IBM
Introduction to Data Science Specialization
IBM

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.

Romeo Kienzler
Polong Lin
Alex Aklson

Instructors: Romeo Kienzler

91,017 already enrolled

Included with Coursera Plus

Get in-depth knowledge of a subject
4.7

(12,676 reviews)

Beginner level
No prior experience required
1 month
at 10 hours a week
Flexible schedule
Learn at your own pace
Get in-depth knowledge of a subject
4.7

(12,676 reviews)

Beginner level
No prior experience required
1 month
at 10 hours a week
Flexible schedule
Learn at your own pace

What you'll 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

Details to know

Shareable certificate

Add to your LinkedIn profile

Taught in English

See how employees at top companies are mastering in-demand skills

Placeholder

Advance your subject-matter expertise

  • Learn in-demand skills from university and industry experts
  • Master a subject or tool with hands-on projects
  • Develop a deep understanding of key concepts
  • Earn a career certificate from IBM
Placeholder
Placeholder

Earn a career certificate

Add this credential to your LinkedIn profile, resume, or CV

Share it on social media and in your performance review

Placeholder

Specialization - 4 course series

What is Data Science?

Course 111 hours4.7 (71,109 ratings)

What you'll learn

  • Define data science and its importance in today’s data-driven world.

  • Describe the various paths that can lead to a career in data science.

  • Summarize  advice given by seasoned data science professionals to data scientists who are just starting out.

  • Explain why data science is considered the most in-demand job in the 21st century.

Skills you'll gain

Category: Data Science
Category: Big Data
Category: Machine Learning
Category: Deep Learning
Category: Data Mining

Tools for Data Science

Course 218 hours4.5 (28,855 ratings)

What you'll learn

  • Describe the Data Scientist’s tool kit which includes: Libraries & Packages, Data sets, Machine learning models, and Big Data tools 

  • Utilize languages commonly used by data scientists like Python, R, and SQL 

  • Demonstrate working knowledge of tools such as Jupyter notebooks and RStudio and utilize their various features  

  • Create and manage source code for data science using Git repositories and GitHub. 

Skills you'll gain

Category: Data Science
Category: Python Programming
Category: Github
Category: Rstudio
Category: Jupyter notebooks

Data Science Methodology

Course 36 hours4.6 (20,241 ratings)

What you'll learn

  • Describe what a data science methodology is and why data scientists need a methodology.

  • Apply the six stages in the Cross-Industry Process for Data Mining (CRISP-DM) methodology to analyze a case study.

  • Evaluate which analytic model is appropriate among predictive, descriptive, and classification models used to analyze a case study.

  • Determine appropriate data sources for your data science analysis methodology.

Skills you'll gain

Category: Data Science
Category: Data Analysis
Category: CRISP-DM
Category: Methodology
Category: Data Mining

Databases and SQL for Data Science with Python

Course 420 hours4.7 (20,098 ratings)

What you'll learn

  • Analyze data within a database using SQL and Python.

  • Create a relational database and work with multiple tables using DDL commands.

  • Construct basic to intermediate level SQL queries using DML commands.

  • Compose more powerful queries with advanced SQL techniques like views, transactions, stored procedures, and joins.

Skills you'll gain

Category: Python Programming
Category: Cloud Databases
Category: Relational Database Management System (RDBMS)
Category: SQL
Category: Jupyter notebooks

Instructors

Romeo Kienzler
IBM
10 Courses687,279 learners

Offered by

IBM

Get a head start on your degree

Placeholder

Degree credit eligible

This Specialization has ACE® recommendation. It is eligible for college credit at participating U.S. colleges and universities. Note: The decision to accept specific credit recommendations is up to each institution.

Why people choose Coursera for their career

Felipe M.
Learner since 2018
"To be able to take courses at my own pace and rhythm has been an amazing experience. I can learn whenever it fits my schedule and mood."
Jennifer J.
Learner since 2020
"I directly applied the concepts and skills I learned from my courses to an exciting new project at work."
Larry W.
Learner since 2021
"When I need courses on topics that my university doesn't offer, Coursera is one of the best places to go."
Chaitanya A.
"Learning isn't just about being better at your job: it's so much more than that. Coursera allows me to learn without limits."

New to Data Analysis? Start here.

Placeholder

Open new doors with Coursera Plus

Unlimited access to 7,000+ world-class courses, hands-on projects, and job-ready certificate programs - all included in your subscription

Advance your career with an online degree

Earn a degree from world-class universities - 100% online

Join over 3,400 global companies that choose Coursera for Business

Upskill your employees to excel in the digital economy

Frequently asked questions