SQL for Data Science
Gain practical, hands-on experience working with SQL in a data science environment. Use Jupyter Notebooks to perform SQL access to relational databases.
Develop your skills in this critical language for data science and build your competence in this exciting field.
Earn your certificate
Once you have completed this course, you will earn your certificate.Preview digital certificate
This course is part of the following program :
You'll learn with these experts
Data science is composed of a variety of elements including statistical analysis, programming tools, algorithms, and machine learning techniques. It includes the application of several methodologies, including statistics, scientific methods, artificial intelligence (AI) and data analysis.
1. Facebook: Facebook is now the world's most popular social networking platform. It has millions of users across the globe and is always undertaking large-scale quantitative research utilizing data science to learn more about social relationships. Face recognition and text analysis are two fundamental applications of deep learning, a cutting-edge data science technology that Facebook employs. Facebook also uses powerful neural networks to classify faces in photos. Plus, it uses their Deep Text engine that was created in-house to classify written words.
2. Amazon: Amazon has always sought to be a consumer platform that constantly improves client satisfaction. By employing data science methodologies, Amazon utilizes predictive shipping technologies to analyze massive quantities of data to predict what products people will buy. It tracks buying habits and stores products in nearby warehouses where possible. Amazon also monitors user behavior, order history, rival prices, availability of the product, and so on. Fraud detection is another issue that all e-commerce platforms face. As a result, Amazon has developed its own techniques and algorithms. Plus Amazon uses workflow data to increase warehouse product packing and packaging line productivity.
Once you’ve completed SQL for Data Science, you will be able to:
- Create a database in a cloud.
- Apply foundational knowledge of SQL language.
- Analyze data using Python.
- Sort and group data in result sets and by data type.
- Use string patterns and ranges to query data.
Data is a valuable asset, and data-driven business processes are helping to boost efficiency and innovation. As a result, the need for data scientists with extraordinary talents and strong skills is growing, and firms are willing to offer excellent remuneration packages to attract the best candidates. The following are some well-known data science service providers:
- JP Morgan Chase