Data Science Tools Course at IBM

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.

The highlights

Professional certificate programme from IBM
Introductory level study
Seven-week training
Three to seven hours (per week)
Self-paced education
Expert instructors from IBM
Purchasable verified certificate
Course in Data Analysis and Statistics

Program offerings

Professional certificate programme from ibm
Introductory level study
Seven-week training
Three to seven hours (per week)
Self-paced education
Expert instructors from ibm
Purchasable verified certificate
Course in data analysis and statistics

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. 7,411

certificate availability

Yes

certificate providing authority

IBM

certificate fees

₹7,411

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

Admission details

Step 1: The Data Science Tools online course page is accessible here: https://www.edx.org/course/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.

The syllabus

About this course

Learning Objectives and Syllabus
General Information
Introduction to Tools for Data Science
Grading Scheme

Module 1

Data Scientist's Toolkit

Introduction to Python
Languages of Data Science
Introduction to SQL
Other Languages
Introduction to R Language
Languages: Practice Quiz
Part 1: Open Source Tools for Data Science
Categories of Data Science Tools
Part 2: Open Source Tools for Data Science
Cloud-Based Tools for Data Science
Commercial Tools for Data Science
Practice Quiz - Tools
Application Programming Interfaces (API)
Libraries for Data Science
Sharing Enterprise Data – Data Asset eXchange
Data Sets - Powering Data Science
The Model Asset Exchange
Machine Learning Models
Packages, Data Sets, APIs, Models: Practice Quiz
Explore Data Sets and Models: Lab
Graded Quiz: Module 1

Module 2

Open Source Tools

Plotting in RStudio
Introduction to R and RStudio
RStudio – Get started in RStudio: Lab
Plotting in RStudio: Lab
RStudio: Practice Quiz
GitHub - Getting Started
Overview of Git/GitHub
Getting Started with GitHub: Lab
Working with Branches: GitHub
Branching, Merging and Pull Requests on GitHub: Lab (Optional)
Git and GitHub via command line: Lab (Optional)
Git and GitHub via command line (Optional)
Jupyter Kernels
Branching and merging via command line (Optional)
Branching and merging via command line: Lab 2 (Optional)
Contributing to repositories via pull request (Optional)
Contributing to repositories via pull request: Lab 3 (Optional)
GitHub: Practice Quiz
Getting Started with Jupyter
Jupyter Notebooks - The Basics: Lab
Introduction to Jupyter Notebooks
Jupyter Architecture
Jupyter Notebooks - More Features: Lab
Jupyter Notebooks on the Internet: Reading
Jupyter Notebooks - Advanced Features: Lab
Jupyter Notebooks: Practice Quiz -
Module 2 - Graded Quiz

Module 3

IBM Tools for Data Science section

Watson Studio Introduction
What is IBM Watson Studio?
Jupyter Notebooks in Watson Studio - Part 1
Create an Account on IBM Watson Studio
Jupyter Notebooks in Watson Studio - Part 2
Linking GitHub to Watson Studio
Create a Watson Studio Project with Jupyter Notebooks: Lab
IBM Watson Knowledge Catalog
Practice Quiz - Watson Studio
IBM SPSS Modeler
SPSS Modeler Flows in Watson Studio
Data Refinery
Modeler Flows in Watson Studio (1hr): Lab
IBM SPSS Statistics
Auto AI in Watson Studio
Model Deployment with Watson Machine Learning
IBM Watson OpenScale
Other IBM Tools: Practice Quiz
Module 3 - Graded Quiz

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.

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.

Can I take this course with my co-workers?

Yes. Refer to the link for more info: https://business.edx.org/?lead_source=edX+Course+Page&utm_campaign=B2B+Container&utm_source=Referral.

Where can I showcase my verified edX certificate?

Since the certification is shareable, you can link it to your CV/resume, put it on your LinkedIn profile, share it on social media, etc.

What’s the Data Science Tools online course duration?

The programme is a seven-week course.