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. The purpose of this course is to introduce relational database concepts and help you learn and apply foundational knowledge of the SQL language. It is also intended to get you started with performing SQL access in a data science environment. The emphasis in this course is on hands-on and practical learning . As such, you will work with real databases, real data science tools, and real-world datasets. You will create a database instance in the cloud. Through a series of hands-on labs you will practice building and running SQL queries. You will also learn how to access databases from Jupyter notebooks using SQL and Python. No prior knowledge of databases, SQL, Python, or programming is required. Anyone can audit this course at no-charge. If you choose to take this course and earn the Coursera course certificate, you can also earn an IBM digital badge upon successful completion of the course. LIMITED TIME OFFER: Subscription is only $39 USD per month for access to graded materials and a certificate.
Databases and SQL for Data Science
ofrecido por
Learner Career Outcomes
38%
33%
Qué aprenderás
Create and access a database instance on cloud
Write basic SQL statements: CREATE, DROP, SELECT, INSERT, UPDATE, DELETE
Filter, sort, group results, use built-in functions, access multiple tables
Access databases from Jupyter using Python and work with real world datasets
Habilidades que obtendrás
Learner Career Outcomes
38%
33%
100 % en línea
Fechas límite flexibles
Nivel principiante
Aprox. 13 horas para completar
Inglés (English)
Programa - Qué aprenderás en este curso
Week 1 - Introduction to Databases and Basic SQL
In Week 1 you will be introduced to databases. You will create a database instance on the cloud. You will learn some of the basic SQL statements. You will also write and practice basic SQL hands-on on a live database.
Week 2 - Advanced SQL
By the end of this module you will: (1) earn how to use string patterns and ranges to search data, how to sort and group data in result sets, as well as (2) learn how to work with multiple tables in a relational database using join operations.
Week 3 - Accessing Databases using Python
After completing the lessons in this week, you will learn how to explain the basic concepts related to using Python to connect to databases and then create tables, load data, query data using SQL and analyze data using Python
Week 4: Course Assignment
As a hands-on Data Science assignment, you will be working with multiple real world datasets for the city of Chicago. You will be asked questions that will help you understand the data just like a data scientist would. You will be assessed both on the correctness of your SQL queries and results.
Principales revisiones sobre Databases and SQL for Data Science
Practice lab assignments were excellent in reinforcing my learning, they were just the right kind of challenging. This course has been the best one in the Data Science Professional series by far.
One of the best course I completed on Coursera. All the learning material is well organised and easy to understand. Also the non-graded sections regarding relational databases are interesting.
Instructor
Rav Ahuja
AI and Data Science Program DirectorAcerca de IBM
Preguntas Frecuentes
¿Cuándo podré acceder a las lecciones y tareas?
Una vez que te inscribes para obtener un Certificado, tendrás acceso a todos los videos, cuestionarios y tareas de programación (si corresponde). Las tareas calificadas por compañeros solo pueden enviarse y revisarse una vez que haya comenzado tu sesión. Si eliges explorar el curso sin comprarlo, es posible que no puedas acceder a determinadas tareas.
¿Qué recibiré si me suscribo a este Certificado?
Cuando te inscribes en un curso, obtienes acceso a todos los cursos del Certificado y te darán un certificado cuando completes el trabajo. Se añadirá tu Certificado electrónico a la página Logros. Desde allí, puedes imprimir tu Certificado o añadirlo a tu perfil de LinkedIn. Si solo quieres leer y visualizar el contenido del curso, puedes auditar el curso sin costo.
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