Data Science Tools by IBM via Edx: Fee, Duration, How to Apply

Quick Facts

particular	details
Medium of instructions English	Mode of learning Self study	Mode of Delivery Video and Text Based	Learning efforts 3-7 Hours Per Week

Course overview

The Data Science Tools certification course from IBM provides you with a background on popular data science and data visualisation tools, including RStudio IDE, Jupyter Notebooks, and Watson Studio. Learn about the proper usage of each tool and how data scientists utilise these tools today. You will also get to understand what programming languages the data science tools can execute and what limitations and features they possess.

The seven-week-long Data Science Tools programme is introductory and belongs to the Data Analysis and Statistics domain. Besides, the tools will be hosted in the cloud, and you will learn to follow instructions and test the tools to run simple code in R or Python. For finishing the training, you will complete a final project on IBM Watson Studio with a Jupyter Notebook on Cloud.

Moreover, you must demonstrate your expertise in writing Markdown, preparing a notebook, and sharing your work with peers. This hands-on Data Science Tools training will familiarise you with some of the most in-use, greatest, and latest data science tools. The course curriculum, divided into six modules, allows you to learn through lab sessions, assignments, graded quizzes, practice exercises, and more.

Learners may choose any track from the two mentioned ones: audit and verified. These tracks are self-paced and offer limited and unlimited accessor audit and verified tracks respectively.

Course and certificate fees

Type of course

Free

For the Data Science Tools live certificate, you must opt for the verified track by paying the required fees. However, auditing the training materials for free is also an option if you are not interested in the certificate.

Data Science Tools fee structure

Course Name	Fees
Data Science Tools - without certificate	FREE
Data Science Tools – Certificate	Rs. 8,267

certificate availability

Yes

certificate providing authority

IBM

certificate fees

₹8,229

Who it is for

Applicants who pursue becoming Data Scientist.

What you will learn

Data science knowledge Knowledge of data visualization

As you finish the Data Science Tools certification syllabus, you will become proficient in the following tasks:

Using various data visualisation and Data science course hosted on the Skills Network Labs
Popular tools frequently utilised by R Programmers like the RStudio IDE
Using Jupyter Notebooks and understanding its basic and advanced features to explore why it's so popular
IBM Watson Studio and its capabilities, limitations, and features
Creating and sharing a Jupyter Notebook

The syllabus

Welcome

Video: Course Introduction
General Information
Learning Objectives and Syllabus
Grading Scheme
Learning goals for the course

Module 1: Overview of Data Science Tools

Module Introduction and Learning Objectives
Video: Categories of Data Science Tools
Video: Open Source Tools for Data Science - Part 1
Video: Open Source Tools for Data Science - Part 2
Open source story Board
Video: Commercial Tools for Data Science
Video: Cloud Based Tools for Data Science
Reading: Module 1 Summary
Practice Quiz: Overview of Data Science Tools
Graded Quiz: Overview of Data Science Tools

Module 2: Languages of Data Science

Module Introduction and Learning Objectives
Video: Languages of Data Science
Video: Introduction to Python
Video: Introduction to R Language
Video: Introduction to SQL
Video: Other Languages for Data Science
Reading: Module 2 Summary
Practice Quiz: Languages
Graded Quiz: Languages of Data Science

Module 3: Packages, APIs, Datasets and Models

Module Introduction and Learning Objectives
Video: Libraries for Data Science
Video: Application Programming Interfaces (APIs)
Video: Data Sets - Powering Data Science
Video: Sharing Enterprise Data - Data Asset eXchange
Video: Machine Learning Models – Learning from Models to Make Predictions
Video: The Model Asset eXchange
Hands-on Lab: Explore Datasets and Models
Reading: Module 3 Summary
Practice Quiz: Libraries, APIs, Datasets and Model
Graded Quiz: Libraries, APIs, Datasets and Models

