Power BI for Data Science and Analytics

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Power BI for Data Science and Analytics

This course is part of Mastering Power BI for Data Analytics & Storytelling Specialization

Instructor: Edureka

2,170 already enrolled

Included with Coursera Plus

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4 modules

Gain insight into a topic and learn the fundamentals.

Intermediate level

Recommended experience

1 week to complete

at 10 hours a week

Flexible schedule

Learn at your own pace

4 modules

Gain insight into a topic and learn the fundamentals.

Intermediate level

Recommended experience

1 week to complete

at 10 hours a week

Flexible schedule

Learn at your own pace

What you'll learn

Understand the role of data analytics and AI in business intelligence.
Configure and navigate the Power BI environment for effective use.
Apply Power BI’s AI-driven features for smart data exploration.
Build interactive reports and dashboards for data-driven decisions.

Skills you'll gain

Details to know

Shareable certificate

Add to your LinkedIn profile

Assessments

27 assignments

Taught in English

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Build your subject-matter expertise

This course is part of the Mastering Power BI for Data Analytics & Storytelling Specialization

When you enroll in this course, you'll also be enrolled in this Specialization.

Learn new concepts from industry experts
Gain a foundational understanding of a subject or tool
Develop job-relevant skills with hands-on projects
Earn a shareable career certificate

There are 4 modules in this course

Welcome to Power BI for Data Science and Analytics. This course is designed to help you develop practical skills in data analytics using Power BI, a leading business intelligence platform.

You will learn to use key Power BI features to extract and visualize insights from your data, making it easier to share findings and drive decisions. By the end of this course, you’ll be able to: - Use Power BI effectively for data analytics from connecting to data sources to building interactive reports and dashboards. - Create insightful visualizations that communicate important trends and patterns clearly to your team or stakeholders. - Apply AI features in Power BI such as natural language queries, anomaly detection, and cognitive services—to uncover deeper insights from your data. - Centralize and model data with dataflows, enabling reusable, efficient reporting for both text and image analytics. - Evaluate the impact of AI features on your analysis, so you can select the right tools for your projects. - Design scorecards to track KPIs and performance metrics in a format that’s easy to understand and act upon. This course is built for Data Analysts, Business Intelligence Developers, and Business Analysts looking to strengthen their analytical and reporting skills using Power BI. Some familiarity with MS Excel, Python, or Power BI is helpful, but not required, you willl gain hands-on experience with practical assignments and real-world scenarios. Join us on this journey to elevate your Power BI analytical skills and design capabilities.

In this module, you will be able to set an environment for analyzing datasets to apply various algorithms in Power BI. Gain a basic understanding of the importance of Data Science and Analytics. Construct AI-related results on the data to visualize important metrics that deal with anomaly detection, QnA etc.

What's included

28 videos5 readings9 assignments1 discussion prompt1 plugin

28 videosTotal 112 minutes

Course Introductory Video3 minutes
Data Science and Analytics 4 minutes
Era of Data Science3 minutes
Case Study - Fintech3 minutes
Case study - HealthCare3 minutes
Power BI in Data Analytics3 minutes
Features in Power BI for Data Science4 minutes
Installation of MS SQL Server2 minutes
SQL Server Interface - Object Explorer6 minutes
SQL Server Interface - Basic Scripts5 minutes
Working with Power BI5 minutes
Installation of Power BI Desktop and Service5 minutes
Installing of ALM Toolkit3 minutes
ALM Toolkit - Operations5 minutes
Introduction to Time Intelligence Functions 7 minutes
Time Intelligence Functions - Working4 minutes
AI in Power BI - NLQ and Smart Discovery5 minutes
AI in Power BI - Anomaly Detection3 minutes
Cognitive Services in Power BI2 minutes
Sentiment Analysis2 minutes
Key Phrase Extraction2 minutes
Language Detection1 minute
Usage Metrics and Q&A in Power BI4 minutes
Introduction to Dynamic Lines 5 minutes
Implementation of Dynamic Lines3 minutes
Dynamic lines for Power BI Visuals4 minutes
Interactive Reporting using Power BI3 minutes
Summary of Power BI for Data Analytics1 minute

5 readingsTotal 155 minutes

Welcome to Power BI for Data Science and Analytics10 minutes
Power BI Getting Started30 minutes
A Beginner’s Guide To Data Science40 minutes
ALM Toolkit45 minutes
AI Features in Power BI30 minutes

9 assignmentsTotal 38 minutes

Knowledge Check: Introduction to Data Analytics5 minutes
Knowledge Check: Environment Configuration and Setup5 minutes
Knowledge Check: Exploring Artificial Intelligence in Power BI5 minutes
Knowledge Check: Exploring Dynamic Lines in Power BI5 minutes
Knowledge Check: Integrating Data Science and AI Capabilities in Power BI10 minutes
Practice Quiz: Foundations of Data Analytics2 minutes
Practice Quiz: Environment Configuration and Setup2 minutes
Practice Quiz: Exploring Artificial Intelligence in Power BI2 minutes
Practice Quiz: Dynamic Lines in Power BI2 minutes

1 discussion promptTotal 10 minutes

Introduce Yourself10 minutes

1 pluginTotal 10 minutes

Power BI for Data Science Readiness Check10 minutes

In the second week of this course, You will be able to construct dataflows to prepare, transform, and centralize data for consistent and reusable reporting . Manage data such that AI features can be utilized effectively on the designed dataset.

