Tools for Data Science by IBM via Coursera: 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

Course overview

Some popular data science tools used today include JupyterLab, RStudio IDE, Jupyter Notebooks, Git, GitHub, and more. Tools for Data Science by Coursera will introduce you to these data science tools and their features.

The Tools for Data Science certification is a part of a series of certification programmes related to data science and can be applied to different specialisations. Over the period of seven weeks, you will learn 18 hours of content in the form of video lessons and will receive extra readings and quizzes. You will have to create a final project at the end of the programme to showcase your skills and proficiency.

The Coursera Tools for Data Science programme is offered by IBM. It is easy to comprehend as it is a beginner-level course with flexible deadlines. You can earn digital badges and a shareable certificate that will help you enhance your resume and can be shared on LinkedIn.

Course and certificate fees

The fees for course Tools for Data Science is -

Certification	Fee Amount in INR
Tools for Data Science (Audit)	Free
Tools for Data Science - 1 month	Rs.4,115 /- per month
Tools for Data Science - 3 months	Rs.2,743 /- per month
Tools for Data Science- 6 months	Rs.2,058 /- per month

certificate availability

Yes

certificate providing authority

Coursera

Eligibility criteria

You can achieve the certificate for Tools for Data Science training by completing the graded assignments and the curriculum.

What you will learn

Data science knowledge R programming Knowledge of python

The Tools for Data Science syllabus course will help you get familiar with these concepts:

Toolkits used in data science
Open source tools
Data science tools
Languages of data science
Introduction to Python and R languages

The syllabus

Module 1: Overview of Data Science Tools

Videos

Course Introduction
Categories of Data Science Tools
Open Source Tools for Data Science - Part 1
Open Source Tools for Data Science - Part 2
Commercial Tools for Data Science
Cloud Based Tools for Data Science

Readings

Learning goals for the course
Module 1 Summary
Model Development

Assignments

Practice Quiz - Data Science Tools
Graded Quiz - Data Science Tools

Plugins

Open source tool board
Summary: Open Source Tools for Data Science

Module 2: Languages of Data Science

Videos

Languages of Data Science
Introduction to Python
Introduction to R Language
Introduction to SQL
Other Languages for Data Science

Reading

Module 2 Summary

Assignments

Practice Quiz - Languages
Graded Quiz - Languages

Module 3: Packages, APIs, Datasets and Models

Videos

Libraries for Data Science
Application Programming Interfaces (APIs)
Data Sets - Powering Data Science
Sharing Enterprise Data - Data Asset eXchange
Machine Learning Models – Learning from Models to Make Predictions
The Model Asset eXchange

Reading

Module 3 Summary

Quizzes

Practice Quiz - Libraries, APIs, Data Sets, Models
Graded Quiz - Libraries, APIs, Data Sets, Models

Plugins

Additional Sources of Datasets
Reading: Getting started with the Model Asset eXchange and the Data Asset Exchange

Module 4: Jupyter Notebooks and JupyterLab

Videos

Introduction to Jupyter Notebooks
Getting Started with Jupyter
Jupyter Kernels
Jupyter Architecture
Additional Anaconda Jupyter Environments
Additional Cloud Based Jupyter Environments

Reading

Module 4 Summary

Quizzes

Practice Quiz - Jupyter Notebooks and Jupyter Lab
Graded Quiz - Jupyter Notebooks and JupyterLab

App Items

Hands-on Lab: Getting Started with Jupyter Notebooks
Hands-on Lab: Using Markdown in Jupyter Notebooks
Hands-on Lab: Working with Files in Jupyter Notebooks

Plugins

(Optional):Hands-on Lab: Download & Install Anaconda
Jupyter Notebooks on the Internet

Module 5: RStudio & GitHub

Videos

Introduction to R and RStudio
Plotting in RStudio
Overview of Git/GitHub
Introduction to GitHub
GitHub Repositories
GitHub - Getting Started
GitHub Branches
GitHub - Working with Branches

App Items

R Basics with RStudio
Getting started with RStudio and Installing packages
Creating Data Visualizations using ggplot
Plotting with RStudio
[Optional] Getting Started with Branches using Git Commands

Plugins

Optional Reading: Download & Install R and RStudio
Hands-on Lab: Getting Started with GitHub
Hands-On Lab: Branching and Merging (Web UI)

Module 5: RStudio & GitHubModule 5: RStudio & GitHub

Readings

Module 5 Summary
Glossary

Quizzes

Practice Quiz - RStudio
Practice Quiz - GitHub
Graded Quiz - RStudio & GitHub

Module 6: Create and Share your Jupyter Notebook

Module 7: [Optional] IBM Watson Studio

Videos

Introduction to Watson Studio
Optional: Creating an account on IBM Watson Studio
Jupyter Notebooks in Watson Studio - Part 1
Jupyter Notebooks in Watson Studio - Part 2
Linking GitHub to Watson Studio

Reading

Summary

Quiz

Practice Quiz - Watson Studio

App Item

(Optional)Obtain IBM Cloud Feature Code and Activate Trial Account

Plugins

Creating a Watson Studio Project with Jupyter Notebooks
Assignment using Watson Studio

Admission details

You can visit the Tools for Data Science page by clicking on the link here: https://www.coursera.org/learn/open-source-tools-for-data-science
Make sure you have signed up on Coursera and are logged into your account.
Next, you must click on the ‘Enroll for free’ option and choose the right programme.
After clicking on ‘Next’, you can start your free 7-day trial, audit the course, or pay the monthly fee to keep learning after that.

Filling the form

You just have to sign up on Coursera with your full name, email address and password for the Tools for Data Science classes certification course application form. After signing up, keep yourself logged in to your account and join any free course or avail of a free trial. To sign up, you can either use your Google or Facebook account. Else, create a Coursera account by providing your name, email address, and password.

Scholarship Details

Coursera offers financial aid for the Tools for Data Science online certification if you cannot pay the fee. You can use this aid to pay the course fee. To apply, click on 'financial aid available on the course page, fill the application form, and Coursera will review your application and reply in about two weeks.

How it helps

Data science plays a crucial role in the IT and corporate sector as it enables companies to interpret gigantic data from numerous sources and make better decisions. Top universities and companies have designed the Tools for Data Science programme to help you master data science tools and accelerate your career. The course also lets you apply your knowledge to create a final project and provides a certificate after that.

Besides, this certificate is shareable in the LinkedIn certifications section. You can enrol for free and go through the course material during your free trial period to decide whether you wish to buy the course. Upon completing this course and securing certification, you can advance your career in the IT and corporate sector.

Instructors

Ms Aije Egwaikhide
Senior Data Scientist
IBM

Other Bachelors, Other Masters

Ms Svetlana Levitan
Senior Developer
IBM

M.S, Ph.D

Mr Romeo Kienzler
Data Scientist
IBM

Other Masters

FAQs

What are the other courses in the data science specialisation?

Some of the other data science courses in this series include Introduction to Data Science Specialisation, IBM Data Science Professional Certificate, and Data Science Fundamentals with Python and SQL Specialisation.

How many hours will it take to finish the online Tools for Data Science live course?

You can complete the Tools for Data Science certification programme in approximately 18 hours.

How long is the free trial period for online Tools for Data Science classes programme ?

The free trial period is for seven days only.

What language is used in the video content for online Tools for Data Science certification programme?

The videos will be available in English, with subtitles in multiple languages.

Will there be subtitles in German and Spanish?

Yes, the subtitles are available in multiple languages, including German, Spanish, French, European Portuguese, Italian, Vietnamese, Russian, and more.