Course
Case Study: Inventory Analysis in Power BI
- IntermediateSkill Level
- 4.7+
- 168 reviews
This Power BI case study follows a real-world business use case on tackling inventory analysis using DAX and visualizations.
Data Visualization
Follow short videos led by expert instructors and then practice what you’ve learned with interactive exercises in your browser.
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Course
This Power BI case study follows a real-world business use case on tackling inventory analysis using DAX and visualizations.
Data Visualization
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Learn how to store, secure, scale, and process data in Azure using Blob Storage, Cosmos DB, queues, and event-driven services.
Cloud
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Learn to analyze and visualize network data with the igraph package and create interactive network plots with threejs.
Probability & Statistics
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Develop the skills you need to clean raw data and transform it into accurate insights.
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Learn the basics of A/B testing in R, including how to design experiments, analyze data, predict outcomes, and present results through visualizations.
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Learn to analyze Airbnb data using SQL in Databricks, create dashboards, and derive actionable insights.
Importing & Cleaning Data
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In this course youll learn techniques for performing statistical inference on numerical data.
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Develop a better intuition for advanced probability, risk assessment, and simulation techniques to make data-driven business decisions with confidence.
Probability & Statistics
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Learn efficient techniques in pandas to optimize your Python code.
Software Development
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Apply your finance and R skills to backtest, analyze, and optimize financial portfolios.
Applied Finance
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Learn business valuation with real-world applications and case studies using discounted cash flows (DCF).
Applied Finance
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Machine Learning
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Build smart, interactive, and reliable AI applications easier than ever before with the OpenAI Responses API and GPT-5.
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Manage the complexity in your code using object-oriented programming with the S3 and R6 systems.
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Learn to create, secure, and manage APIs with Azure API Management through hands-on practice.
Cloud
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Learn tools and techniques to leverage your own big data to facilitate positive experiences for your users.
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Streamline your AI projects by building modular models and mastering advanced optimization with PyTorch Lightning!
Artificial Intelligence
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Use data manipulation and visualization skills to explore the historical voting of the United Nations General Assembly.
Exploratory Data Analysis
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Learn how to reduce training times for large language models with Accelerator and Trainer for distributed training
Artificial Intelligence
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Leverage the power of tidyverse tools to create publication-quality graphics and custom-styled reports that communicate your results.
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Data Engineering
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In this course youll learn how to leverage statistical techniques for working with categorical data.
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Begin your journey with Scala, a popular language for scalable applications and data engineering infrastructure.
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Get ready to categorize! In this course, you will work with non-numerical data, such as job titles or survey responses, using the Tidyverse landscape.
Data Manipulation
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Elevate decision-making skills with Decision Models, analysis methods, risk management, and optimization techniques.
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Go beyond MCP basics with sampling, notifications, roots, and the STDIO and StreamableHTTP transports in Python.
Artificial Intelligence
Data science is an area of expertise focused on gaining information from data. Using programming skills, scientific methods, algorithms, and more, data scientists analyze data to form actionable insights.
You’ll need to learn a programming language such as Python or R and master the principles of math and statistics. Knowledge of data analysis methods and data science tools is also essential. There are many ways to learn data science. As well as formal means of education, such as a degree or university study, there are plenty of other resources to help you learn at your own pace. As well as online courses and tutorials, there are books, videos, and more.
As well as knowledge of mathematics and statistics, data scientists need programming skills in languages such as Python, R, and SQL. Additionally, data science requires the ability to work with large data sets, knowledge of data visualization, data wrangling, and database management. Skills in machine learning and deep learning can also be useful.
In a professional capacity, almost every industry can use data science to some degree. Healthcare organizations use data science to detect and cure diseases, while finance companies use it to detect and prevent fraud. All kinds of industries use data science for marketing, such as building recommendation systems and analyzing customer churn.
Yes, data science is among the fastest-growing sectors in the US and worldwide. It’s also one of the best-paid careers out there. According to data from Payscale, experience data scientists earn an average of $97,609 and have a satisfaction rating of four stars out of five in the US.
There are a few things to consider here. First, data science degrees can be competitive to get onto, often requiring consistently high grades. Similarly, many of the skills required for data science require a lot of study and patience. It can take several months to master all of the necessary basics, as well as a lot of practical experience to secure an entry-level position.
Yes, you’ll need some coding experience in languages such as Python, R, SQL, Java, and C/C++. However, due to its relatively simple syntax, Python programming language is often the preferred choice among newcomers.
For a person with no prior coding experience and/or mathematical background, it can typically take 7 to 12 months of intensive studies to be at the level of an entry-level data scientist. However, it is important to remember that learning only the theoretical basis of data science may not make you a real data scientist.
Once you’ve mastered the foundations of data science, you can then specialize in a variety of areas, including machine learning, artificial intelligence, big data analysis, business analytics and intelligence, data mining, and more.
Make progress on the go with our mobile courses and daily 5-minute coding challenges.