About Course
Core Content & Key Learning Areas
The curriculum integrates statistical analysis, programming, and advanced modeling to extract value from data:
Programming for Data Science: An essential proficiency in Python for data manipulation and constructions of the models.
Statistics and Mathematical Foundations: A solid understanding of probability, statistical inference, hypothesis testing, and linear algebra needed for data analysis.
Data Visualization and Business Intelligence: Use tools to create visualizations and dashboards for data storytelling and informed decision making.
Data Collection and Processing: Key methods for cleaning, transforming, organizing, and preparing raw data for analysis and model training.
Machine Learning: Implementing, training, and evaluating basic Machine Learning algorithms for classification, regression, and clustering tasks.
AI and Deep Learning Fundamentals: An introduction to the principles of artificial intelligence and the basic concepts of neural networks and deep learning models.
Career Pathways
DSAI graduates are equipped to turn raw data into actionable insights and build intelligent systems. Your career path is centered on analysis and prediction:
• Junior Data Analyst
• Business Intelligence (BI) Analyst
• Junior Data Scientist
• Data Visualization Specialist
• AI/ML Data Preparator