals of GIS (Coursera)

CS: Information & Technology Sci: Physical & Earth Sciences

Explore the world of spatial analysis and cartography with geographic information systems (GIS). What you will learn: define core geospatial concepts; practice with subset data using selections and feature attributes; create map books using advanced mapping techniques; create layer and map packages.

Jun 22nd 2026
4 Weeks
Data Analysis Geographic Information Systems GIS
Details
Graph Analytics for Big Data (Coursera) Coursera
University of California, San Diego

Graph Analytics for Big Data (Coursera)

Statistics & Data Analysis Data Science

Want to understand your data network structure and how it changes under different conditions? Curious to know how to identify closely interacting clusters within a graph? Have you heard of the fast-growing area of graph analytics and want to learn more? This course gives you a broad overview of the field of graph analytics so you can learn new ways to model, store, retrieve and analyze graph-structured data.

Jun 22nd 2026
5-12 Weeks
Big Data Data Analysis Graphs
Details
Pattern Discovery in Data Mining (Coursera) Coursera
University of Illinois at Urbana-Champaign

Pattern Discovery in Data Mining (Coursera)

Statistics & Data Analysis Data Science

Learn the general concepts of data mining along with basic methodologies and applications. Then dive into one subfield in data mining: pattern discovery. Learn in-depth concepts, methods, and applications of pattern discovery in data mining. We will also introduce methods for data-driven phrase mining and some interesting applications of pattern discovery. This course provides you the opportunity to learn skills and content to practice and engage in scalable pattern discovery methods on massive transactional data, discuss pattern evaluation measures, and study methods for mining diverse kinds of patterns, sequential patterns, and sub-graph patterns.

Jun 22nd 2026
4 Weeks
Algorithms Data Mining Data Analysis
Details
Introducción a Data Science: Programación Estadística con R (Coursera) Coursera
Universidad Nacional Autónoma de México

Introducción a Data Science: Programación Estadística con R (Coursera)

Statistics & Data Analysis Data Science

Este curso te proporcionará las bases del lenguaje de programación estadística R, la lengua franca de la estadística, el cual te permitirá escribir programas que lean, manipulen y analicen datos cuantitativos. Te explicaremos la instalación del lenguaje; también verás una introducción a los sistemas base de gráficos y al paquete para graficar ggplot2, para visualizar estos datos. Además también abordarás la utilización de uno de los IDEs más populares entre la comunidad de usuarios de R, llamado RStudio.

Jun 22nd 2026
4 Weeks
Data Analysis Data Science R Language
Details
Interprofessional Healthcare Informatics (Coursera) Coursera
University of Minnesota

Interprofessional Healthcare Informatics (Coursera)

Statistics & Data Analysis Data Science

Interprofessional Healthcare Informatics is a graduate-level, hands-on interactive exploration of real informatics tools and techniques offered by the University of Minnesota and the University of Minnesota's National Center for Interprofessional Practice and Education. We will be incorporating technology-enabled educational innovations to bring the subject matter to life. Over the 10 modules, we will create a vital online learning community and a working healthcare informatics network.

Jun 22nd 2026
5-12 Weeks
Healthcare Informatics Telehealth
Details
Business Intelligence Concepts, Tools, and Applications (Coursera) Coursera
University of Colorado System

Business Intelligence Concepts, Tools, and Applications (Coursera)

Statistics & Data Analysis Data Science

This is the fourth course in the Data Warehouse for Business Intelligence specialization. Ideally, the courses should be taken in sequence. In this course, you will gain the knowledge and skills for using data warehouses for business intelligence purposes and for working as a business intelligence developer. You’ll have the opportunity to work with large data sets in a data warehouse environment and will learn the use of MicroStrategy's Online Analytical Processing (OLAP) and Visualization capabilities to create visualizations and dashboards.

Jun 22nd 2026
5-12 Weeks
Data Analysis Decision Making Business Intelligence
Details
Machine Learning Foundations: A Case Study Approach (Coursera) Coursera
University of Washington

Machine Learning Foundations: A Case Study Approach (Coursera)

Statistics & Data Analysis Data Science

Do you have data and wonder what it can tell you? Do you need a deeper understanding of the core ways in which machine learning can improve your business? Do you want to be able to converse with specialists about anything from regression and classification to deep learning and recommender systems? In this course, you will get hands-on experience with machine learning from a series of practical case-studies.

Jun 22nd 2026
5-12 Weeks
Python Machine Learning Clustering
Details
Text Retrieval and Search Engines (Coursera) Coursera
University of Illinois at Urbana-Champaign

Text Retrieval and Search Engines (Coursera)

Statistics & Data Analysis Data Science

Recent years have seen a dramatic growth of natural language text data, including web pages, news articles, scientific literature, emails, enterprise documents, and social media such as blog articles, forum posts, product reviews, and tweets. Text data are unique in that they are usually generated directly by humans rather than a computer system or sensors, and are thus especially valuable for discovering knowledge about people’s opinions and preferences, in addition to many other kinds of knowledge that we encode in text.

Jun 22nd 2026
5-12 Weeks
Machine Learning Search Data Mining
Details