- 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
Beginner
Online
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
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
certificate providing authority
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
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
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
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
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.
You can complete the Tools for Data Science certification programme in approximately 18 hours.
The free trial period is for seven days only.
The videos will be available in English, with subtitles in multiple languages.
Yes, the subtitles are available in multiple languages, including German, Spanish, French, European Portuguese, Italian, Vietnamese, Russian, and more.
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