Data Science Meets Power BI: Transforming Data into Insights

Data Science Meets Power BI: Transforming Data into Insights, available at $69.99, has an average rating of 4.5, with 120 lectures, 10 quizzes, based on 15 reviews, and has 215 subscribers.

You will learn about Master integration of Python and R into Power BI for enhanced data analysis and visualizations. Acquire skills in using IDEs for script creation, testing, and debugging in Python and R. Understand how to apply Natural Language Processing (NLP) concepts and handle large datasets effectively. Gain expertise in creating custom functions, performing advanced statistical analyses, and creating intricate visualizations not native to Power BI. This course is ideal for individuals who are Beginners in Data Science: Aspiring data scientists with little to no coding experience will find this course valuable as it provides a solid foundation in Python, R, and Power BI. or Power BI Users: Individuals already using Power BI for data analysis and visualization, but looking to enhance their capabilities by integrating Python and R for more advanced statistical analysis and data visualizations. or Data Analysts: Professionals already working in the field of data analysis who want to broaden their skill set with the use of Python, R, and Power BI. or Business Intelligence Professionals: Those involved in BI who want to augment their analysis skills and deliver deeper insights using Power BI, Python, and R. or Students: Individuals studying fields like computer science, statistics, or business who want to complement their academic knowledge with practical, industry-relevant skills in data science and visualization. It is particularly useful for Beginners in Data Science: Aspiring data scientists with little to no coding experience will find this course valuable as it provides a solid foundation in Python, R, and Power BI. or Power BI Users: Individuals already using Power BI for data analysis and visualization, but looking to enhance their capabilities by integrating Python and R for more advanced statistical analysis and data visualizations. or Data Analysts: Professionals already working in the field of data analysis who want to broaden their skill set with the use of Python, R, and Power BI. or Business Intelligence Professionals: Those involved in BI who want to augment their analysis skills and deliver deeper insights using Power BI, Python, and R. or Students: Individuals studying fields like computer science, statistics, or business who want to complement their academic knowledge with practical, industry-relevant skills in data science and visualization.

Enroll now: Data Science Meets Power BI: Transforming Data into Insights

Summary

Title: Data Science Meets Power BI: Transforming Data into Insights

Price: $69.99

Average Rating: 4.5

Number of Lectures: 120

Number of Quizzes: 10

Number of Published Lectures: 120

Number of Published Quizzes: 10

Number of Curriculum Items: 131

Number of Published Curriculum Objects: 131

Original Price: $129.99

Quality Status: approved

Status: Live

What You Will Learn

Master integration of Python and R into Power BI for enhanced data analysis and visualizations.
Acquire skills in using IDEs for script creation, testing, and debugging in Python and R.
Understand how to apply Natural Language Processing (NLP) concepts and handle large datasets effectively.
Gain expertise in creating custom functions, performing advanced statistical analyses, and creating intricate visualizations not native to Power BI.

Who Should Attend

Beginners in Data Science: Aspiring data scientists with little to no coding experience will find this course valuable as it provides a solid foundation in Python, R, and Power BI.
Power BI Users: Individuals already using Power BI for data analysis and visualization, but looking to enhance their capabilities by integrating Python and R for more advanced statistical analysis and data visualizations.
Data Analysts: Professionals already working in the field of data analysis who want to broaden their skill set with the use of Python, R, and Power BI.
Business Intelligence Professionals: Those involved in BI who want to augment their analysis skills and deliver deeper insights using Power BI, Python, and R.
Students: Individuals studying fields like computer science, statistics, or business who want to complement their academic knowledge with practical, industry-relevant skills in data science and visualization.

Target Audiences

Beginners in Data Science: Aspiring data scientists with little to no coding experience will find this course valuable as it provides a solid foundation in Python, R, and Power BI.
Power BI Users: Individuals already using Power BI for data analysis and visualization, but looking to enhance their capabilities by integrating Python and R for more advanced statistical analysis and data visualizations.
Data Analysts: Professionals already working in the field of data analysis who want to broaden their skill set with the use of Python, R, and Power BI.
Business Intelligence Professionals: Those involved in BI who want to augment their analysis skills and deliver deeper insights using Power BI, Python, and R.
Students: Individuals studying fields like computer science, statistics, or business who want to complement their academic knowledge with practical, industry-relevant skills in data science and visualization.

