Data Analysis courses

4.82

Data visualization is a critical skill for anyone that routinely using quantitative data in his or her work - which is to say that data visualization is a tool that almost every worker needs today....

4.75

Describe the fundamentals of spreadsheet applications Perform basic spreadsheet tasks including navigation, data entry, and using formulas. Employ data quality techniques to import and clean data in Excel. Analyze data in spreadsheets by using filter...

4.72

In this capstone project we’ll combine all of the skills from all four specialization courses to do something really fun: analyze social networks! The opportunities for learning are practically endless in a social network. Who...

3.77

This course will cover the steps used in weighting sample surveys, including methods for adjusting for nonresponse and using data external to the survey for calibration. Among the techniques discussed are adjustments using estimated response...

In any data-driven company, you will undoubtedly cross paths with data engineers. Among other things, they facilitate some of your work by making data readily available to everyone within the organization, and possibly in bringing...

Now that you've learned the basics of SQL in our Introduction to SQL course, it's time to supercharge your queries using joins and relational set theory. In this course, you'll learn all about the power...

4.52

The Business Analytics Capstone Project gives you the opportunity to apply what you've learned about how to make data-driven decisions to a real business challenge faced by global technology companies like Yahoo, Google, and Facebook....

4.41

Welcome to the specialization course Relational Database Systems. This course will be completed on six weeks, it will be supported with videos and various documents that will allow you to learn in a very simple...

4.48

Discover the basic concepts of cluster analysis, and then study a set of typical clustering methodologies, algorithms, and applications. This includes partitioning methods such as k-means, hierarchical methods such as BIRCH, and density-based method...

4.5

Describe Data Science’s role in various contextsUnderstand how Statistics and Machine Learning affect Data ScienceUse the key terms used by data scientistPredict whether a Data Science project will be successful

4.77

In this Capstone Project, you'll bring together all the new skills and insights you've learned through the four courses. You'll be given a 'mock' client problem and a data set. You'll need to analyze the...

4.76

Explain factors to consider when making decisions about data collectionDiscuss the difference between biased and unbiased dataDescribe databases with references to their functions and componentsDescribe best practices for organizing data

4.87

Sports analytics now include massive datasets from athletes and teams that quantify both training and competition efforts. Wearable technology devices are being worn by athletes everyday and provide considerable opportunities for an in-depth look a...

4.77

What are the ethical considerations regarding the privacy and control of consumer information and big data, especially in the aftermath of recent large-scale data breaches? This course provides a framework to analyze these concerns as...

DAX, or Data Analysis eXpressions, is a formula language used in Microsoft Power BI to create calculated columns, measures, and custom tables. Once mastered, DAX gives you powerful control over visuals and reports, allowing for...

Visualizing data using charts, graphs, and maps is one of the most impactful ways to communicate complex data. In this course, you’ll learn how to choose the best visualization for your dataset, and how to...

4.16

This MOOC – a joint initiative between EIT Digital, Université de Nice Sophia-Antipolis / Université Côte d'Azur, and INRIA - introduces the Linked Data standards and principles that provide the foundation of the Semantic web....

Have you ever heard about Internet of Things devices? Of course, you have. Maybe you also have a Raspberry PI in your house monitoring the temperature and humidity. IoT devices are everywhere around us, collecting...

5

Prepare data for modelling by handling missing values, formatting and normalizing data, binning, and turning categorical values into numeric values. Conduct exploratory data analysis using descriptive statistics, data grouping, data analysis and corr...

4.5

This course will cover the major techniques for mining and analyzing text data to discover interesting patterns, extract useful knowledge, and support decision making, with an emphasis on statistical approaches that can be generally applied...