We may earn an affiliate commission when you visit our partners.
Course image
Google Cloud Training, Romeo Kienzler, Alex Aklson, Rav Ahuja, Hima Vasudevan, Polong Lin, Svetlana Levitan, Sandip Saha Joy, and Aije Egwaikhide

Interested in learning more about data science, but don’t know where to start? This 4-course Specialization from IBM will provide you with the key foundational skills any data scientist needs to prepare you for a career in data science or further advanced learning in the field.

Read more

Interested in learning more about data science, but don’t know where to start? This 4-course Specialization from IBM will provide you with the key foundational skills any data scientist needs to prepare you for a career in data science or further advanced learning in the field.

This Specialization will introduce you to what data science is and what data scientists do. You’ll discover the applicability of data science across fields, and learn how data analysis can help you make data driven decisions. You’ll find that you can kickstart your career path in the field without prior knowledge of computer science or programming languages: this Specialization will give you the foundation you need for more advanced learning to support your career goals.

You’ll grasp concepts like big data, statistical analysis, and relational databases, and gain familiarity with various open source tools and data science programs used by data scientists, like Jupyter Notebooks, RStudio, GitHub, and SQL. You'll complete hands-on labs and projects to learn the methodology involved in tackling data science problems and apply your newly acquired skills and knowledge to real world data sets.

In addition to earning a Specialization completion certificate from Coursera, you’ll also receive a digital badge from IBM recognizing you as a specialist in data science foundations.

This Specialization can also be applied toward the IBM Data Science Professional Certificate.

Enroll now

Share

Help others find Specialization from Coursera by sharing it with your friends and followers:

What's inside

Four courses

What is Data Science?

(0 hours)
Do you want to know why data science has been labeled the sexiest profession of the 21st century? This course introduces data science, its applications, and career paths in the field. Data science uses machine learning and deep learning to find patterns in data and make data-driven conclusions and predictions.

Tools for Data Science

(0 hours)
In order to be successful in Data Science, you need to be skilled with using tools that Data Science professionals employ. This course teaches you about the popular tools in Data Science and how to use them.

Data Science Methodology

(0 hours)
If there is a shortcut to becoming a Data Scientist, then learning to think and work like a successful Data Scientist is it. In this course, you will learn and then apply this methodology that you can use to tackle any Data Science scenario. You’ll explore two notable data science methodologies, Foundational Data Science Methodology, and the six-stage CRISP-DM data science methodology, and learn how to apply these data science methodologies.

Databases and SQL for Data Science with Python

(0 hours)
Working knowledge of SQL is a must for data professionals. Much of the world's data resides in databases. SQL is a powerful language used for communicating with and extracting data from databases. In this course, you will learn SQL inside out—from the very basics of Select statements to advanced concepts like JOINs.

Learning objectives

  • Describe what data science and machine learning are, their applications & use cases, and various types of tasks performed by data scientists  
  • Gain hands-on familiarity with common data science tools including jupyterlab, r studio, github and watson studio 
  • Develop the mindset to work like a data scientist, and follow a methodology to tackle different types of data science problems
  • Write sql statements and query cloud databases using python from jupyter notebooks

Save this collection

Save Introduction to Data Science to your list so you can find it easily later:
Save
Our mission

OpenCourser helps millions of learners each year. People visit us to learn workspace skills, ace their exams, and nurture their curiosity.

Our extensive catalog contains over 50,000 courses and twice as many books. Browse by search, by topic, or even by career interests. We'll match you to the right resources quickly.

Find this site helpful? Tell a friend about us.

Affiliate disclosure

We're supported by our community of learners. When you purchase or subscribe to courses and programs or purchase books, we may earn a commission from our partners.

Your purchases help us maintain our catalog and keep our servers humming without ads.

Thank you for supporting OpenCourser.

© 2016 - 2024 OpenCourser