Welcome to “Data Science Meets Power BI: Transforming Data into Insights”. This comprehensive course is designed to arm you with the powerful skills of Python and R, and the dynamic visualisation capabilities of Power BI. Whether you’re a beginner or intermediate user, our expert instructors will guide you through the world of data science and its integration with Power BI.

Learn how to set up Python and R in clean environments, minimising conflicts with Power BI. Explore the use of Integrated Development Environments (IDEs) to write, test, and debug your Python and R scripts. Discover the best Python and R packages for optimal functionality and compatibility, and use these tools to perform high-level statistical analyses, solve complex problems with simple functions and algorithms, and create stunning, highly customizable visuals that go beyond the native capabilities of Power BI.

From basic Python and R knowledge to advanced topics like Natural Language Processing (NLP) and handling large datasets, this course will boost your analytical capabilities and transform you into a proficient data analyst.

In over 15 hours of intensive training videos and multiple resource packs, this course provides the ultimate analytical toolset that empowers you to create in-depth reports and derive actionable insights from your data. Dive into the world where data science meets Power BI and emerge a versatile, highly skilled professional ready to tackle any data challenge.

No prior coding knowledge is required, just bring along your enthusiasm to learn and explore! Join us and start your journey to becoming a data science and Power BI powerhouse today!

Course Curriculum

Chapter 1: Python Fundamentals and Data Manipulation

Lecture 1: Learning Tips From Enterprise DNA

Lecture 2: Python Fundamentals: Resource Pack

Lecture 3: User-interface updates to be aware of

Lecture 4: Did you know?

Lecture 5: Course Overview – Let's Get Started!

Lecture 6: Introduction to Python and Power BI

Lecture 7: Setting Up Anaconda: Your Python Environment

Lecture 8: Mastering Dictionaries and Dataframes in Python

Lecture 9: Essential Dataframe Functions for Data Manipulation

Lecture 10: Combining and Filtering Data in Python

Lecture 11: Python Fundamentals and Data Manipulation – Review

Lecture 12: Python Fundamentals and Data Manipulation Insights

Lecture 13: Your Feedback Matters!

Chapter 2: Python Advanced Concepts and Visualization with Power BI

Lecture 1: Crafting Insights Beyond Visualization

Lecture 2: Data Visualization: Unleashing the Power of Python

Lecture 3: Exploring Three Ways to Harness Python Scripting

Lecture 4: Python Visuals and Spyder IDE: A Dynamic Duo

Lecture 5: Harnessing the Potential of Date Tables in Python

Lecture 6: Creating Python-Enhanced Reports: Part A

Lecture 7: Creating Python-Enhanced Reports: Part B

Lecture 8: Python Advanced Concepts and Visualization with Power BI – Review

Lecture 9: Advanced Python & Visualization with Power BI: Key Insights

Chapter 3: Python Datasets and String Functions

Lecture 1: Python's Datasets and String Facts

Lecture 2: Introduction to Datasets and String Functions

Lecture 3: Datasets and String Functions: Resource Pack

Lecture 4: Boosting Efficiency with Intellisense and AutoComplete for Jupyter Notebook

