Course HighlightsCOURSE
Introduction to Data Science

Introduction to Data Science

Discover the world of data science, its applications and use cases. Explore key data science concepts including big data, data mining, machine learning, and deep learning.

Take this important first step towards a rewarding career in data science.

Introduction to Data Science Highlights

Course Enrollment

Starts on

15 June 2021

Enrollment closes on
31 December 2022

  Course duration

Duration

  • 6 weeks, online
    3-6 hours/week
  Course Fee

Fee

US$99 - US$199

Course Enrollment

Starts on

15 June 2021

Enrollment closes on
31 December 2022

Course duration

Duration

  • 6 weeks, online
    3-6 hours/week
Course Fee

Fee

US$99 - US$199

With the power of data science to hand, businesses are gleaning valuable insights that give them a competitive edge. Through the manipulation of large pools of data, data scientists are also presenting organizations with critical information that enables them to carve out a path to the future. Individuals building the necessary skills to excel in data science, therefore, are moving into an exciting field that offers an interesting and rewarding career.

In this course, you will learn about the fundamentals of data science and discover how organizations are using data science to solve problems. You will explore important concepts including big data, data mining, machine learning and deep learning, and you will look at use cases and applications of data science. Plus, you will learn from big data science professionals and practitioners how to start a career in this exciting field.

If you’re keen to take your first step in the world of data science, this Introduction to Data Science course will teach you the key concepts you need to move forward. Plus, it will provide you with the necessary foundation you need to progress through the remaining courses of the IBM Data Science Professional Certificate to enable you to earn professional certification.

This course comprises six purposely designed modules that take you on a carefully defined learning journey. If you are thinking about taking the course separately, it is worth noting that it is part of the IBM Data Science Professional Certificate Program and you may want to consider enrolling for the whole program rather than just enrolling for one course at a time.

It is a self-paced course, which means it is not run to a fixed schedule with regard to completing modules or submitting assignments. To give you an idea of how long the course takes to complete, it is anticipated that if you work 3-6 hours per week, you will complete the course in 6 weeks. However, as long as the course is completed by the end of your enrollment, you can work at your own pace. And don’t worry, you’re not alone! You will be encouraged to stay connected with your learning community and mentors through the course discussion space.

The materials for each module are accessible from the start of the course and will remain available for the duration of your enrollment. Methods of learning and assessment will include discussion space, videos, reading material, quizzes, exercise and final assignment.

Once you have successfully completed the course, you will earn your IBM Certificate.

As part of our mentoring service you will have access to valuable guidance and support throughout the course. We provide a dedicated discussion space where you can ask questions, chat with your peers, and resolve issues. Depending on the payment plan you have chosen, you may also have access to live classes and webinars, which are an excellent opportunity to discuss problems with your mentor and ask questions. Mentoring services may vary package wise.

You will:

  • Have a good understanding of the fundamentals of data science.
  • Have an understanding of how organizations are using data science to solve problems.
  • Have knowledge of use cases and the applications of data science.
  • Individuals looking for a good introduction to data science.
  • Individuals who would like to explore the tools and technologies used in data science.
  • Invididuals who would like to begin understanding how to apply a particular data science approach to their work.

    No prerequisites are required for taking this course.

 

Course Outline

General Information
Learning Objectives
Syllabus
Grading Scheme
Copyrights and Trademarks
Learning Objectives
Video : What is Data Science (2:29)
Fundamentals of Data Science (2:52)
Video : The Many Paths to Data Science (3:47)
Advice for New Data Scientists (2:50)
Data Science: The Sexiest Job in the 21st Century
Module Summary
Learning Objectives
A Day in the Life of a Data Scientist (3:45)
Old Problems, New Problems, Data Science Solutions (3:56)
Data Science Topics and Algorithms (3:53)
Cloud for Data Science (3:22)
What Makes Someone a Data Scientist
Module Summary
Learning Objectives
Foundations of Big Data (5:22)
How Big Data is Driving Digital Transformation (3:55)
What is Hadoop? (6:36)
Data Science Skills and Big Data (4:35)
Data Scientists at New York University (4:13)
Module Summary
Learning Objectives
How Data Science is Saving Lives (4:37)
How Companies Should Get Started in Data Science (2:52)
Applications of Data Science (3:38)
The Final Deliverable
Module Summary
Learning Objectives
How Can Someone Become a Data Scientist (5:19)
Recruiting for Data Science (7:32)
Careers in Data Science (2:51)
High School Students and Data Science Careers (4:52)
The Report Structure
Module Summary
Peer-graded Assignment: Final Assignment
Download your Certificate
Course Certificate

Earn your certificate

Once you have completed this course, you will earn your certificate.

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Introduction to Data Science