School of Data Science

About the School

Welcome to the School of Data Science, an institution of CERED dedicated to educating the next generation of data scientists and analysts. Our school is at the forefront of data science education, offering cutting-edge programs and courses designed to equip students with the skills and knowledge needed to thrive in the data-driven world.

Our aim is to provide a robust and comprehensive education in data science, fostering innovation, critical thinking, and problem-solving skills. We aim to produce graduates who are not only proficient in technical skills but also possess the ability to apply data science techniques to real-world challenges across various industries.

Courses Offered

At the School of Data Science, we offer a wide array of courses that cover the essential tools and techniques in data science. Our curriculum includes:

Python for Data Science: This course provides a solid foundation in Python programming, focusing on its applications in data analysis, machine learning, and data visualization. Students learn to manipulate data, perform statistical analyses, and create sophisticated models using popular Python libraries such as NumPy, pandas, and scikit-learn.

R Programming: In this course, students explore the R programming language, widely used in statistical computing and graphics. The curriculum covers data manipulation, statistical modeling, and data visualization, equipping students with the skills to analyze complex data sets and generate meaningful insights.

SPSS (Statistical Package for the Social Sciences): Our SPSS course introduces students to one of the most widely used software packages for statistical analysis in social sciences. Students learn to perform various statistical tests, data management, and data visualization, making SPSS a valuable tool for research and analysis.

SQL (Structured Query Language): This course covers SQL, the standard language for managing and manipulating databases. Students learn to write complex queries, manage database structures, and perform data extraction and transformation tasks, essential for any data-driven role.

Tableau: In the Tableau course, students learn to create interactive and shareable dashboards that present data in a visually appealing and accessible manner. Tableau is a powerful tool for data visualization, helping students communicate insights effectively to stakeholders.

Excel for Data Analysis: This course emphasizes the use of Microsoft Excel in data analysis, teaching students advanced techniques in data manipulation, statistical analysis, and visualization. Excel remains a fundamental tool in many data-related roles, and proficiency in it is highly valued.

Machine Learning with TensorFlow: Students delve into the world of machine learning with TensorFlow, an open-source platform developed by Google. This course covers the basics of machine learning, deep learning, and neural networks, enabling students to build and deploy machine learning models.

Data Visualization with D3.js: In this course, students learn to create dynamic and interactive data visualizations using D3.js, a powerful JavaScript library. This skill is essential for presenting complex data in an intuitive and engaging way.