Lecture 5: Mastering User-Defined Functions in Python

Lecture 6: Building Cleaning Functions for Data Preprocessing

Lecture 7: Visualizing Cleaned Data: Unveiling Patterns and Insights

Lecture 8: Building an Interactive Heatmap Dashboard in Python

Lecture 9: Lists and For Loops: Harnessing the Power of Iteration

Lecture 10: Python Datasets and String Functions – Review

Lecture 11: Python Datasets & String Functions: Key Insights

Chapter 4: Text Analysis in Python

Lecture 1: Scripting Semantics: Python's Text Analysis Facts

Lecture 2: Introduction to Text Analysis

Lecture 3: Lemmatization in Text Analysis

Lecture 4: Cleaning Text and Analyzing Word Frequency

Lecture 5: Word Cloud Generation in Text Analysis

Lecture 6: Creating Shaped Word Clouds in Text Analysis

Lecture 7: Sentiment Analysis Application in Text Analysis

Lecture 8: Building a Text Analysis Dashboard: Part 1

Lecture 9: Building a Text Analysis Dashboard: Part 2

Lecture 10: Text Analysis in Python – Review

Lecture 11: Text Analysis in Python: Tips and Insights

Chapter 5: Introduction to R in Power BI

Lecture 1: R's Uncharted Integration in Power BI Revealed

Lecture 2: R in Power BI – Resource Pack

Lecture 3: Getting Ready for R in Power BI

Lecture 4: The Power of R in Power BI: Why it Matters

Lecture 5: Installing R and RStudio: Your R Development Environment

Lecture 6: First Steps in RStudio: Navigating the R Interface

Lecture 7: Configuring R with Power BI: Seamless Integration

Lecture 8: How R Talks with Power BI: Bridging the Gap

Lecture 9: Introduction to R in Power BI – Review

Lecture 10: Integrating R with Power BI: Key Insights and tips

Chapter 6: Fundamentals of R Programming

Lecture 1: Cracking the Code: Intriguing R Facts

Lecture 2: Fundamentals of R Programming Resource Pack

Lecture 3: Working with Objects: Building Blocks of R

Lecture 4: Object Classes: Exploring R's Data Structures

Lecture 5: Manipulating Vectors: Essential Techniques in R

Lecture 6: Data Frames: Managing Structured Data in R

Lecture 7: Working with Factors: Handling Categorical Data in R

Lecture 8: Exploring Packages: Expanding R's Functionality

Lecture 9: Locating Helpful Packages: Navigating the R Ecosystem

Lecture 10: Data Manipulation: Row Operations with dplyr in R

Lecture 11: Data Manipulation: Column Operations with dplyr in R

Lecture 12: Data Manipulation: Pipe Operations with dplyr in R

Lecture 13: Fundamentals of R Programming – Review

Lecture 14: R Programming Basics: Key Insights

Chapter 7: Data Visualization in R

Lecture 1: Data Visualization in R Facts

Lecture 2: Data Visualization in R Resource Pack

Lecture 3: Introduction to ggplot2: Creating Stunning Visualizations

Lecture 4: Plotting with esquisse: Simplifying Data Visualization in R

Lecture 5: Bivariate Visualizations: Uncovering Relationships in Data

Lecture 6: Labels, Colors, and Themes: Customizing Visual Elements in R

Lecture 7: Interactive R Visualization: Engaging Dashboards and Reports

Lecture 8: Data Visualization in R – Review

Lecture 9: Crafting Visual Stories: Data Visualization Techniques in R

Chapter 8: R Enhanced Power BI and Intermediate Topics

Lecture 1: Beyond Basics: Intermediate R

Lecture 2: Capstone R Enhanced Power BI Resource Pack

Lecture 3: Capstone Introduction: Setting the Stage for Your R Power BI Project

Lecture 4: Building the Histogram: Analyzing Data Distributions

Lecture 5: Building the T-Test: Hypothesis Testing in R

Lecture 6: Building the Power BI Report: Integrating R Visuals

Lecture 7: Additional Topics : Resource Pack

Lecture 8: Troubleshooting R: Common Issues and Solutions

Instructors

Enterprise DNA
Future-Proof Your Career: Master Data Skills | Upskill in AI
Sam McKay
Unleashing Potential: The Power of Data Mastery

Rating Distribution

1 stars: 0 votes
2 stars: 0 votes
3 stars: 0 votes
4 stars: 7 votes
5 stars: 8 votes

Frequently Asked Questions

How long do I have access to the course materials?

You can view and review the lecture materials indefinitely, like an on-demand channel.

Can I take my courses with me wherever I go?

Definitely! If you have an internet connection, courses on Udemy are available on any device at any time. If you don’t have an internet connection, some instructors also let their students download course lectures. That’s up to the instructor though, so make sure you get on their good side!

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