Free Data Analysis Course: Python, SQL, and R

Learn data analysis with this free course covering statistics, data wrangling, and visualization by an Airbnb/MIT alum.

25
Resources
92+
Hours
About this free data analysis course:
This free course teaches some of the most important techniques and tools necessary to manipulate and analyze large datasets. You'll learn how to use statistics, programming, and machine learning models to produce data-driven insights—and find out how to communicate your results with data visualizations.
Exploratory and predictive statistics, and R for statistical analysis
Basic computer programming in Python
Introductory algorithms and practical machine learning techniques
Software design and version control using Unix and Git
Data visualization best practices
Big data manipulation using Hadoop and MapReduce
Data Analysis with Python, SQL, and R

This course provides a short but intensive introduction to data analytics, divided into three parts:

  • In part 1, we learn general programming practices (software design, version control) and tools (Python, SQL, Unix, and Git).
  • In part 2, we learn R and focus more narrowly on data analysis, studying statistical techniques, machine learning, and presentation of findings.
  • Part 3 includes a choice of elective topics: visualization, social network analysis, and big data (Hadoop and MapReduce). Choose from any or all of them to enrich your understanding and skills.

There will be a capstone project at the end that you can use to demonstrate your skills to potential employers or for a school application. This is an intensive course with a lot of material to learn, but at the end, you will know all the tools and techniques you need to start analyzing data: how to manipulate data, apply statistical and machine learning techniques, and visualize results. You'll be prepared to begin a career in data analysis.

Why learn data analytics?

Data analysis is both a fascinating topic in itself and a tool that lets you make powerful inferences and understand the world around you. The techniques you will learn will help you accurately characterize data using models and then make inferences and decisions. If you enjoy applying math and analytical thinking to practical problems, this course is for you. Being able to find trends in large datasets will help you know how to make sound decisions in all aspects of your life.

What will you learn in this free data analytics course?

This free course teaches some of the most important techniques and tools necessary to manipulate and analyze large datasets and summarize conclusions. This includes:

  • exploratory and predictive statistics
  • basic computer programming in Python
  • more advanced computer program design
  • an introduction to algorithms
  • R for statistical analysis
  • practical machine learning techniques
  • Unix and Git
  • data visualization best practices

Finally, there are three optional elective tracks: Visualizing Data, Analyzing Social Networks, and Big Data: Hadoop and MapReduce. Analytics and data science are enormous and burgeoning fields with many areas of study, and we will not have time to cover them all. In the interest of getting you analyzing real datasets as quickly as possible, the emphasis in this path is on practical application as opposed to theory. Furthermore, while significant math is required in this path, we will not be covering the theoretical basis for statistics or machine learning. The focus will be on analysis and manipulation of data rather than setup and storage. Some advanced statistics topics such as time series and Bayesian methods will not be studied in this path. Finally, some specific topics such as natural language processing and computer vision will not be covered.

Who is this data analytics course for?

1
Working professionals who have want to incorporate data driven projects into their line of work.
2
Someone who has read our blog or watched tutorials and wants to dive into more specific subject matter.
3
Students who are about to graduate their secondary or post secondary education, and want to understand the basics of a new skillset quickly.
4
Aspiring analysts, operators, or entrepreneurs who want to transition into a tech career, but aren't sure where to start.

Frequently Asked Questions

What are the prerequisites for this data analysis course?

The course is available to anyone interested in learning foundational data analysis skills. While welcoming to beginners, an introductory statistics and/ or programming class will come in handy, but is not necessary. Basic familiarity with calculus and general computer competency is assumed.

Can I get a job after taking this free data analysis course?

While this course introduces many foundational analysis concepts, this course alone will not get you job ready. Luckily, our Data Analytics Career Track was created for anyone looking to transition into a data career. If you’ve validated your interest in pursuing a data further, see if mentorship through our Intro to Analytics course is right for you.


Is this course suitable for beginners?

Yes! This course was designed for the curious and driven beginner.

Is data analysis easy to learn?

Many students discover that data analysis is as much an art as it is a science, and it can be difficult to apply your learnings to new projects. While this course teaches the fundamentals, it’s important to get feedback from your peers along the way.

Ready to advance your career?