Data Science & Data Analytics Professional Programs

The Fundamentals of Generative AI module introduces learners to the rapidly evolving field of AI that focuses on creating new, original content such as text, images, audio, and code. The module covers the theoretical foundations, key algorithms, and practical applications of generative AI in real-world scenarios.

The Artificial Intelligence (AI) module introduces learners to the principles, techniques, and applications of AI in solving real-world problems. The module covers both the theoretical foundations and practical implementations of intelligent systems, providing a strong base for advanced analytics and machine learning projects.

The Machine Learning module provides learners with the core theoretical knowledge and practical skills required to build predictive models and intelligent data-driven systems. The module covers the full machine learning workflow, from data preprocessing and feature engineering to model training, evaluation, and deployment.

The Statistics for Data Science module builds the analytical foundation needed to understand, interpret, and model data effectively. This module introduces students to essential statistical concepts used in real-world data analysis, predictive modeling, and decision-making.

The SQL module provides students with essential skills for managing, querying, and analyzing data stored in relational databases. Learners are introduced to database fundamentals, including tables, relationships, schemas, and normalization. The module focuses on writing efficient SQL queries to retrieve, filter, sort, and manipulate data.

This course provides comprehensive training in Microsoft Excel, starting from basic spreadsheet operations and advancing to complex data analysis techniques. Students will learn essential functions, formulas, charts, data management tools, and reporting features. The advanced module covers pivot tables, advanced formulas, dashboards, macros, and automation techniques for professional-level data analysis. By the end of the course, learners will be able to efficiently organize, analyze, and present data for business decision-making.

The Python Programming module builds the essential programming foundation required for data science and analytics. Students learn Python from the ground up, covering core concepts such as variables, data types, operators, conditional statements, loops, functions, and object-oriented programming. The module emphasizes writing clean, efficient code that supports data manipulation, automation, and analytical workflows.

The Excel & Advanced Excel module equips learners with strong foundational and analytical skills using one of the most essential tools in data-driven industries. The module begins with core Excel functions such as data entry, formatting, formulas, functions, charts, and basic data organization techniques. Students learn how to efficiently manage and manipulate datasets using tables, sorting, filtering, and conditional formatting.