Data Transformation

This path is designed to build the broad range of expert-level knowledge necessary to confidently pass the PL-300 Data Analyst certification exam (replacement for DA-100).

This path is the most in-depth and rigorous on the list, designed to provide you expert-level skills in all of the key pillars of Power BI. 

This Learning Path offers a comprehensive journey through data visualization and analysis techniques, with a special emphasis on Power BI.

This path is focused on developing expert level skills in data cleaning, data transformation and data modeling. You will learn to maximize the capabilities of the Power Query UI, and also write M code.

This path is designed to provide you the necessary skills to build full enterprise apps by integrating Power BI , Power Automate and Power Apps. 

This path is similar to the Data Analyst learning path above, but is geared to building a strong and broad foundation of data analysis skills, as compared to being more specifically focused on passing the PL 300 exam.

This Learning Path navigates learners through real-world scenarios to cultivate problem-solving skills using the M language in Power Query.

This Learning Path offers a comprehensive journey through advanced data analysis and modeling techniques all illustrated through practical scenarios.

Expand Power BI's capabilities in accessing a wide range of data using APIs

The second part of the preparation course for the Microsoft's DP-500 Exam Certification

Deepen your understanding of the Power Query/M concepts through practical application

The first of the two-part preparation course for the Microsoft's DP-500 Exam Certification

Get familiar with structured values in the M language and discover how to interact with them.

Expand your Power BI report by integrating it with Power Platform applications to incorporate capabilities above and beyond just reporting on insights.

Data Transformation with AI is an immersive course that delves into the world of Data Science and Artificial Intelligence. You'll gain essential knowledge and skills to harness the power of data and build intelligent systems. Topics include data analysis, machine learning, deep learning, and ethical AI considerations, making this course suitable for beginners and those seeking to advance their expertise.

An in depth overview of the entire Power BI suite, with a focus on using Power BI to extract compelling insights from your own data.

Find out how Sidekick can help to review, optimize & cleanup your dataset and reports

How to build the ultimate Stream Deck profile - perform an array of common Power BI tasks at the push of a button

Know the techniques in creating indexes and how to loop efficiently using DAX

This session will cover which Python and R packages and examples can facilitate functionalities found in Power BI

Learning how to use SELECT, FROM, WHERE, GROUP BY, HAVING, ORDER BY

Discover the key points around OEE and producing a technically sound report

Explore the incredible impact of Artificial Intelligence (AI) on the field of data professionals.

Explore structured columns containing Lists, Records or Tables

Create an analysis report on environmental data and potentially impact how this data is visualized and recorded

Create a report summary of the overall services provided by a Call Centre for its management

Take on the challenge of creating an analysis report on hotels revenue management data.

Take a deep dive into the world of utilisation and timesheet data

Analyze the data of a large insurance company who are due to undergo an internal audit with regard to its complaint’s procedure

Challenge your data skills by producing a report that gives the user the ability to select a currency and see the associated sales and cost

Work on one of the most significant measures for manufacturing productivity - OEE

Produce insights for management level that can highlight any issues and prepare them for the audit

This SQL cheat sheet gives you the most common SQL objects and commands, including data types, DML and DDL statements, aggregate functions, string and date functions, and subqueries.

This offers techniques to retrieve and manipulate data based on specific row indexes or key matches, enhancing the flexibility and precision of data analysis.

When programming in Python, having a reliable cheat sheet by your side can be a game-changer. Python may be known for its simplicity and readability, but there’s no denying that its extensive range of features and functionalities is too much to memorize!