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

Included with Coursera Plus

Get in-depth knowledge of a subject
4.7

(13,371 reviews)

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

(13,371 reviews)

Beginner level
No prior experience required
4 weeks to complete
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

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Taught in English
61 practice exercises

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  • Develop a deep understanding of key concepts
  • Earn a career certificate from IBM

Specialization - 4 course series

What is Data Science?

What is Data Science?

Course 111 hours

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

Data Science, Big Data, Cloud Computing, Digital Transformation, Data Analysis, Deep Learning, Machine Learning, Data Literacy, Data Mining, Data-Driven Decision-Making, and Artificial Intelligence
Tools for Data Science

Tools for Data Science

Course 218 hours

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

Jupyter, GitHub, R Programming, Git (Version Control System), Machine Learning, Data Visualization Software, Python Programming, Cloud Computing, Big Data, Query Languages, R (Software), Statistical Programming, Data Science, Computer Programming Tools, Version Control, Development Environment, Open Source Technology, Other Programming Languages, and IBM Cloud
Data Science Methodology

Data Science Methodology

Course 36 hours

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

Predictive Modeling, Data Cleansing, Data Collection, Data Quality, Business Analysis, Feature Engineering, Data Modeling, Data Transformation, User Feedback, Data Processing, Jupyter, Peer Review, Decision Tree Learning, Data Analysis, Business Requirements, Data Science, Software Development Methodologies, Data Mining, and Stakeholder Engagement

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

SQL, Pandas (Python Package), Databases, Data Manipulation, Data Analysis, Relational Databases, Jupyter, Python Programming, Query Languages, Stored Procedure, and Transaction Processing

Earn a career certificate

Add this credential to your LinkedIn profile, resume, or CV. Share it on social media and in your performance review.

Get a head start on your degree

When you complete this Specialization, you may be able to have your learning recognized for credit if you are admitted and enroll in one of the following online degree programs.¹

 
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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. 

Instructors

Romeo Kienzler
IBM
10 Courses792,635 learners

Offered by

IBM

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