Advanced Analytics

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 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 delves into data analysis techniques, focusing on Power BI functions. It guides learners to enhance their data insight extraction skills.

This path is designed to help you harness the full power of Power BI in combination with R and Python. You will learn how to conduct advanced analyses and gain insight into complex business questions.

This Learning Path delves into data analysis and visualization using both R and Python, covering data cleaning, data frames, and the use of packages like dplyr, tidyverse, skim R, and seaborn. It offers hands-on examples, such as creating various plots, performing group-based operations, and utilizing descriptive statistics for effective data interpretation.

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

This learning path offers a deep dive into data management and analysis, emphasizing the hands-on use of Python and Scala languages for manipulating CSV and JSON files, and the application of SQL for data querying. 

Learn valid inference techniques for two-sample and two-variable data questions.

Master the ultimate tool for executing and analyzing DAX queries against various sources including Power BI and SSAS

Dramatically enhance Power BI's capabilities by incorporating Python's flexible and powerful data wrangling, data analysis and data visualization functionality

Master the most powerful tool for data modeling and DAX calculations in Power BI and Analysis Services

Advanced course using Power BI & DAX to solve complex but common business problems and scenarios you'll face everyday

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

Clean data and perform Natural Language Processing through Python's functions, algorithms and programming methods

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

Covers the use of quick measures and the features

Develop compelling dashboards within Power BI using a range of analytical and visualisation techniques

Check the Replays of the Feb 2022 Analytics Summit Event for Analysts, Excel Users, Database Professionals, Data Enthusiasts and more.

Identify trends in sales and customer behavior and assess the performance of different stores or regions using the LFL Analysis in Retail

Develop advanced Power BI analytical techniques

Analyzing your data set in comprehensive way to get a better understanding

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

The session include function Let and how to declare and using parameters in Power Query and DAX

Jump into this twitter related dataset and showcase some interesting insights based on the text of the tweet and the stock reference or tagged within the tweet itself.

Deep dive into the world of F1 and create an analysis of the drivers' stats

Enhance your development skills by creating a supplier insights report

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

Challenge your data skills by creating a report on transport and shipping data 

Develop an analysis report about the Football/Soccer Players Summer Transfers Season 2022-23

An excellent opportunity for you to create a one-page data report for Covid-19 analysis

Challenge your data skills in creating an analysis report on substance

This Excel formulas cheat sheet covers advanced forecasting formulas, statistical analysis, data manipulation functions, error handling, and more.