There are several reasons why learning or improving SQL (Structured Query Language) can be beneficial for data science:
SQL is the standard language for working with relational databases, which are a common source of data for data science projects. By learning SQL, you'll be able to easily retrieve, manipulate, and analyze the data stored in these databases.
SQL allows you to efficiently work with large datasets. When working with data science projects, it is common to deal with datasets that are too large to fit into memory. SQL provides powerful tools for filtering, grouping, and aggregating large datasets, so you can work with subsets of the data that are small enough to fit into memory.
SQL can help you to understand the underlying data better. Even though SQL is a programming language, it is declarative, unlike most of the general-purpose programming languages like Python, C++ or Java. It means the code you write will tell the SQL engine what you want and the engine will take care of the HOW to get the results, so it will help to get more understanding about the dataset, its structure and its constraints
SQL is a good tool for data preparation, cleaning and validation. Since it is a powerful tool to manipulate and filter the data, you could use it to prepare your dataset to a better shape before applying any statistical or machine learning models.
SQL can be a valuable skill in the job market. Many companies store data in relational databases, and SQL knowledge is often a required or preferred skill for data science positions.
In summary, learning SQL can be a valuable addition to your data science toolkit, as it allows you to efficiently work with large datasets and can be a valuable skill in the job market : Survey
This course is addressed to Data scientists, programmers, bioinformaticians, researchers or students.
At the end of the course, the participants are expected to:
This course is addressed to data scientists, programmers, bioinformaticians, researchers or students and there is no requirement.
You are required to bring your own laptop with administrative rights. You will be asked to download and install a database client prior to the tutorial.
The registration fees for academics are 100 CHF and 500 CHF for for-profit companies.
You will be informed by email of your registration confirmation. Upon reception of the confirmation email, participants will be asked to confirm attendance by paying the fees within 5 days.
Applications close on 10/04/2024. Deadline for free-of-charge cancellation is set to 10/04/2024. Cancellation after this date will not be reimbursed. Please note that participation in SIB courses is subject to our general conditions.
This course will be streamed.
It will start at 9:00 and end around 17:00. Precise information will be provided to the participants in due time.
Coordination: Grégoire Rossier
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Please note that participation in SIB courses is subject to our general conditions.
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