Introduction To Data Analysis Using R

This is the second course in the Data Analyst R pathway. This course expands upon the programming concepts and techniques covered in Intro to R. It will also teach you how to use the most common data structures in data analysis. This information is crucial for data professionals.

This is the third course in our Data Analyst in Rails program. This course expands on the R programming skills you've acquired in the first two courses. It allows you to perform more complicated operations in R.

This course is part of the Data Analysis in R career path. This course will build upon the skills and knowledge that you have acquired in the previous three courses.

At the end of the course, you’ll complete a portfolio project in which you’ll find the best markets for advertising an e-learning platform that combines your data science programming skills and the statistical skills you’ve learned in this course. It also serves as a portfolio project you can use to demonstrate the statistical skills that you’ll bring to the job for potential future employers.

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Once you complete this project, you’ll be able to showcase your data cleaning skills in your portfolio to prove to future employers you’ve got the skills needed to tackle working with messy data sets.

At the end of the course, you’ll put it all together to create a portfolio project and perform additional analysis through data visualization and correlation analysis to explore parents’, students’, …

Databases are everywhere. Databases are everywhere. Every day data and information flow in and out of databases. This SQL fundamentals course is a great place to start learning SQL. This course explains the interdependencies between databases and helps you learn new skills. This interactive course is suitable for all levels of SQL knowledge.

But that’s not the final challenge! Next, you’ll test your data cleaning skills by cleaning up after the Avengers. If you’re able to complete this challenge, you’ll dive into yet another guided project analyzing survey data to better understand Star Wars fans. In this project, you will get a chance to compute summary statistics and map column values in pandas.

When you’ve gotten through these …

Then, you’ll tackle more complex tasks like authenticating with private APIs, and submitting more complex requests.

In this course, you’ll learn the fundamentals of APIs, like how to connect to an open API, and how to interpret different status codes. You’ll also learn how to work with the JSON data format in R, since most data from APIs will be provided in JSON format.

Although there are many …

The course wraps up with a challenge that’ll get you more familiar with how web scraping can work across different sites. Then, you’ll dive into a guided project that’ll help you put your own unique spin on web-scraped data analysis.

Then, you’ll dig deeper into scraping, learning to use the CSS Selector to get precisely the data you want (and none of the other content or code you don’t).

In this …

At the end of the course, you’ll dive into a different data set and complete a portfolio project in which you’ll investigate Fandango Movie Ratings to see whether Fandango could be inflating movie ratings on its site. This project is a chance for you to combine the statistics skills you’ve learned in this course, and an opportunity to learn to identify and overcome common setbacks in practical …

We’ll start by teaching you how to identify and work with the various data types you’ll encounter in just about any data science role. Next, we’ll introduce you to new concepts like functions, operators, expressions, and control flow, and we’ll show you how to use them to optimize your work in a database.

This is the second course in our SQL Fundamentals skill path. In the previous course, you …

By the end of the course, you’ll understand the difference between theoretical and experimental probability. You’ll have experience calculating the probabilities for a variety of different events, and you’ll be able to calculate the number of permutations and combinations possible in experiment outcomes.

Finally, you’ll learn about counting techniques like permutations and combinations before …

At the end of the course, you’ll complete a portfolio project in which you’ll work with Jeopardy data to analyze text, searching for winning Jeopardy strategies. It’s a chance for you to combine the skills you learned in this course, and when you finish it you’ll have a fascinating project to showcase in your portfolio and an interesting conversation starter for data science networking — who …

You’ll learn how to select appropriate features for your linear regression model to yield the best performance. You’ll also learn concepts such as gradient descent, an optimization algorithm used to minimize a function by iteratively moving in the direction of steepest descent. And you’ll learn how to fit a model using the Ordinary Least Squares (OLS) algorithm, understand why OLS works, and …

You’ll also learn how to handle missing values in your data, a critical part of almost every data analysis project. Rather than dropping rows or columns, which reduces the amount of data you have to work with, you’ll learn statistical techniques to impute missing data, and you’ll also learn how to insert data from outside sources.

Then you’ll dive into map and anonymous functions, two …

At the end of the course, you’ll complete a portfolio project in which you’ll work with Jeopardy data to analyze text, searching for winning Jeopardy strategies. It’s a chance for you to combine the skills you learned in this course, and when you finish it you’ll have a fascinating project to showcase in your portfolio and an interesting conversation starter for data science networking — who …

In our Introduction to Machine Learning With R course, you will learn the basics about machine learning. We'll cover concepts such as K-Nearest Neighbors Algorithms, (KNN), and talk about error metrics like the Mean Squared Error and Root Mean Squared Error. Hyperparameter optimization optimizes machine learning algorithms to increase their accuracy and performance. To test your model more …

In this course we’ll dive into advanced SQL concepts like aggregate functions and summary statistics. These concepts are key in helping learners perform a variety of useful functions to gain insights from extensive datasets.

In SQL, summary functions are used to summarize data in different groups based on specific criteria that have previously been defined by a set of expressions. By summarizing …