Data ScienceRelational Database Management System (RDBMS)Cloud DatabasesPython ProgrammingSQLIpython
Introduction to Data Science Specialization
Launch your career in data science. Gain foundational data science skills to prepare for a career or further advanced learning in data science.
Offered By
What you will learn
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
Skills you will gain
About this Specialization
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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.
Applied Learning Project
You will utilize tools like Jupyter, GitHub, R Studio, and Watson Studio to complete hands-on labs and projects throughout the Specialization. Using new skills and knowledge gained through the program, you’ll also work with real world data sets and query them using SQL from Jupyter notebooks.
Learner Career Outcomes
38%
Started a new career after completing this specialization.
20%
Got a pay increase or promotion.
Shareable Certificate
Earn a Certificate upon completion
100% online courses
Start instantly and learn at your own schedule.
Flexible Schedule
Set and maintain flexible deadlines.
Beginner Level
No prior experience required.
Approx. 4 months to complete
Suggested 4 hours/week
English
Subtitles: English, Arabic, French, Portuguese (European), Chinese (Simplified), Italian, Vietnamese, Korean, German, Russian, Turkish, Spanish, Persian
Learner Career Outcomes
38%
Started a new career after completing this specialization.
20%
Got a pay increase or promotion.
Shareable Certificate
Earn a Certificate upon completion
100% online courses
Start instantly and learn at your own schedule.
Flexible Schedule
Set and maintain flexible deadlines.
Beginner Level
No prior experience required.
Approx. 4 months to complete
Suggested 4 hours/week
English
Subtitles: English, Arabic, French, Portuguese (European), Chinese (Simplified), Italian, Vietnamese, Korean, German, Russian, Turkish, Spanish, Persian
There are 4 Courses in this Specialization
What is Data Science?
42,899 ratings
The art of uncovering the insights and trends in data has been around since ancient times. The ancient Egyptians used census data to increase efficiency in tax collection and they accurately predicted the flooding of the Nile river every year. Since then, people working in data science have carved out a unique and distinct field for the work they do. This field is data science. In this course, we will meet some data science practitioners and we will get an overview of what data science is today.
Tools for Data Science
20,298 ratings
What are some of the most popular data science tools, how do you use them, and what are their features? In this course, you'll learn about Jupyter Notebooks, RStudio IDE, Apache Zeppelin and Data Science Experience. You will learn about what each tool is used for, what programming languages they can execute, their features and limitations. With the tools hosted in the cloud on Cognitive Class Labs, you will be able to test each tool and follow instructions to run simple code in Python, R or Scala. To end the course, you will create a final project with a Jupyter Notebook on IBM Data Science Experience and demonstrate your proficiency preparing a notebook, writing Markdown, and sharing your work with your peers.
Data Science Methodology
15,441 ratings
Despite the recent increase in computing power and access to data over the last couple of decades, our ability to use the data within the decision making process is either lost or not maximized at all too often, we don't have a solid understanding of the questions being asked and how to apply the data correctly to the problem at hand.
Databases and SQL for Data Science
12,585 ratings
Much of the world's data resides in databases. SQL (or Structured Query Language) is a powerful language which is used for communicating with and extracting data from databases. A working knowledge of databases and SQL is a must if you want to become a data scientist.
Offered by
IBM
IBM offers a wide range of technology and consulting services; a broad portfolio of middleware for collaboration, predictive analytics, software development and systems management; and the world's most advanced servers and supercomputers. Utilizing its business consulting, technology and R&D expertise, IBM helps clients become "smarter" as the planet becomes more digitally interconnected. IBM invests more than $6 billion a year in R&D, just completing its 21st year of patent leadership. IBM Research has received recognition beyond any commercial technology research organization and is home to 5 Nobel Laureates, 9 US National Medals of Technology, 5 US National Medals of Science, 6 Turing Awards, and 10 Inductees in US Inventors Hall of Fame.
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