What's included

20 videos4 readings10 assignments1 discussion prompt

20 videosTotal 81 minutes

Getting the data ready3 minutes
Different Methods of Dataflows Creation5 minutes
Data Preparation4 minutes
Real Time data ingestion vs Batch processing4 minutes
Dataflow Calculation Engine3 minutes
Data Models5 minutes
Setting up Data Models for AI4 minutes
Data Modelling Disciplines to Support AI2 minutes
Binary Prediction - Setting up the Model5 minutes
Binary Prediction - Execution6 minutes
Introduction to Python3 minutes
Basics of Python5 minutes
Demonstration of Python4 minutes
Installing Python2 minutes
Integrating Python with Power BI1 minute
Creating Visuals in Power BI using Python2 minutes
Binary Prediction3 minutes
Classification5 minutes
Regression5 minutes
Summary: Dataflows and AI Analytics1 minute

4 readingsTotal 120 minutes

Introduction to Dataflows30 minutes
Creation of Dataflows30 minutes
Python in Power BI30 minutes
Tutorial: Build a machine learning model in Power BI30 minutes

10 assignmentsTotal 53 minutes

Knowledge Check: Handling Dataflows5 minutes
Knowledge Check: Dataflow Management5 minutes
Knowledge Check: Binary Prediction5 minutes
Knowledge Check: Python Visuals in Power BI5 minutes
Knowledge Check: AI in Power BI15 minutes
Knowledge Check: Dataflows and AI10 minutes
Practice Quiz: Overview of Dataflows2 minutes
Practice Quiz: Dataflow Modeling2 minutes
Practice Quiz: Python Integration with Power BI2 minutes
Practice Quiz: AI Analytics2 minutes

1 discussion promptTotal 10 minutes

Have you worked with Machine Learning Models Before?10 minutes

In the third week of this course, we'll learn about techniques offered by Power BI to analyze text and images to gain insights from the data. Focus on using M Functions to model data according to user preference.

What's included

15 videos4 readings7 assignments

15 videosTotal 55 minutes

Text Analysis - Detect Language5 minutes
Text Analysis - Key Phrase Extraction3 minutes
Text - Sentiment Analysis3 minutes
Report Generation6 minutes
Image Analysis5 minutes
Image Recognition3 minutes
Scorecard3 minutes
Key Features of Scorecard2 minutes
Creation of Scorecard2 minutes
Demonstrataion of Scorecard2 minutes
Gateway2 minutes
Installing Gateway1 minute
M - Functions 7 minutes
Deep Dive in M - Functions5 minutes
Summary of Advanced Cognitive Features0 minutes

4 readingsTotal 110 minutes

Power BI Desktop Privacy Levels30 minutes
Stop-words List25 minutes
Sentiment Analysis and Opinion Mining Language Support25 minutes
Power Query M function30 minutes

7 assignmentsTotal 28 minutes

Knowledge Check: Exploring Advanced Cognitive Analytics Capabilities2 minutes
Knowledge Check: Overview of Scorecard5 minutes
Knowledge Check: M Query and Functions5 minutes
Knowledge Check: Exploring Advanced Cognitive Analytics Capabilities10 minutes
Practice Quiz: Exploring Advanced Cognitive Analytics Capabilities2 minutes
Practice Quiz: Overview of Scorecard2 minutes
Practice Quiz: M-functions2 minutes

This module is designed to assess an individual on the various concepts and teachings covered in this course. Answer a comprehensive quiz which marks you as a learner who is confident in working with Power BI.

What's included

1 video1 reading1 assignment1 discussion prompt1 plugin

1 videoTotal 2 minutes

Course Summary of Power BI for Data Science and Analytics2 minutes

1 readingTotal 30 minutes

Project: Global Superstore Analysis30 minutes

1 assignmentTotal 30 minutes

Knowledge Check: End Course Test30 minutes

1 discussion promptTotal 10 minutes

Describe Your Learning Journey10 minutes

1 pluginTotal 10 minutes

Applying Power BI for Data Science: A Scenario-Based Exercise10 minutes

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Instructor

Edureka

84 Courses97,634 learners

Offered by

Edureka

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Frequently asked questions

The "Power BI for Data Science and Analytics" course provides comprehensive insights into the full potential of AI features offered by the Power BI service. This course is designed to empower learners with the knowledge and skills needed to seamlessly utilize AI-generated reports for analysis and enable efficient data visualization.

This course caters to a diverse audience, embracing those new to the field as Data Scientist, Data Analyst, Business Analyst and Business Intelligence Developer will enhance their skills in Analytics, while BI Developers will gain insights into AI analytical features and visualization.

Yes, Prior working experience with MS Excel, RDBMS (Relational Database Management Systems), Python and Machine Learning is advantageous, offering a valuable foundation for this course. However, it is important to note that possessing proficiency in these tools is not obligatory.

To access the course materials, assignments and to earn a Certificate, you will need to purchase the Certificate experience when you enroll in a course. You can try a Free Trial instead, or apply for Financial Aid. The course may offer 'Full Course, No Certificate' instead. This option lets you see all course materials, submit required assessments, and get a final grade. This also means that you will not be able to purchase a Certificate experience.