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Data Science Hands-On with Open Source Tools
Course
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.
Flexible Schedule
Beginner Level
Mentor Support
Estimated Time
4 weeks
1-2 hours/week
1-2 hours/week
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.
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
Instructions
Final Exam
Certificate
Why Learn with SkillUp Online?
We believe every learner is an individual and every course is an opportunity to build job-ready skills. Through our human-centered approach to learning, we will empower you to fulfil your professional and personal goals and enjoy career success.
Reskilling into tech? We’ll support you.
Upskilling for promotion? We’ll help you.
Cross-skilling for your career? We’ll guide you.
Personalized Mentoring & Support
1-on-1 mentoring, live classes, webinars, weekly feedback, peer discussion, and much more.
Practical Experience
Hands-on labs and projects tackling real-world challenges. Great for your resumé and LinkedIn profile.
Best-in-Class Course Content
Designed by the industry for the industry so you can build job-ready skills.
Job-Ready Skills Focus
Competency building and global certifications employers are actively looking for.
FAQs
The domain of data science has a bright future. Its prospects are extremely promising as a result of the growing number of fields in which it can be applied. Data science, together with artificial intelligence and machine learning, are already contributing to a better level of intelligent decision-making for organizations and this will continue into the future.
The use of data analysis tools enables businesses to gain insights from customer data as well as find trends and patterns. This in turn enables them to make more informed business decisions. They use these tools to perform simple or more complicated forms of data analysis.
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 their features and limitations. You will then learn how to test each tool and run simple code in Python or R using tools hosted in the cloud.
This course comprises four purposely designed modules that take you on a carefully defined learning path.
Yes, this is a mentored course. 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 according to your chosen package.
This course is fully online. All you need is a good connection to the internet to access the course material that will be in the form of articles, videos, and knowledge checks.You are not required to attend any classes in person.
Type of certificate
IBM Certificate
About this course
4 Modules
3 Skills
Includes
Discussion space
4 Hands-on labs
4 Quizzes
Exercises to explore
Jupyter Notebooks
Zeppelin Notebooks
R Studio
This course has been created by
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