Module 4: Jupyter Notebooks and JupyterLab

Module Introduction and Learning Objectives
Video: Introduction to Jupyter Notebooks
Video: Getting Started with Jupyter
Hands-on Lab: Getting Started with Jupyter Notebooks
Video: Jupyter Kernels
Hands-on Lab: Using Markdown in Jupyter Notebooks
Video: Jupyter Architecture
Hands-on Lab: Working with Files in Jupyter Notebooks
Video: Additional Anaconda Jupyter Environments
Video: Additional Cloud Based Jupyter Environments
(Optional) : Hands-on Lab: Download & Install Anaconda on Windows
Reading: Jupyter Notebooks on the Internet
Reading: Module 4 Summary
Practice Quiz: Jupyter Notebooks and Jupyter Lab
Graded Quiz - Jupyter Notebooks and JupyterLab

Module 5: RStudio & GitHub

Module Introduction and Learning Objectives
Video: Introduction to R and RStudio
Optional Reading: Download & Install R and RStudio
Hands on Lab: R Basics with RStudio
Video: Plotting in RStudio
Reading: Getting started with RStudio and Installing packages
Hands on Lab: Creating Data Visualizations using ggplot
Hands-on Lab: Plotting with RStudio
Video: Overview of Git/GitHub
Video: Introduction to GitHub
Video: GitHub Repositories
Video: GitHub - Getting Started
Hands-on Lab: Getting Started with GitHub
Video: GitHub Branches
Video: GitHub - Working with Branches
Hands-On Lab: Branching and Merging (Web UI)
[Optional] Hands-on Lab: Getting Started with Branches using Git Commands
Reading: Module 5 Summary
Reading: Glossary
Practice Quiz - RStudio
Practice Quiz - GitHub
Graded Quiz - RStudio & GitHub

Module 6: Create and Share Your Jupyter Notebook

Module Introduction and Learning Objectives'
Final Assignment Instructions: Create and Share Your Jupyter Notebook
Hands-on Lab: Create your Jupyter Notebook
Submit Your Work and Grade Your Peers
Final Exam

Course Wrap-Up

Thanks from the Course Team
Copyright and Trademarks

Course Rating

Course Rating and Feedback

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Module 7: [Optional] Bonus Module

Reading: Module Introduction and Learning Objectives
Video: Introduction to Watson Studio
Video: Optional: Creating an account on IBM Watson Studio
Obtain IBM Cloud Feature Code and Activate Trial Account
Video: Jupyter Notebooks in Watson Studio - Part 1
Video: Jupyter Notebooks in Watson Studio - Part 2
Reading: Creating a Watson Studio Project with Jupyter Notebooks
Video: Linking GitHub to Watson Studio
Reading: Assignment using Watson Studio
Reading: Module 7 Summary
Practice Quiz - Watson Studio

Admission details

Step 1: The Data Science Tools online course page is accessible here: https://www.edx.org/learn/data-science/ibm-data-science-tools

Step 2: Peruse programme details, certificate information, and syllabus. After you’re done, choose a session and click on the red-coloured ‘Enroll Now’ option.

Step 3: You can either access the verified track or pick the free audit option.

Step 4: If you are an owner of an edX account, simply use your credentials to log in. In case you don’t have an account, you can start your account by providing your personal/professional email address or any other social credentials.

Step 5: As you create your account or sign in, you will successfully register for the training.

Filling the form

To enrol in the Data Science Tools classes course, if you are creating an edX profile, you'll have to provide your name, email address, and country of residence. Generate a unique password and username for future sessions. Besides your Microsoft or Apple credentials, Google credentials or your Facebook account can also help you sign in.

How it helps

The Data Science Tools course benefits those in the domain of Data Analysis and Statistics and wishes to master the data visualisation and data science tools. With a hands-on approach, the training teaches you to use these tools hosted on Skills Network Labs. Besides, you will know how to create and share a Jupyter Notebook.

The edX Data Science Tools certificate also enhances your employment prospects, and you will learn directly from the experts at IBM.

Instructors

Mr Romeo Kienzler
Data Scientist
IBM

Other Masters

Ms Svetlana Levitan
Senior Developer
IBM

M.S, Ph.D

Ms Maureen McElaney
Developer Advocate
IBM

FAQs

What does the online Data Science Tools certificate look like?

It will comprise your instructors’ signatures, your name, edX logo, partner university logo, unique certification ID, and the Data Science Tools course name.

Who will teach the Data Science Tools certificate programme?

The Data Science Tools online course is mentored by Romeo Kienzler, who is the Chief Data Scientist at IBM; Svetlana Levitan, who is the Senior Developer Advocate with IBM Center.