# Start your data science education with the Data Science Fundamentals Learning Path

You: 4 courses for 18 hours + 2 IBM badges = bragging rights

The hardest step in any endeavour is when you have no idea how to begin. This article describes a short, straightforward learning path to begin building your data science skills. The recently launched Data Science Fundamentals Learning Path at Big Data University guides you through short no-charge online courses that prepare you to earn your IBM Data Science Foundations Level 1 and Level 2 badges to show off your new skills!

Whether your background is computer science, psychology, statistics, English, or anything else, analyzing and understanding data is a valued skill that can position you well in your current or next job. And it's never too early to start. Increasingly, primary schools are introducing students to concepts and tools to prepare them for early job and entrepreneur opportunities. The data science profession has gained a lot of momentum, and it has become the leading job in many surveys in terms of salaries (see Related Topics below).

## About Big Data University

Big Data University is an IBM community initiative that started in 2010. With more than 500,000 registered learners, Big Data University provides comprehensive learning paths in the areas of data science, big data, and analytics to nurture a community of skilled, open-source data professionals. Moreover, each learning path in BDU offers an IBM badge after passing the first course in the path.

BDU courses are short by design. They follow the "5 x 5" rule:

- Learning paths cannot have more than 5 courses.
- Courses cannot be more than 5 hours.
- Courses cannot have more than 5 modules.
- Modules cannot have more than 5 videos.
- Videos cannot be more than 5 minutes.

This structure is ideal for a busy person like you who wants to learn small chunks of the material at your own pace. It also forces BDU instructors to present material in a compact way.

Now get started with Big Data University on this simple, no-charge data science learning path!

## Introducing the Data Science Fundamentals Learning Path courses

The Data Science Fundamentals Learning Path at Big Data University includes the following four courses, as shown in Figure 1:

- Data Science 101 (3 hours) plus earn your Data Science Foundations Level 1 badge
- Data Science Methodology (5 hours)
- Data Science Hands-on with Open Source Tools (5 hours)
- R 101 (5 hours) plus earn your Data Science Foundations Level 2 badge

##### Figure 1. The flow of the Data Science Fundamentals Learning Path

## Diving into the course details

Read more about each of the courses.

### Data Science 101 (3 hours)

Using an interview-style approach, this course teaches you the history and basics of data science. Taking Data Science 101 is like watching a documentary or movie trailer. This course is one of the most popular ones in BDU with more than 10,000 learners registered only one month after publication!

So sit back, relax, take the course, and get your first Data Science Foundations Level 1 IBM badge! Add the badge to your CV, and share it on LinkedIn and other social media sites.

### Data Science Methodology (5 hours)

Once you have a solid understanding of what data science is and what kind of problems it can help solve, this second course teaches you a formal methodology to work in data science. Let's not kid ourselves: some of the data science topics can be very dry. Senior IBM Data Scientist John Rollins developed this course in an interactive way to keep you engaged and awake!

### Data Science Hands-on with Open Source Tools (5 hours)

In this third course in the learning path, things get more interesting and practical. Using the Data Scientist Workbench (DSWB), IBM's integrated, cloud-based learning platform for hands-on exercises, you can "do" data science right away. With the DSWB, you don't need to install any software. DSWB is a collection of open source tools, and it's completely free of charge. Spend 10% of your time setting up your environment and 90% doing data science instead of the other way around! This course describes common open source tools, including OpenRefine, Jupyter notebooks, Zeppelin notebooks, and RStudio. New tools are continually added to keep the content current. For example, you can now learn about Seahorse, which is a visual tool to work with machine learning for non-programmers.

### R 101 (5 hours)

You cannot call yourself a data scientist if you don't know how to code in at least one programming language. Python, Scala, and R are popular languages for data scientists. R is an open-source language created for statistics that has a large number of libraries contributed by the community. This course will give you a good interactive introduction to R.

After you complete all four courses in this learning path, you will receive the IBM badge Data Science Foundations – Level 2. Feel proud, and share it on LinkedIn!

## Conclusion

Invest a weekend on this learning path so that you can improve your qualifications to be hired in the data science field!

If you like the format, BDU offers more learning paths, including the following:

- Big Data Fundamentals
- Data Science for Business
- Hadoop Fundamentals
- Spark Fundamentals
- Scala Programming for Data Science
- Big Data Analytics

#### Downloadable resources

#### Related topics

- Help Wanted: Black Belts in Data
- The Supply and Demand of Data Scientists: What the Surveys Say
- Tracking the Data Science Talent Gap
- Full list of BDU courses
- Full list of BDU courses in Chinese