Explore popular data science tools. Discover their features and learn how to use them. Become familiar with Jupyter Notebooks, RStudio IDE, and Watson Studio.
Gain practical experience through project work and build valuable knowledge for a rewarding career in data science.
If you wish, you can enroll for the program also or enroll this course individually.
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 IBM Data Science Tools course, you will learn about key tools used in data science, including Jupyter Notebooks, RStudio IDE, and Watson Studio. 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. Plus, you will complete a final project with a Jupyter Notebook on IBM Watson Studio that will demonstrate your proficiency in preparing a notebook, writing Markdown, and sharing your work with your peers.
If youre keen to pursue a career in the world of data science, then this Data Science Tools course 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 Professional 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 Professional 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 4-5 hours per week, you will complete the course in 4-5 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 exams questions.
Once you have successfully completed the course, you will earn your IBM Data Science Tools 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 is an excellent opportunity to discuss problems with your mentor and ask questions. Mentoring services may vary package-wise.
You will have:
No prerequisites are required for taking this course.
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.
1-on-1 mentoring, live classes, webinars, weekly feedback, peer discussion, and much more.
Hands-on labs and projects tackling real-world challenges. Great for your resumé and LinkedIn profile.
Designed by the industry for the industry so you can build job-ready skills.
Competency building and global certifications employers are actively looking for.
IBM Certificate
04 Modules
06 Skills
Discussion space
13 Labs
11 Quizzes
42 Videos
01 Final assignment
Jupyter Notebook using IBM Watson Studio
RStudio
Jupyter Notebooks
GitHub
IBM Tools
Subscribe to get the latest tech career trends, guidance, and tips in your inbox.
You will discover how to use data science tools such as Jupyter Notebooks, RStudio IDE, and Watson Studio. You will learn what each tool is used for, what programming languages each one can execute, their features and limitations, and how data scientists use these tools today.
Yes, to complete the course you will create a final project with a Jupyter Notebook on IBM Watson Studio, on the cloud, and you will demonstrate your proficiency in preparing a notebook, writing Markdown, and sharing your work with your peers.
You will learn how to use Jupyter Notebooks, and you will discover key details about its features and why it's so popular. You will also learn to create and share a Jupyter Notebook.
Data Science Tools is a course that runs online. To access the course materials, you will need access to the internet.When youenrollfor thiscourse (please note, this course is also part of the IBM Data Science Professional Certificate, though you dont have to be enrolled on the program to take this course), you willfind you have access to the course materialsin your dashboard.You will therefore be able to see thecoursematerialsas soon as youenroll.
Yes, if you successfully complete this course, you will earn an IBM Data Science Tools Certificate.Please note, this courseispart of the IBM Applied Data Science Certificate Program, thus you will also be one step closer to obtaining IBM Data Science Professional Certification if that issomething you are seeking to achieve.
Data Science Tools has been developed as part of the IBM Data Science Professional Certificate Program. However, it is possible to enroll on this course without having enrolled on the program. You will gain an IBM Professional Certificate for this even if youre not enrolled on the full program. There are no prerequisites for enrolling onto the course.
IBM Certificate
04 Modules
06 Skills
Discussion space
13 Labs
11 Quizzes
42 Videos
01 Final assignment
Jupyter Notebook using IBM Watson Studio
RStudio
Jupyter Notebooks
GitHub
IBM Tools
Subscribe to get the latest tech career trends, guidance, and tips in your inbox.