About

In this Tools for Data Science course offered by Coursera in partnership with IBM, you'll become familiar with the Data Scientist’s tool kit which includes: Libraries & Packages, Data Sets, Machine Learning Models, Kernels, as well as the various Open source, commercial, Big Data and Cloud-based tools.

Overview

The Tools for Data Science course offered by Coursera in partnership with IBM, gives plenty of hands-on experience in order to develop skills for working with these Data Science Tools. With the tools hosted in the cloud on Skills Network Labs, you will be able to test each tool and follow instructions to run simple code in Python, R, or Scala.

What you will learn

In order to be successful in Data Science, you need to be skilled with using tools that Data Science professionals employ as part of their jobs. This course teaches you about the popular tools in Data Science and how to use them. Work with Jupyter Notebooks, JupyterLab, RStudio IDE, Git, GitHub, and Watson Studio. You will understand what each tool is used for, what programming languages they can execute, their features and limitations. Towards the end the course, you will create a final project with a Jupyter Notebook. You will demonstrate your proficiency preparing a notebook, writing Markdown, and sharing your work with your peers.

Programme Structure

Courses include:

Data Scientist's Toolkit

Open Source Tools

IBM Tools for Data Science

Final Assignment: Create and Share Your Jupyter Notebook

Key information

Duration

Part-time
- 1 days

Start dates & application deadlines

You can apply for and start this programme anytime.

Language

English

Delivered

Online

Self-paced

Campus Location

Mountain View, United States

Disciplines

Computer Sciences Data Science & Big Data Web Technologies & Cloud Computing View 417 other Short Courses in Web Technologies & Cloud Computing in United States

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Academic requirements

We are not aware of any specific GRE, GMAT or GPA grading score requirements for this programme.

English requirements

We are not aware of any English requirements for this programme.

Other requirements

General requirements

Beginner Level
Anyone can complete this course in a self-paced manner without any prior programming or Data Science experience.

Tuition Fees

Tuition fees are shown in and the most likely applicable fee is shown based on your nationality.

International Applies to you

Applies to you

Non-residents

Free
Out-of-State

Free

Additional Details

Audit: free access to course materials except graded items
Certificate: a trusted way to showcase your skills
A year of unlimited access with Coursera Plus $399

Funding

Coursera provides financial aid to learners who cannot afford the fee. Apply for it by clicking on the Financial Aid link beneath the "Enroll" button on the left. You'll be prompted to complete an application and will be notified if you are approved. You'll need to complete this step for each course in the Specialization, including the Capstone Project.

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Tools for Data Science Coursera