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    • Home
    • IBM
    • Courses
    • Tools for Data Science

    Tools for Data Science

    BY
    IBM via Coursera

    Learn most popular data science tools and their features by enrolling in the Tools for Data Science offered by IBM on Coursera.

    Brochure Enquire
    • Overview
    • The highlights
    • Fee
    • Eligibility criteria
    • What you will learn
    • Admission Details
    • The syllabus
    • Scholarship
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    Lavel

    Beginner

    Mode

    Online

    Duration

    2 Weeks

    Quick facts

    particular details
    Medium of instructions English
    Mode of learning Self study
    Mode of Delivery Video and Text Based
    Learning efforts 10 Hours Per Week

    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.

    The highlights

    • Data science programme
    • Enrol for free
    • Shareable certificate 
    • Digital badges
    • 100% online medium
    • Graded quizzes and assignments
    • Flexible deadlines
    • Beginner-friendly course 
    • Offered by IBM
    • Hands-on projects
    • Subtitles in multiple languages
    • Financial aid is provided

    Program offerings

    • Enrol for free
    • Shareable certificate
    • Data science course
    • Digital badges
    • Flexible deadlines
    • Professional course
    • Beginner level
    • 100% online
    • Multiple language subtitles
    • Quizzes
    • Graded assignments
    • Financial aid available
    • Extra readings.

    Course and certificate fees

    The fees for course Tools for Data Science is :


    Certification 

    Amount

    Tools for Data Science (Audit)

    Free

    Tools for Data Science - 1 month

    Rs.1,683

    Tools for Data Science - 3 months

    Rs.3,384

    Tools for Data Science- 6 months

    Rs.5,051

    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

    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. 

    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
    • Model Development
    • Summary: Open Source Tools for Data Science
    • Module 1 Summary
    Assignments
    • Graded Quiz - Data Science Tools
    • Practice Quiz: Introduction to Data Science Tools
    • Practice Quiz: Commercial and Cloud-Based Data Science Tools
    Plugins
    • Open source tool board

    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
    • Machine Learning Models – Learning from Models to Make Predictions
    • The Model Asset eXchange
    Reading
    • Additional Sources of Datasets
    • Hands on Lab: Getting Started with Open Source Datasets and Deep Learning Models
    • Module 3 Summary
    assignments
    • Practice Quiz - Libraries, APIs, Data Sets, Models
    • Graded Quiz - Libraries, APIs, Data Sets, Models

    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
    • (Optional): Hands-on Lab: Download & Install Anaconda on Windows
    • Jupyter Notebooks on the Internet
    • Module 4 Summary
    assignments
    • 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

    Module 5: RStudio & GitHubModule 5: RStudio & GitHub

    Readings
    • [Optional] Download & Install R and RStudio
    • Hands-on Lab: Getting Started with GitHub
    • Hands-On Lab: Branching and Merging (Web UI)
    • Module 5 Summary
    • Glossary
    assignments
    • Practice Quiz - RStudio
    • Practice Quiz - GitHub
    • Graded Quiz - RStudio & GitHub

    Module 6: Final project and submission

    readings
    • Final Project Overview
    • Final Project Submission Guidelines and Deliverables
    assignment
    • Final Exam
    app items
    • Hands-on Lab: Create your Jupyter Notebook•60 minutes
    • AI Graded: Final Project - Submission and Evaluation

    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

    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.

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