Data Ethics and Governance
Focuses on the responsible use of data, covering topics like data privacy, ethics, and governance standards.
SQL for Data Science
Focuses on database querying using SQL for data analysis. Teaches data manipulation, joins, and aggregations for extracting insights from databases.
AI & Deep Learning
An introduction to artificial intelligence, neural networks, and deep learning. Focuses on building basic models for real-world applications.
Statistics for Data Science
Covers statistical methods essential for data scientists, including probability distributions, hypothesis testing, and regression analysis.
Data Mining Techniques
Teaches techniques for extracting patterns and valuable insights from large datasets. Focuses on classification, clustering, and association rule mining.
Big Data Technologies
Provides an overview of big data platforms, including Hadoop and Spark, and teaches how to process large datasets.
Data Visualization with Tableau
Teaches students how to create interactive data visualizations using Tableau. Focuses on dashboards, charts, and real-time analytics.
Machine Learning Basics
Provides an introduction to machine learning algorithms, their applications, and how to implement them. Covers supervised and unsupervised learning.
Python for Data Science
Focuses on Python programming for data analysis. Covers Python libraries (NumPy, Pandas) essential for data manipulation and analysis.
Introduction to Data Science
This course introduces core concepts and applications of data science. Students will learn data handling, pattern recognition, and decision-making.
