Course HighlightsCOURSE
Data Science Hands-On with Open Source Tools

Data Science Hands-On with Open Source Tools

Explore popular data science tools. Discover their features and learn how to use them. Become familiar with Jupyter Notebooks, RStudio IDE, and Zeppelin Notebooks.

Gain practical experience through project work and build valuable knowledge for a rewarding career in data science.

Data Science Hands-On with Open Source Tools Highlights

  Course duration

Duration

  • 4 weeks
    1-2 hours/week
  Course Fee

Fee

US$ 99 - US$ 199

Course duration

Duration

  • 4 weeks
    1-2 hours/week
Course Fee

Fee

US$ 99 - US$ 199

Data science is a blend of programming tools, statistical analysis, algorithms, and machine learning principles. It involves the use of multiple approaches including statistics, scientific methodologies, artificial intelligence (AI), and data analysis. A data scientist will utilize all these instruments to then discover meaningful patterns hidden in raw data.

In this course, you will learn about key tools used in data science, including Jupyter Notebooks, RStudio IDE, and Zeppelin Notebooks. You will discover what each tool is used for, what programming languages they can execute, and what their features and limitations are. Using tools hosted in the cloud, you will then learn how to test each tool and run simple code in Python or R.

If you’re keen to pursue a career in the world of data science, this course on data science tools will introduce you to some critical technologies. Plus, it will provide you with important knowledge you need to progress through the remaining courses of the IBM Data Science Foundation Certificate to enable you to earn professional certification.

This course comprises four purposely designed modules that take you on a carefully defined learning path. If you are thinking about taking the course separately, it is worth noting that it is part of the IBM Data Science Foundation Certificate Program and you may want to consider enrolling for the whole program rather than just enrolling for one course at a time.

It is a self-paced course, which means it is not run to a fixed schedule with regard to completing modules or submitting assignments. To give you an idea of how long the course takes to complete, it is anticipated that if you work 1-2 hours per week, you will complete the course in 4 weeks. However, as long as the course is completed before the end date, you can work at your own pace.

The materials for each module will become available when you start the particular module. Methods of learning and assessment will include videos, reading material, and online exam questions.

Once you have successfully completed the course, you will earn your IBM Certificate.

As part of our mentoring service you will have access to valuable guidance and support throughout the course. We provide a dedicated discussion space where you can ask questions, chat with your peers, and resolve issues. Depending on the payment plan you have chosen, you may also have access to live classes and webinars, which are an excellent opportunity to discuss problems with your mentor and ask questions. Mentoring services may vary package wise.

After completing this course, you will have:

  • Introductory knowledge of the languages and tools used in data science.
  • An understanding of common open source tools used to perform data science tasks.
  • An introductory understanding of IBM tools for data science.
  • Individuals looking to extend their introductory knowledge of data science.
  • Individuals who would like to explore the tools and technologies used in data science.
  • Invididuals who would like to begin understanding how to use a particular data science approach in their work.

No prerequisites are required for taking this course.

Course Outline

General Information
Learning Objectives
Syllabus
Grading Scheme
Certificate Information
Change Log
Copyrights and Trademarks
Learning Objectives
What is Skills Network Labs? (4:36)
Account features (4:44)
Creating an account (1:04)
Lab - Getting Started with the Data Science Tools
Graded Review Questions
Learning Objectives
What are Jupyter Notebooks? (0:56)
Getting started with Jupyter (4:30)
Lab - Getting Started with Jupyter Notebooks
Graded Review Questions
Learning Objectives
What are Zeppelin Notebooks? (2:33)
Zeppelin for Scala (3:03)
Getting started with Zeppelin (5:37)
Managing your Interpreters in Zeppelin (2:52)
Apache Spark in Zeppelin Notebooks (2:57)
Lab - Getting Started with Apache Zeppelin
Graded Review Questions
Learning Objectives
What is RStudio IDE? (1:45)
Uploading files, Installing packages and loading libraries in RStudio IDE (3:10)
Getting started with RStudio IDE (4:08)
RStudio Environment and History (3:05)
Apache Spark in RStudio IDE (4:18)
Lab - Getting Started with RStudio IDE
Graded Review Questions
Course Certificate

Earn your certificate

Once you have completed this course, you will earn your certificate.

Preview digital certificate
Data Science Hands-On with Open Source Tools